VEHICLE

RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional Application No. 62/754,508, filed on November 1, 2018; the contents of which are incorporated herein by reference.

FIELD OF THE INVENTION

[0002] This application relates to localizing a subsea unmanned vehicle, and, more particularly, to a system and method for localizing a subsea unmanned vehicle.

BACKGROUND

[0003] In the oil and gas industry, underwater vehicles are used for subsea infrastructure monitoring and maintenance. For example, application fields include the inspection of offshore infrastructure Inspection, Maintenance and Repair (“IMR”) and offshore well construction monitoring (e.g., blow out preventer“BOP” and riser monitoring). Further, examples of IMR include pipe inspection, manifold and subsea trees inspection and repair. Other fields such as oceanographic surveys, underwater fiber optics telecom cables or offshore wind turbines inspections may also benefit from this technology.

[0004] However, the above noted applications require the mobilization of at least one floating infrastructure and at least one underwater vehicle. The floating infrastructure may be of different type such as, but not limited to, a ship, a floating rig, a floating production storage and offloading (“FPSO”), an unmanned surface autonomous vehicle. The floating infrastructure can be used to launch the at least one underwater vehicle and/or control the operations and recover the at least one underwater vehicle.

[0005] Further, targeting the applications involves the deployment of a wide range of underwater robots. Remote Operated Vehicles (“ROVs”) are used for inspection and monitoring activity. The ROVs may be highly maneuverable with, for example, up to 6 degrees of freedom. ROVs typically are tethered in order to receive power and high-bandwidth telemetry. Unfortunately, deployment of the tether can be expensive and complex due to the associated ship infrastructure and due to the management of the entanglement risks. Further, for deep-water operations, the ROV operators usually deploy multiple ROVs to manage the tether risks.

[0006] As a result, there is a need to develop un-tethered autonomous vehicles. Un-tethered vehicles have mainly been developed for long range missions with“torpedo-shape” vehicle, usually called Autonomous Underwater Vehicle (“AUV”). The AUVs have a limited number of degrees of freedom, which results in the AUVs not being able to hover.

[0007] However, all of the above noted applications require a good estimate of the position of the underwater vehicles, which is challenging because satellite based Global Navigation Satellite System (“GNSS”) does not work underwater.

SUMMARY OF DISCLOSURE

[0008] This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

[0009] In an embodiment of the present disclosure, a subsea unmanned vehicular localization system is provided. The system may include a subsea unmanned vehicle. The subsea unmanned vehicle may include at least three receiver elements. The subsea unmanned vehicle may also include a multi-channel data acquisition tool. The multi-channel data acquisition tool may be configured to synchronize one or more signals associated with a plurality of channels. The subsea unmanned vehicle may also include a processing module. The processing module may be configured to estimate a location of the subsea unmanned vehicle.

[0010] One or more of the following features may be included. The at least three receiver elements may be configured to receive one or more acoustic signals transmitted via an acoustic transmitter located on a stationary reference unit. The at least three receiver elements may be configured to receive one or more acoustic signals transmitted via an acoustic transmitter located on a moving reference unit. The subsea unmanned vehicle may be configured to transmit the estimated location of the subsea unmanned vehicle to a reference unit via a communication link. The estimated location may be transmitted via a communication link using one or more existing telemetry infrastructures. The subsea unmanned vehicle may include a navigation system. [0011] In another embodiment of the present disclosure, a method for localizing a subsea unmanned vehicular system is provided. The method for localizing a subsea unmanned vehicular system may include receiving one or more acoustic signals on a subsea unmanned vehicle from an acoustic transmitter located on a reference unit. The method for localizing a subsea unmanned vehicular system may include estimating a location of the subsea unmanned vehicle using the received one or more acoustic signals.

[0012] One or more of the following features may be included. The estimated location of the subsea unmanned vehicle may be used to adapt one or more behaviors of the subsea unmanned vehicle. One or more obstructions in a path of the one or more acoustic signals, transmitted, via an acoustic transmitter located on the reference unit, to the subsea unmanned vehicle may be detected and accounted for. Estimating the location of the subsea unmanned vehicle may include calculating one or more broad angles using the one or more acoustic signals. Estimating the location of the subsea unmanned vehicle may include calculating a depth of the subsea unmanned vehicular system using the one or more calculated broad angles. The one or more calculated broad angles may be defined by the direction of the subsea unmanned vehicle relative to the reference unit. Estimating the location of the subsea unmanned vehicle may include calculating a time of travel between the time the one or more acoustic signals are sent from the acoustic transmitter located on the reference unit and the time the one or more acoustic signals are received by the subsea unmanned vehicular system. The estimated location of the subsea unmanned vehicle may be transmitted to the reference unit via a communication link. The subsea unmanned vehicle and reference unit may both include a clock. Each of the clocks may be configured to be synchronized with one another.

[0013] In another embodiment of the present disclosure, a method for localizing a subsea unmanned vehicular system is provided. The method for localizing a subsea unmanned vehicular system may include receiving, via an acoustic transmitter located on a reference unit, one or more acoustic signals on a subsea unmanned vehicular system. The method for localizing a subsea unmanned vehicular system may include calculating one or more broad angles using the one or more acoustic signals. The method for localizing a subsea unmanned vehicular system may include calculating a sound velocity profile using the one or more acoustic signals. The method for localizing a subsea unmanned vehicular system may include estimating a location of the subsea unmanned vehicular system using the calculated broad angles and calculated sound velocity profile.

[0014] One or more of the following features may be included. One or more behaviors of the subsea unmanned vehicular system may be altered using the calculated sound velocity profile. The estimated location of the subsea unmanned vehicle may be used to adapt one or more behaviors of the subsea unmanned vehicle. One or more obstructions in a path of the one or more acoustic signals, transmitted, via an acoustic transmitter located on the reference unit, to the subsea unmanned vehicle may be detected and accounted for. The estimated location of the subsea unmanned vehicle may be transmitted to the reference unit via a communication link. The estimated location may be transmitted via a communication link using one or more existing telemetry infrastructures. The reference unit may be a ship. The reference unit may be a piece of subsea equipment.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention is illustrated by way of example, and not limitation, in the figures of the accompanying drawings in which like references indicate similar elements and in which:

[0016] FIG. 1 is a diagram depicting an embodiment of a system in accordance with the present disclosure;

[0017] FIG. 2 is diagram of a subsea unmanned vehicle localization system, according to an embodiment of the present disclosure;

[0018] FIG 3. is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0019] FIG. 4 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0020] FIG. 5 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0021] FIG. 6 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0022] FIG. 7 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure; [0023] FIG. 8 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0024] FIG. 9 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0025] FIG. 10 is a block diagram of a subsea unmanned vehicle localization method in accordance with the present disclosure;

[0026] FIG. 1 1 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0027] FIG. 12 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0028] FIG. 13 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0029] FIG. 14 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0030] FIG. 15 is a block diagram a of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0031] FIG. 16 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0032] FIG. 17 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0033] FIG. 18 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0034] FIG. 19 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0035] FIG. 20 is a diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0036] FIG. 21 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure;

[0037] FIG. 22 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure; [0038] FIG. 23 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure; and

[0039] FIG. 24 is a block diagram of a subsea unmanned vehicle localization system in accordance with the present disclosure.

DESCRIPTION

[0040] The discussion below is directed to certain implementations and/or embodiments. It is to be understood that the discussion below may be used for the purpose of enabling a person with ordinary skill in the art to make and use any subject matter defined now or later by the patent “claims” found in any issued patent herein.

[0041] It is specifically intended that the claimed combinations of features not be limited to the implementations and illustrations contained herein, but include modified forms of those implementations including portions of the implementations and combinations of elements of different implementations as come within the scope of the following claims. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions may be made to achieve the developers' specific goals, such as compliance with system-related and business related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. Nothing in this application is considered critical or essential to the claimed invention unless explicitly indicated as being "critical" or "essential."

[0042] It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms may be used to distinguish one element from another. For example, a first object or step could be termed a second object or step, and, similarly, a second object or step could be termed a first object or step, without departing from the scope of the disclosure. The first object or step, and the second object or step, are both objects or steps, respectively, but they are not to be considered a same object or step.

[0043] Referring to FIG. 1, there is shown a subsea unmanned vehicle localization process 10. Subsea unmanned vehicle localization process 10 may be located within a subsea unmanned vehicle (e.g., subsea unmanned vehicle 302). Further, subsea unmanned vehicle localization process may reside on and may be executed by computer 12, which may be connected to network 14 (e.g., the Internet or a local area network). Examples of computer 12 may include, but are not limited to: a personal computer, a server computer, a series of server computers, a mini computer, and a mainframe computer. Computer 12 may be a web server (or a series of servers) running a network operating system, examples of which may include but are not limited to: ANDROID™, iOS™, Microsoft® Windows® Server; Novell® NetWare®; or Red Hat® Linux®, for example. (Microsoft and Windows are registered trademarks of Microsoft Corporation in the United States, other countries or both; Novell and NetWare are registered trademarks of Novell Corporation in the United States, other countries or both; Red Hat is a registered trademark of Red Hat Corporation in the United States, other countries or both; and Linux is a registered trademark of Linus Torvalds in the United States, other countries or both.) Additionally /alternatively, subsea unmanned vehicle localization process 10 may reside on and be executed, in whole or in part, by a client electronic device, such as a personal computer, notebook computer, personal digital assistant, or the like.

[0044] The instruction sets and subroutines of subsea unmanned vehicle localization process 10, which may include one or more software modules, and which may be stored on storage device 16 coupled to computer 12, may be executed by one or more processors (not shown) and one or more memory modules (not shown) incorporated into computer 12. Storage device 16 may include various types of memory systems. For example, but not limited to, storage device 16 may include: a hard disk drive; a solid state drive, a tape drive; an optical drive; a RAD array; a random access memory (RAM); a read-only memory (ROM). Storage device 16 may include various types of files and file types.

[0045] Computer 12 may execute a web server application, examples of which may include but are not limited to: Microsoft IIS, Novell Webserver™, or Apache® Webserver, that allows for HTTP (e.g., HyperText Transfer Protocol) access to computer 12 via network 14 (Webserver is a trademark of Novell Corporation in the United States, other countries, or both; and Apache is a registered trademark of Apache Software Foundation in the United States, other countries, or both). Network 14 may be connected to one or more secondary networks (e.g., network 18), examples of which may include but are not limited to: a local area network; a wide area network; or an intranet, for example. [0046] Subsea unmanned vehicle localization process 10 may be a stand-alone application, or may be an applet / application / script that may interact with and/or be executed within application 20. In addition / as an alternative to being a server-side process, subsea unmanned vehicle localization process 10 may be a client-side process (not shown) that may reside on a client electronic device (described below) and may interact with a client application (e.g., one or more of client applications 22, 24, 26, 28). Further, subsea unmanned vehicle localization process 10 may be a hybrid server-side / client-side process that may interact with application 20 and a client application (e.g., one or more of client applications 22, 24, 26, 28). As such, subsea unmanned vehicle localization process 10 may reside, in whole, or in part, on computer 12 and/or one or more client electronic devices. In some embodiments, subsea unmanned vehicle localization process 10 and/or application 20 may be independent web applications accessible via the Internet. In some embodiments, subsea unmanned vehicle localization process 10 and/or application 20 may be executable applications within a web page or web site accessible via the Internet.

[0047] The instruction sets and subroutines of application 20, which may be stored on storage device 16 coupled to computer 12 may be executed by one or more processors (not shown) and one or more memory modules (not shown) incorporated into computer 12.

[0048] The instruction sets and subroutines of client applications 22, 24, 26, 28, which may be stored on storage devices 30, 32, 34, 36 (respectively) coupled to client electronic devices 38, 40, 42, 44 (respectively), may be executed by one or more processors (not shown) and one or more memory modules (not shown) incorporated into client electronic devices 38, 40, 42, 44 (respectively). Storage devices 30, 32, 34, 36 may include but are not limited to: hard disk drives; solid state drives, tape drives; optical drives; RAID arrays; random access memories (RAM); read only memories (ROM), compact flash (CF) storage devices, secure digital (SD) storage devices, and memory stick storage devices. Examples of client electronic devices 38, 40, 42, 44 may include, but are not limited to, personal computer 38, laptop computer 40, mobile computing device 42 (such as a smart phone, netbook, or the like), notebook computer 44, for example. Using client applications 22, 24, 26, 28, users 46, 48, 50, 52 may access application 20 and may allow users to e.g., utilize subsea unmanned vehicle localization process 10.

[0049] Users 46, 48, 50, 52 may access application 20 directly through the device on which the client application (e.g., client applications 22, 24, 26, 28) is executed, namely client electronic devices 38, 40, 42, 44, for example. Users 46, 48, 50, 52 may access application 20 directly through network 14 or through secondary network 18. Further, computer 12 (e.g., the computer that executes application 20) may be connected to network 14 through secondary network 18, as illustrated with phantom link line 54.

[0050] The various client electronic devices may be directly or indirectly coupled to network 14 (or network 18). For example, personal computer 38 is shown directly coupled to network 14 via a hardwired network connection. Further, notebook computer 44 is shown directly coupled to network 18 via a hardwired network connection. Laptop computer 40 is shown wirelessly coupled to network 14 via wireless communication channel 56 established between laptop computer 40 and wireless access point (e.g., WAP) 58, which is shown directly coupled to network 14. WAP 58 may be, for example, an IEEE 802.1 la, 802.1 lb, 802.1 lg, Wi-Fi, and/or Bluetooth device that is capable of establishing wireless communication channel 56 between laptop computer 40 and WAP 58. Mobile computing device 42 is shown wirelessly coupled to network 14 via wireless communication channel 60 established between mobile computing device 42 and cellular network / bridge 62, which is shown directly coupled to network 14.

[0051] As is known in the art, all of the IEEE 802.1 lx specifications may use Ethernet protocol and carrier sense multiple access with collision avoidance (e.g., CSMA/CA) for path sharing. The various 802.1 lx specifications may use phase-shift keying (e.g., PSK) modulation or complementary code keying (e.g., CCK) modulation, for example. As is known in the art, Bluetooth is a telecommunications industry specification that allows e.g., mobile phones, computers, and personal digital assistants to be interconnected using a short-range wireless connection.

[0052] Client electronic devices 38, 40, 42, 44 may each execute an operating system, examples of which may include but are not limited to Microsoft Windows, Microsoft Windows CE®, Red Hat Linux, or other suitable operating system. (Windows CE is a registered trademark of Microsoft Corporation in the United States, other countries, or both).

[0053] With regards to specific terminology used in the present disclosure, the term“localization” refers to the positioning of an object in a local reference. For example, the local reference may be associated with a reference unit. Additionally, the term positioning refers to global positioning using an earth based referential. Further, the terms“position” and“location” used in this disclosure are intended to be synonymous. A mission of the underwater vehicle refers to a set of actions of the vehicle to achieve some objectives. A typical mission may include, for example and not to be construed as a limitation, a dive, some inspection of subsea equipment and a surface. In resident systems, a mission may be, for example and not to be construed as a limitation, a set of actions.

[0054] Further, the present disclosure utilizes acoustic signals for illustration purposes and, therefore, the present disclosure should not be understood to be limited only to the use of acoustic signals.

[0055] Regarding localizing a subsea underwater vehicle relative to a reference unit (e.g., a surface ship), or inversely for localizing a surface ship (hereinafter“ship”) relative to an underwater vehicle, Short BaseLine (SBL) and USBL may be used. A relative location of the subsea unmanned vehicle may be obtained with a combination of a measured distance from the ship to the subsea unmanned vehicle and the estimation of broad angles between the ship and the subsea unmanned vehicle. The distance may be estimated using a two-way travel time. The broad angles may be estimated by exploiting one or more delays of arrival of one or more acoustic waves in between one or more elements of the array. For example, SBL and Long Base Line (LBL) may rely on the one or more delays of time of arrival of the one or more acoustic waves sent from the underwater vehicle. However, the ability to accurately estimate the time of arrivals may be limited in this scenario. The estimation may be impacted by one or more of noise and reflections. Further, the estimation may be intrinsically limited by a bandwidth of the a signal. A Gabor limit may provide a lowest error bound on a timing estimate for a given bandwidth, as illustrated in Equation 1 below with regards to a lower bound of a timing error:

Additionally, SBL and LBL may poses great calibration challenges due to calculating broad angles being sensitive to errors on a location of the array elements.

[0056] Additionally, the USBL may rely on a phase shift on the elements of the array of one of the one or more acoustic signals sent from a subsea unmanned vehicle. To avoid phase ambiguities, the distance between one or more sensors may be lower than half a wavelength. The phase shifts may depend on a frequency. Therefore, the signal may need to be decomposed using a Fourier Transform, especially for wideband signals. However, the noted techniques may be sensitive to multipath, which may lead to some complexity. Specifically, multipath may occur where an acoustic signal takes one or more paths from an acoustic transmitter to an acoustic receiver and the path includes one or more impedances. For example, the path may include impedances such as between one or more of water and air, water and seabed, and water and a metallic structure. When multipath occurs, an acoustic receiver may acquire multiple version of an acoustic signal with one or more of different time delays, different amplitudes and different doppler characteristics.

[0057] Regarding potential challenges, the array of receiver elements of SBL and USBL may be highly integrated on the ship, which may pose challenges such as, for example, the needing to correct calculated broad angles estimate using the orientation of the ship. For example, for two kilometers apart of the ship and the subsea unmanned vehicle, a location estimate within 10 meters of accuracy may require a broad angle estimate within 0.1 degree of accuracy. As a result, a motion composition of the boat is critical. Therefore, expensive INS may be coupled to the positioning system. Further, acoustic noise on the ship may be high (e.g., propellers, AC, operations on the boat, etc.), and is often higher than the acoustic noise around the underwater vehicle. Therefore, the range of SBL and USBL may often be limited by the noise on the ship. Additionally, calibration of the array on the ship is critical. Therefore, USBL and SBL may be used on ships that have been designed to support such technology. For example, hulls may be used that are calibrated for particular array design. As a result, SBL and USBL may not be able to be used on a“ship of opportunity.” Additionally, the estimated location of a subsea unmanned vehicle typically requires an active acoustic transmitter on the subsea unmanned vehicle. Further, an array of transducers typically is based on a reference unit itself rather than on a subsea unmanned vehicle. An example of SBL and USBL is illustrated in FIG. 2 where SBL is denoted as 202 and USBL is denoted at 204.

[0058] In response to the above challenges, in some embodiments of the present disclosure, a subsea unmanned vehicular localization system is provided, as illustrated in FIG. 3. The system may include subsea unmanned vehicle 302. Subsea unmanned vehicle 302 may include receiver array 304. Receiver array 304 may include at least three receiver elements. Subsea unmanned vehicle 302 may also include a multi-channel data acquisition tool. The multi-channel data acquisition tool may be configured to synchronize one or more signals associated with a plurality of channels. Subsea unmanned vehicle 302 may also include a processing module. The processing module may be configured to estimate a location of subsea unmanned vehicle 302. Subsea unmanned vehicle 302 may be configured to receive one or more acoustic signals 310 from an acoustic transmitter 308 located on a reference unit 306 through an acoustic propagation path. Reference unit 306 is denoted as a ship in FIG. 2, which is for illustration purposes and is not to be construed as to limit reference unit 306 only to a ship.

[0059] Regarding estimating a location of subsea unmanned vehicle 302, a plurality of instruments may provide an estimate of the location. The plurality of instruments may use a wide range of physics principles. However, each of the plurality of instruments have benefits and limitations. Therefore, a successful location estimate lies in the combination of the right instruments for each scenario. For example, the plurality of instruments may include a plurality of positioning instruments, which may include a pressure gauge onboard the subsea unmanned vehicle, which may provide an image of depth when a water density profile is known. Further, a pressure sensor may be used to provide a measure of depth, giving important information for estimating a location of subsea unmanned vehicle 302. A lock may be used with the pressure sensor 402, as illustrated in FIG. 4. Further, FIG. 4 illustrates travel time of two-way 404 and one-way 406 propagation of one or more acoustic signals 310.

[0060] Further, a Doppler Velocity Log (DVL) may also be included, which may provide a local altitude of subsea unmanned vehicle 302. The DVL may provide a velocity of subsea unmanned vehicle 302 relative to a seafloor. However, in order for the DVL to work well, subsea unmanned vehicle 302 must be relatively close in proximity to a seabed. For example, subsea unmanned vehicle 302 may be less than 50 meters from the seabed. An Inertial Measurement Unit (IMU) may also be included. The IMU may be made of one or more of the following: one or more accelerometers (motion sensors), one or more gyroscopes (rotation sensors), and one or more magnetometers (magnetic sensors). The IMU may provide direct measurement of an orientation of subsea unmanned vehicle 302. For example, yaw, pitch, and roll measurements may be provided. The location may be calculated using dead reckoning, which may include double integration of the acceleration. However, drift may occur. Further, displacement due to water current may not be able to be accurately estimated by the IMU. Additionally, Simultaneous Localization And Mapping (SLAM) may be include. SLAM may be based on feature recognition. As a result, SLAM may provide a location relative to one or more features of an environment. Further, one or more acoustic baselines may provide a location estimate relative to a location of one or more acoustic transmitters 308. The one or more acoustic baselines may include one or more of SBL, Ultra Short BaseLine (USBL), or LBL. SBL may include deploying multiple receiver elements on a surface of one or more infrastructures such as, for example, a boat including an inter-element distance of a few meters. On the other hand, in USBL, an array of receiver elements may be deployed on a surface infrastructure, such as, for example and not to be construed as a limitation, a boat, with an inter-element distance of less than 10 centimeters. Further, LBL may include deploying multiple acoustic transmitters. The multiple acoustic transmitters may be deployed far apart from one another. For example, the multiple acoustic transmitters may be deployed at least 100 meters apart from one another.

[0061] Further, when estimating a most likely location of a subsea unmanned vehicle, a sensor fusion may be used. The sensor fusion may include a combination of measurements to compute the most likely location estimate of subsea unmanned vehicle 302. In general, sensor fusion may be done on a vehicle using a Bayesian filter. The Bayesian filter may be a Kalman filter, an extended Kalman filter, or particle filter. The filter may often be designed to operate based on IMU data by default. Other measurements may aid in order to compensate for the drift. The filter and the IMU together are denoted as Inertial Navigation System (INS).

[0062] In the above embodiments, the configuration of subsea unmanned vehicular localization system 10 may be denoted as utilizing inverted Short BaseLine (“iSBL”). As will be described in further detail below, iSBL may use one or more passive acoustic array receivers on subsea unmanned vehicle 302. The one or more passive acoustic array receivers may be onboard subsea unmanned vehicle 302. As a result, the one or more passive acoustic array receivers may not need to transmit one or more acoustic signals to reference unit 306 (i.e., a ship). In this context, “inverted” refers to the one or more passive acoustic array receivers being located on subsea unmanned vehicle 302.

[0063] In accordance with the above embodiments, each of the at least three receiver elements may meet one or more technological requirements. For example, each of the at least three receiver elements may need to meet one or more sufficient sensitivity requirement for a required bandwidth. The sufficient sensitivity may be in the range of 20kHz and 80kHz. In this example, flatness of the a response may not be a major constraint. Additionally, each of the at least three receiver elements may need to meet sufficient dynamics to cover all operating envelope. This may be in terms of signal amplitude. Further, each of the at least three receiver elements may need to meet sufficient Signal to Noise Ratio (SNR) ratio requirements. For example, for each of the at least three receiver elements, self-noise may be low compared to the lowest expected signal on a required bandwidth. Moreover, each of the at least three receiver elements may need to meet a specific beam pattern. The beam pattern may be driven by a cone of an expected location of reference unit 306 relative to subsea unmanned vehicle 302. Additionally, each of the at least three receiver elements may have a form factor which satisfies one or more mechanical constraints. Further, each of the at least three receiver elements may meet a required depth capability.

[0064] In addition to the above technological requirements for each of the at least three receiver elements, one or more omnidirectional hydrophones or transducers may be included. Further, one or more directive hydrophones or transducers may be included, or a combination thereof. Further, one or more baffled hydrophones or transducers may be included, or a combination thereof, may help to avoid noise and multi-path from the directions where the reference unit is not expected.

[0065] Regarding the processing module, a computing solution meeting the needs of computation power and memory may potentially be used. In some circumstances, some applications may require a dedicated computing device for subsea unmanned vehicle localization process 10. Alternatively, other applications may use existing processing capability available on the subsea unmanned vehicle. Further, one or more Graphical Processing Units (GPUs), one or more Central Processing Units (CPUs), one or more Digital Signal Processing (DSP) processors, and one or more Field-Programmable Gate Arrays (FPGA) may provide interesting benefits to the subsea unmanned vehicle. Additionally, multi-processor architecture may be useful to adapt power consumption depending on the computation need.

[0066] Regarding the data acquisition tool, an architecture that satisfies synchronization requirements of multiple channels may be selected. The architecture may contain a centralized acquisition module, as depicted in FIG. 5. In this configuration, each of the at least three receiver elements may generate one or more electrical signals. For example, one or more hydrophones present (i.e., hydrophone 1 502, hydrophone 2 504...hydrophone N 506) may each generate one or more electrical signals. The electrical signals may be amplified. For example, one or more of the hydrophones present may be pre-amplified 508. Further, each of the one or more electric signals may be an image of an acoustic pressure field perceived by each of the at least three receiver elements. The one or more electric signals may then be passed 510 as analog signals to be digitized using a typical Analog to Digital Converter (ADC) solution 512. Further, one or more of the now digitized signals may be streamed 514 to a computing unit 516 which may be used for signal processing and estimating a location of subsea unmanned vehicle 302. [0067] In another data acquisition module, as illustrated in FIG. 6, a decentralized acquisition module may be used. For example, one or more hydrophones present (i.e., hydrophone 1 602, hydrophone 2 604...hydrophone N 606) may each generate one or more electrical signals. Acquisition module 608 may be used on each of the one or more electrical signals. The one or more electrical signals may be digitized and passed 610 to a network hub 612 generated by each of the present hydrophones. In this configuration, pre-amplification and digitization of the one or more electrical signals generated by each of the at least three receiver elements may be done in situ (i.e., as close as possible to the each of the at least three receiver elements). As a result, one or more analog signals may be less polluted by background electro-magnetic noise. The digital signals may then be streamed on network hub 612 in order to allow for a computing unit to process the one or more signals. The digital signals may then be passed 614 to computer 616, which is used for estimating a location of subsea unmanned vehicle 302. The digital signals may be properly synchronized using one or more relevant techniques, including: (1) Network Timing Protocol (NTP), which may shares an absolute in a network of nodes; (2) correcting one or more local clocks using Voltage Controlled Oscillator (VCO); and (3) encoding each clock in a data stream, which may enable numerical resampling by a computing unit. Further, a centralized clock may be included in network hub 612. Alternatively, one or more of the hydrophones may be a clock master. Clock synchronization may be achieved by distributing an identical clock signal among network of network hub 612. Alternatively, clock synchronization may be achieved by sharing a network time information such as NTP and applying a time correction in one or more of units that need to be time-synchronized.

[0068] In one embodiment, subsea unmanned vehicle 302 and reference unit 306 may both include a clock where the clock of subsea unmanned vehicle 302 and the clock of reference unit 306 are configured to be synchronized with one another.

[0069] Further, in some embodiments of the present disclosure, the at least three receiver elements may be configured to receive one or more acoustic signals 310 transmitted via acoustic transmitter 308 located on reference unit 306, where reference unit 306 may be stationary. The one or more acoustic signals 310 may be a broadband acoustic signal.

[0070] In some embodiments, reference unit 306 may be a ship.

[0071] In some embodiments, reference unit 306 may be a piece of subsea equipment (i.e., a Christmas Tree). [0072] In some embodiments of the present disclosure, the at least three receiver elements may be configured to receive one or more acoustic signals 310 transmitted via an acoustic transmitter located on reference unit 306, where reference unit 306 may be moving. For example, and not to be construed as a limitation, reference unit 306 may be a moving vehicle such as a ship.

[0073] Additionally, in some embodiments in accordance with the present disclosure, reference unit 302 may have a known initial location. For example, reference unit 302 may be a surface vessel equipped with a global positioning system (GPS). In an example of a ship, acoustic transmitter 308 may be deployed below the ship itself. Alternatively, acoustic transmitter 308 may be a piece of underwater equipment. For example, acoustic transmitter 308 may be attached to an underwater structure, in which a location of the underwater structure has been measured. In this embodiment, if an initial global location of reference unit 306 is known, then a global location of subsea unmanned vehicle 302 may be estimated using localization of subsea unmanned vehicle 302 relative to reference unit 306.

[0074] In some embodiments in accordance with the present disclosure, an initial location of reference unit 302 may not be known. Because a global location is unknown, only a relative location of the subsea unmanned vehicle may be computed. For example, acoustic transmitter 308 may be attached to a Christmas Tree in a subsea production oilfield where subsea unmanned vehicle 302 may be equipped to estimate a location of subsea unmanned vehicle 302 as described in accordance with the above embodiments.

[0075] With regards to acoustic transmitter 308 as described in the above embodiments, acoustic transmitter 308 may be configured to transmit one or more acoustic signals 310 underwater. For example, an acoustic modem may be used as acoustic transmitter 308. An alternative solution is to use a fit for purpose acoustic transmitter, which may transmit acoustic signals with a specific beam pattern. Therefore, the acoustic transmitter must be configured to provide a high enough bandwidth and able to systematically transmit a“known” portion. As a result, using a higher bandwidth, one or more delays can be better estimated using the Gabor limit as illustrated above in equation 1. Further, better localization results may be provided.

[0076] In some embodiments according to the present disclosure, localizing subsea unmanned vehicle 302 relative to reference unit 306 may be defined in a referential centered on reference unit 306, north oriented. The parameters of the localization may be defined in spherical coordinates by one or more of: (1) a distance between subsea unmanned vehicle 302 and reference unit 306; and (2) one or more broad angles, as illustrated in FIG. 7. (i.e., azimuth and elevation). In this embodiment, one-way acoustic propagation may be sufficient to estimate the location of subsea unmanned vehicle 302. For example, the computation of the location of subsea unmanned vehicle 302 relatively with reference unit 306 may be done by detecting one or more acoustic signals 310 transmitted by acoustic transmitter 308. The localization may be calculated by combining one or more of one or more estimated localization angles and a distance between reference unit 306 and subsea unmanned vehicle 302. In more detail, one or more localization angles may be estimated from the one or more acoustic signals 310 received by receiver array 304. The technique to detect an incoming acoustic signal may include either: (1) a frame detection algorithm, which may be based on one or more one or more correlation computations; and (2) assuming that acoustic transmitter 308 is time-synchronized with receiver array 304 where scheduling of an acoustic signal transmission may be shared or agreed by reference unit 306 and receiver array 304. Further, a distance between reference unit 306 and subsea underwater vehicle 302 may be estimated by calculating the time of acoustic propagation of the one or more acoustic signals 310 transmitted from reference unit 306 to subsea unmanned vehicle 302, assuming one or more clocks are synchronized. For example, an atomic clock may be a suitable solution. Alternatively, a depth or an altitude may be accurately estimated with a pressure measurement or a DVL. Further, in this embodiment, subsea unmanned vehicle 302 may be configured to transmit the estimated location of subsea unmanned vehicle 302 to reference unit 306 via a communication link.

[0077] In the above described embodiments, receiver array 304 may include at least three receiver elements. The at least three receiver elements may be hydrophones. The hydrophones may be located anywhere on subsea unmanned vehicle 302 where one or more acoustic signals 310 transmitted by acoustic transmitter 308 on reference unit 306 can be received.

[0078] With regards to the estimation of the location of subsea unmanned vehicle 302, the location may be estimated by combining one or more of time of arrivals of the received one or more acoustic packets, which contain the one or more acoustic signals 310, on each of the at least three receiver elements of receiver array 304 from the one or more signals transmitted by acoustic transmitter 308 located on reference unit 306. The one or more acoustic packets may include one or more acoustic signals transmitted by acoustic transmitter 308 located on reference unit 306. As illustrated in FIG. 8, a higher the distance between the array elements may result in a better accuracy. Equation 2 below shows angular measured error dq depending on an acoustic wave celerity c, time of arrival St error and sensor array baseline d.

[0079] As noted above, on ships, a main solution for estimating a location of subsea unmanned vehicle 302 with an array of acoustic receiver is to use USBL technology. USBL are designed to be low footprint and to be contained in a single mechanical part. As a result, the inter element distance may be of the order of few centimeters. In this configuration, the algorithms based on time delay estimations may not be good enough. Other algorithms based on phase drift can replace or complement the time delay algorithms. However, those techniques have limitations, including one or more of: (1) higher sensitivity to multi-path; (2) if phase drift is higher than PI, then there may be one or more phase ambiguities, which may occur when acoustic propagation covers more than half a wavelength between two array elements; (3) may not be optimal for broadband signals; and (4) there may be higher complexity due to frequency decomposition. To remedy the above noted limitations, using an array having one or more inter-element distances of the order of one meter may lead to better precision by using one or more time delay estimations.

[0080] In some embodiments in accordance with the present disclosure, the at least three receiver elements may be hydrophones. The hydrophones may be attached individually to subsea unmanned vehicle 302. As a result, a dedicated rigid structure to support the hydrophone array is not needed. Rather, subsea unmanned vehicle 302 is a support structure itself, which provides more flexibility on sensor integration of the at least three receiver elements. An example of configuration is illustrated in FIG. 9. In FIG. 9, six hydrophones 902 may be attached to a top portion of subsea unmanned vehicle 302. Cables and the processing module may be located inside subsea unmanned vehicle 302. Alternatively, the cables and the processing module may be located outside of subsea unmanned vehicle 302.

[0081] Referring to FIG. 10, subsea unmanned vehicle localization process 10 is shown, in accordance with one embodiment of the present disclosure. Subsea unmanned vehicle localization process 10 may include receiving 1002 one or more acoustic signals 310 on subsea unmanned vehicle 302 from an acoustic transmitter located on a reference unit. The method for localizing a subsea unmanned vehicular system may include estimating 1004 a location of the subsea unmanned vehicle using the received one or more acoustic signals 310.

[0082] In some embodiments, estimating a location of subsea unmanned vehicle 302 may include calculating one or more broad angles using the one or more acoustic signals 310.

[0083] Further, in some embodiments estimating a location of subsea unmanned vehicle 302 may include calculating a depth of subsea unmanned vehicle 302 using the one or more calculated broad angles.

[0084] Additionally, one or more broad angles may be calculated for use in estimating a location of subsea unmanned vehicle 302. The one or more broad angles may be defined by a direction of subsea unmanned vehicle 302 relative to reference unit 306. For example, this may be understood as a line of sight. The one or more broad angles may be characterized by one or more of azimuth and elevation, as illustrated by“az” and“el” in FIG. 7. Further, there may be a bijection relationship between the line of sight direction with an acoustic direction of arrival of the one or more acoustic signals 310. This relationship must also be known. In open-water, when there is no diffraction, the line of sight and acoustic arrival direction of the one or more acoustic signals 310 may be considered equal. However, the two directions may differ due to wave diffraction because of sound velocity gradient. If so, a correction may be applied using one or more calibration methods, as discussed in greater detail below.

[0085] Further, the above scenario may be valid in an open-water scenario where channels may not be very“horizontal.” In this context of horizontal channels, a wave-guide such as a SOFAR channel may be created and the relationship between line of sight and acoustic arrival directions of the one or more acoustic signals 310 may be too complex and may not be bij ective. Additionally, if there are other materials than water in the acoustic propagation path between reference unit 306 and subsea unmanned vehicle 302, the above conditions may not be true. For example, if there is a metallic pipe in the vicinity of reference unit 306 and subsea unmanned vehicle 302, it is possible that a first acoustic signal received from the one or more acoustic signals 310 arrival may be from propagation in the metallic pipe rather than the propagation in open-water field, which may bias the results.

[0086] In order to solve the above noted challenge, one or more broad angles may be calculated by measuring one or more times of arrival of one or more acoustic packets on each of the array elements. In some embodiments according to the present disclosure, estimating a location of subsea unmanned vehicle 302 may comprise calculating a time of travel between the time the one or more acoustic signals 310 are transmitted from acoustic transmitter 308 located on reference unit 306 and the time the one or more acoustic signals 310 are received by subsea unmanned vehicle 302. As mentioned above, better results may be achieved when each of the at least three receiver elements are spaced far apart. For example, the one or more times of arrival may be estimated on each of the at least three receiver elements. Given at least three receiver elements, giving at least three times of arrival, and assuming the locations of the receiver elements are known, the one or more broad angles may be estimated. In this example, the estimated time of arrival of the one or more acoustic signals 310 does not need to be an absolute time. Further, a fixed offset on the estimated times of arrival of the one or more acoustic signals 310 may not preclude calculating the one or more broad angles. In assuming open-water conditions, the estimated time of arrival may refer to the first acoustic arrival. In case of multipath, the following arrivals may be rejected using signal processing techniques. FIG. 11 illustrates this embodiment of the present disclosure where a location of subsea unmanned vehicle 302 may be estimated in multiple steps. For example, acoustic to digital 1102 is the acquisition step aiming at providing data that can be processed by a digital computer. This may include one or more of multichannel synchronous acquisition, scaling, and conversion to float, while providing all data in buffers in real time. In this example, a centralized acquisition module, as depicted in FIG. 5, may be used. Specifically, the module may include an acquisition of six channels at 192kHz, 24bits, performed on a unique board for synchronization purposes and sent by a TCP stream to an embedded computing unit. Further, feature search 1104 works to look for a piece of a signal that can be recognized on all channels. The length of this piece of signal may vary depending on the application and the expected signal. This example may further include looking for a known preamble of one or acoustic packets from the one or more acoustic signals 310 as a feature using a match filter, with a length of few milliseconds. The concept of preamble for a telemetry is illustrated in FIG. 12 and will be described in more detail below. In FIG. 12,“P” denotes the one or more preambles. Alternatively, other techniques may be used including one or more of SNR increase detection, self-correlation of a channel, and intercorrelation of multiple channel. Additionally, under high doppler condition, cross-correlation with a preamble may be weak. A solution may be to run multiple cross correlations in parallel on a set of reference signals. This set of reference signals may be obtained by applying one or more expected clock drifts on an initial preamble. For example, instead of running a simple cross-correlation on a preamble P, subsea unmanned vehicle localization process 10 may run five cross-correlation on the transformed preambles of P by clock drifts of -1000 ppm, -500 ppm, 0 ppm, +500 ppm and +1000 ppm. As a result, if the Doppler generate a clock drift of -600ppm, the second cross-correlation may show a high coefficient and the packet may be detected. When a signal of interest has been found, time delay estimation 1 106 may provide the information required for calculating one or more broad angles. It may include measuring relative times of arrival of the one or more acoustic signals 310 on each of the at least three receiver elements. The times may be relative because they may all be offset by a same fixed value. This step may require excellent synchronization between multiple channels, which may include two examples of implementation. For example, processing data might be based on a match-filter between reference signals the multiple channels. In this example, several design options may be selected, including one or more of the following: (1) a maximal value of the match-filter output may provide the time of arrival; (2) a first high peak of the match- filter output may be preferred to select to make sure a direct path arrival is selected instead of one or more reflected paths; and (3) up sampling may help to increase temporal resolution of the time estimation. In the second implementation option, for one direction of arrival, one or more theoretical delays of all channels may be computed. If the theoretical delays are applied to the multiple channels, all channels should match. As a result, an energy function may be defined as a cross product of the delayed channels, where the delays may be a function of a search space of direction of arrival. Moreover, as a signal may be altered on the multiple channels due to baffling, local multipath, a confidence index may be added to delay estimation per channel. This may occur, for example, using a match filter amplitude to avoid outliers. Next, one or more broad angles may be calculated 1108. The broad angles computation aims at inverting the problem known as source localization. Because the problem is non-linear, a numerical optimization may be preferred. One or more of the following assumptions may be taken. First, spherical wave propagation may be considered. Acoustic channel studies have shown that this is valid for channels that are not too horizontal. Second, approximation of a plane wave may be assumed, meaning an incoming direction is independent from the location of a sensor. Third, an improved version of the plane wave may be considered by considering one or more correction factors related to a timing offset due to the spherical propagation. This may be necessary in case a ratio of inter-element spacing over a reference unit to a subsea unmanned vehicle is not small. Broad angles calculation 1 108 may take as input the relative time delays per channel and output the computed one or more broad angles, an image of the position of reference unit 306. Further, broad angles calculation 1 108 may include a confidence index if available. Further, position computation 1 110 may include correcting the computed one or more broad angles (azimuth and elevation) with respect to an orientation of subsea unmanned vehicle 302 (yaw, pitch and roll) to obtain a local estimation of reference unit’s 306 direction. The distance may then be computed. Position calculation 1110 may also integrate a Bayesian filter, which may be similar to a particle filter, to avoid bad measurements and add a confidence index to the value, by using the fact that a position function is continuous in time. However, a location estimated by position calculation 1 110, may suffer from one or more of the following imperfections. First, an update rate of the location estimate might be low. For example, the update rate may be a few minutes. This resolution may be too low for one or more algorithms onboard subsea unmanned vehicle 302. For example, if subsea unmanned vehicle 302 is autonomous, the autonomy behavior may require a better time resolution than few minutes. Further, one or more location updates may be erroneous due to one or more of noise, doppler, and failure of the system (i.e., hardware or software). The errors may have a disastrous impact on one or more external algorithms, such as, for example, autonomy software.

[0087] In response to the above challenges, the location estimation may be improved significantly when coupled with a navigation system. In one or more embodiments, subsea unmanned vehicle 302 may include navigation system 1306, as illustrated in FIG. 13. Further, the location calculated in position calculation 1110 may be provided as feedback to navigation system 1306 in feedback to navigation system step 1112. Further, for greater performance, an output from subsea unmanned vehicle localization process 10 may be coupled with navigation system 1306, which is a more comprehensive software that may utilize one or more heterogeneous and asynchronous input sources. The objective of navigation system 1306 is to maximize the certainty of the location estimate. For example, navigation system 1306 may take inputs such as, for example, IMU, pressure measurement, DVL. In this example, the calculated one or more broad angles may be estimates. The estimates may be associated with a certainty factor, given by subsea unmanned vehicle localization process 10. Depending on the exact implementation, a certainty factor may be an image of a variance of the estimation of a location of subsea unmanned vehicle 302.

[0088] In one embodiment, the one or more calculated broad angles, as described above, may be defined by the direction of subsea unmanned vehicle 302 relative to reference unit 306. [0089] In one embodiment, if one or more obstructions are in a path of the one or more acoustic signals 310, transmitted, via acoustic transmitter 308 located on reference unit 306, to subsea unmanned vehicle 302, the one or more obstructions may be detected and accounted for.

[0090] In one embodiment in accordance with the present disclosure, reference unit 306 may be stationary, as illustrated in FIG. 13. In this embodiment, a global location of reference unit 306 may be known by subsea unmanned vehicle 302. Acoustic transmitter 308 may be located on reference unit 306. Acoustic transmitter 308 may take one or more of the following forms: (1) a boat; (2) an underwater structure; and (3) another underwater vehicle. Acoustic transmitter 308 may be a“fit for purpose” acoustic transmitter where the one or more acoustic packets may be sent when a location of subsea unmanned vehicle 302 needs to be updated. Further, acoustic transmitter 308 may also be an acoustic modem that transmits one or more acoustic packets containing information during a mission. For example, the one or more acoustic signals 310 may be directed to Rx array 1302. One or more images of the one or more acoustic signals 10 received by each of the at least three receiver elements may be generated by Rx array 1302 and may in turn be used to estimate one or more broad angles 1304. The estimated one or more broad angles may be directed to navigation system 1306. Navigation system 1306 may take into account one or more of IMU, DVL, and one or more pressures. As a result, a relative location of subsea unmanned vehicle 302 may be estimated. The estimation may include one or more uncertainties. Subsea unmanned vehicle localization process 10 may output the calculated one or more broad angles between subsea unmanned vehicle 302 and reference unit 306. A global location of subsea unmanned vehicle 302 may be computed by using an instantaneous approach, as illustrated in FIG. 14. Relative Position Calculation 1402 may calculate a relative location of subsea unmanned vehicle 302. Further, the calculated one or more broad angles (elevation and azimuth) may first be corrected by an orientation of subsea unmanned vehicle 302. For example, this may include one or more of a yaw, pitch and roll. Further, a measurement reflecting a distance between reference unit 306 and subsea unmanned vehicle 302 may be included in Equation 2, as shown below, to calculate the relative position/location of subsea unmanned vehicle 302 where the term“dist” represent“distance”:

[0091] Further, in FIG. 14, the convention P , Q is used to define the absolute location n. P gives the location of the reference point on a structure and Q defines an orientation. The orientation may be specified by one or more of yaw, pitch and roll. From this relative location, the absolute location may be calculated by applying a coordinate change in coordinate update 1404. Coordinate update may depend on the coordinate system reference of use. For example, in the World Geodetic System (WGS84) coordinate system reference, P may be defined by longitude[°], latitude[°] and altitude[m]. Coordinate update 1404 may require one or more mathematical transformations. Thus, subsea unmanned vehicle localization process 10 may use this coordinate system in navigation system 1306. Alternatively, in a Universe Transverse Mercator (UTM), P is locally defined by north [m], east [m], and altitude [m]. Coordinate update 1404 is a sum of the relative location with an absolute location of reference unit 306. An instantaneous location may be valid if all measurements are taken at the same time. Further, each measurement is valid at the time of measurement only, which poses one or more of the following challenges. First, one issue occurs if the measurements are not taken at the same time. For example, this may occur if the output of subsea unmanned vehicle localization process 10 is not synchronized with the IMU measurement. Second, one or more users may need an estimated location of subsea unmanned vehicle 302 at a different time than the exact measurement time. For example, the one or more users may be the autonomy software of subsea unmanned vehicle 302. Further, there may be an issue of noise in one or more of the measurements, which raises an issue of trustworthiness as to whether a most recent location estimate or one or more previous measurements should be trusted. To solve the above challenges, a Navigation System algorithm based on a Bayesian approach, such as Kalman filtering may be used. Instead of running the instantaneous calculation as illustrated in FIG. 14, navigation system 1306 may include one or more of a notion of time and a notion of distributions (i.e., Probability Density Functions (PDF)) of one or more variables. As a result, the dynamics of subsea unmanned vehicle 302 may be included in the state of the problem. The problem may be solved as a maximization of a certainty of a location of subsea unmanned vehicle 302 at any time, which is illustrated in FIG. 13. Further, subsea unmanned vehicle localization process 10 may leverage a high-level control of one or more movements of subsea unmanned vehicle 302. One or more movements of subsea unmanned vehicle 302 may be coordinated in order to enhance subsea unmanned vehicle localization process 10. The one or more coordinated movements may be used to calibrate one or more locations and timing offsets of the at least three receiver elements.

[0092] Regarding FIG. 15, an embodiment of subsea unmanned vehicle localization process 10 is shown. Specifically, FIG. 15 illustrates a signal flow path with a moving reference unit having no transmission of a location of reference unit 306 to subsea unmanned vehicle 302. In this particular embodiment, an initial location of reference unit 306 is unknown. One or more acoustic signals 310 may be directed to Rx array 1302. One or more images of the one or more acoustic signals 310 received by each of the at least three receiver elements may be generated by Rx array 1302 and may in turn be used to estimate one or more broad angles 1304. The estimated one or more broad angles may be directed to navigation system 1306. Navigation system 1306 may take into account one or more of IMU, DVL, and one or more pressures. In this example, it may be assumed that acoustic telemetry (i.e. acoustic transmitter 308) cannot transmit an absolute location of reference unit 306. As a result, subsea unmanned vehicle 302 may only compute a location relative to reference unit 306. When coupled with navigation system 1306, a model of reference unit 306 may be considered. This may include taking one of several options. First, in a stationary approach, it may be assumed that reference unit 306 does not move fast compared to the update rate of subsea unmanned vehicle localization process 10. This may apply well to one or more fixed structures such as a subsea infrastructure (e.g., a manifold). In a second approach, a priori model approach may be used where behavior of reference unit 306 may follow a model that can be loaded on subsea unmanned vehicle 302. The model may specify the route of reference unit 306 over time. Further, a machine learning approach may be used where subsea unmanned vehicle 302 may learn on the fly how a relative location is related to an absolute measurement data given by the IMU and DVL. This may lead to a relationship between the absolute measurement data such as IMU and DVL with the relative location of subsea unmanned vehicle 302. Further, if an uplink telemetry exists from subsea unmanned vehicle 302 to reference unit 306, then the relative location may be communicated to reference unit 306. As a result of the above, reference unit 306 may use this relative location to make one or more decisions. For example, reference unit 306 may elect to follow subsea unmanned vehicle 302. Based on one or more updated relative location estimates, reference unit 306 may adapt one or more of it its navigation modes to follow subsea unmanned vehicle 302. [0093] In some embodiments in accordance with the present disclosure, the estimated location of subsea unmanned vehicle 302 may be used to adapt one or more behaviors of subsea unmanned vehicle 302.

[0094] Regarding FIG. 16, an embodiment of subsea unmanned vehicle localization process 10 is shown. In this particular embodiment, an initial location of reference unit 306 is known by subsea unmanned vehicle 302. In this embodiment, acoustic telemetry may be included. For example, telemetry modem 1604 may be included. Acoustic telemetry 1604 may be used to transmit information in between reference unit 306 and subsea unmanned vehicle 302. In this configuration, the acoustic telemetry may be used to transmit an absolute location of reference unit 306. If reference unit 306 is a floating platform such as, for example, a ship, then a radio GNSS may be reliable enough to obtain the absolute location of reference unit 306. If reference unit 306 is another underwater vehicle, then the absolute location may come from another navigation system. Using the transmitted absolute location of reference unit 306, it is possible to derive the absolute location of subsea unmanned vehicle 302 from the relative location of the subsea unmanned vehicle localization process 10. However, both the absolute location of the ship and the relative location of subsea unmanned vehicle 302 may suffer from one or more errors related to noise, bias, low update rate, and latency in the communication link. Therefore, optimal processing or algorithm may involve one or more of asynchronous and heterogeneous measurements that consider both a belief that propagation of the one or more acoustic signals 310 and one or more time dynamics aspects. Therefore, in this embodiment, navigation system 1306 may be included having both models of reference unit 306 and subsea unmanned vehicle 302. This approach may be based on a Bayesian approach such as, for example, a Kalman filter. Further, as FIG. 16 illustrates, one or more acoustic signals 310 may be directed to one or more of Rx array 1302. One or more images of the one or more acoustic signals 10 received by each of the at least three receiver elements may be generated by Rx array 1302 and may in turn be used to estimate one or more broad angles 1304. The estimated one or more broad angles may be directed to navigation system 1306. Navigation system 1306 may take into account one or more of IMU, DVL, and one or more pressures. The estimated one or more broad angles may be directed to navigation system 1306 along with the one or more acoustic signals 310 that may be passed to telemetry modem 1604. As a result, the absolute location of subsea unmanned vehicle 302 may be estimated. The estimation may include one or more uncertainties. [0095] In some embodiments, reference unit 306 may be a floating structure where the location of acoustic transmitter 308 is expected to oscillate due to waves and heaves. Further, depending on the specific GPS technology, accuracy from 1 to 10 meters may be expected. To reduce the uncertainty of subsea unmanned vehicle localization process 10, it may subsea unmanned vehicle 302 may consider an exact location of acoustic transmitter 308 at the time of the transmission of one or more acoustic packets containing one or more acoustic signals 310. One or more of the following solutions may be combined to solve the above noted issue. For example, an INS may be implemented on reference unit 306 to filter the noise of the GPS and to achieve better accuracy with the aid of the IMU. Second, an exact location of acoustic transmitter 308 may be encoded systemically in one or more acoustic telemetry packets containing the one or more acoustic signals 310 that are transmitted from reference unit 306 to subsea unmanned vehicle 302. This solution may be robust if the location of acoustic transmitter 308 is accurate. Further, this solution may require a significant telemetry bandwidth. Third, depending on specific GPS technology and on a telemetry rate associated with a location of acoustic transmitter 308, a confidence index of the location may be associated with location of acoustic transmitter 308. The confidence index may include a variance of one or more parameters of one or more locations of acoustic transmitter 308. For example, if a location of acoustic transmitter 308 is transmitted every minute, with a wave amplitude of 3 meters and a wave periodicity of 10 seconds, the standard deviation of the altitude of acoustic transmitter 308 location may be in the range of few meters. This confidence index may be used by navigation system 1306 of subsea unmanned vehicle localization process 10. Fourth, a location of acoustic transmitter 308 may be low-pass filtered in order to remove high frequency components. The high frequency components may be removed due to the low telemetry rate associated with the high frequency components.

[0096] In some of the embodiments, a relative location of subsea unmanned vehicle 302 with reference unit 306 may be calculated by subsea unmanned vehicle 302, regardless of whether or not there is telemetry or if existing telemetry is not working properly. Therefore, one or more behaviors of subsea unmanned vehicle 302 may be adapted. Advantages of this configuration include the following examples. First, autonomy behavior of subsea unmanned vehicle 302 may be related to the relative location of subsea unmanned vehicle 302 with reference unit 306. As mentioned above, an example of autonomy behavior includes“follow me” behavior where subsea unmanned vehicle 302 may follow reference unit 306. The “follow-me” behavior may be implemented with one or more specificities. The one or more specificities may include one or more of a required space offset, a required depth, and a required altitude or a maximal/minimal speed. A more complex example includes searching for a specific underwater feature such as, for example, one or more of a pipe, an equipment, a leak, etc., while remaining in a defined space relative to reference unit 306. Second, telemetry performance may depend significantly on the relative location of subsea unmanned vehicle 302 with reference unit 306. Therefore, signal amplitude may be related to distance, via one or more of spreading and absorption losses. To guarantee a minimum SNR, subsea unmanned vehicle 302 may want to remain at a certain distance from reference unit 306. The required distance may also depend on other factors including one or more of noise level and one or more absorption parameters. Further, a signal amplitude may also be related to the one or more broad angles due to directivity of one or more transducers. As a result, to maintain a sufficient SNR, subsea unmanned vehicle 302 may have to remain in one or more of in a cone and a more sophisticated space. Additionally, the signal amplitude may also depend on ray bending due to a sound velocity gradient on a water column. The sound velocity gradient may generate some acoustic diffraction, which may result in non-uniform energy propagation. One or more spaces may be characterized by a lower signal amplitude than expected due to the acoustic propagation escaping from the one or more spaces. Other spaces may be characterized by an increased amplitude due to a focusing effect. Based on input to subsea unmanned vehicle localization process 10, it may be possible to orient subsea unmanned vehicle 302 in the one or more spaces, where the one or more spaces may show a higher amplitude. An example of this advantage lies in its usefulness in a case of communication loss. For example, if the acoustic telemetry is lost for any portion of time, subsea unmanned vehicle 302 may be able to resolve the problem based on input to subsea unmanned vehicle localization process 10. Another advantage may include telemetry adaptation. For example, one or more parameters of the telemetry may be optimized depending on the relative location. Specific examples may include if the distance is relatively short between subsea unmanned vehicle 302 and reference unit 306, absorption may not be significant and spreading loss may be predominant. As a result, it may be efficient to use a higher frequency band in order to avoid noise while increasing the telemetry bandwidth. Additionally, if the distance increases, subsea unmanned vehicle 302 may choose to use a safer telemetry mode. Examples of safer modes may include, depending on the configurations, one or more of using lower frequency, decreasing the bandwidth, increasing a redundancy rate of the modem for more reliable Forward-Error Correction, increasing transmitted power, focusing more the beam pattern, and changing modulation. A third advantage may include optimization of input to subsea unmanned vehicle localization process 10. For example, input to subsea unmanned vehicle localization process 10 performance may be optimized based on the relative location as described above. At low SNR, the accuracy of input to subsea unmanned vehicle localization process 10 may be expected to degrade and the accuracy may be measured using a confidence index. These embodiments may incorporate one or more of the above noted features regarding optimization of telemetry.

[0097] In one or more embodiments, the estimated location of the subsea unmanned vehicle 302 may be transmitted to reference unit 306 via a communication link using one or more existing telemetry infrastructures. However, as illustrated in FIG. 17, acoustic channel usage during a typical un-tethered AUV mission, driven from a ship (i.e. reference unit 306), may include one or more challenges, as described below. The acoustic channel must be shared between acoustic positioning and acoustic telemetry. Due to frequency band constraints and due to the lack of underwater communication standards, there have not been other solutions than to use time multiplexing to share the available bandwidth. For example, existing USBL ping technology may be made of an acoustic request from the ship to a subsea unmanned vehicle, followed by a reply from a transponder on the subsea unmanned vehicle to the ship. The USBL device on the ship computes the location of the unmanned vehicle. Due to the long propagating time in the water, few seconds must be dedicated to each USBL ping. In this example, 30% of the time may be allocated to USBL pinging. Further, most acoustic telemetry systems use wide band acoustic signals, making them suitable for location estimation. Therefore, leveraging existing telemetry infrastructure to provide one or more acoustic signals used by subsea unmanned vehicle localization process 10 onboard subsea unmanned vehicle 302.

[0098] In another embodiment, a solution to the above challenges is presented that highlights the concept of removing allocating time for USBL and to only use acoustic downlink telemetry packets calculating the location of subsea unmanned vehicle 302 relative to a transmitting modem, as illustrated in FIG. 18. As a result, more bandwidth may be left for telemetry purpose and the location of subsea unmanned vehicle 302 may be calculated more often, leading to higher system performance. Further, acoustic telemetry systems may be half duplex communications, meaning the communication can occur in both directions but never in the same time. Therefore, one or more telemetry packets to subsea unmanned vehicle 302 may be used to estimate the relative location from acoustic transmitter 308 located on reference unit 306 relative to subsea unmanned vehicle 302. Once a location update is calculated by subsea unmanned vehicle localization process 10, it may be possible to transmit the location update to reference unit 306 via the telemetry infrastructure. As described above and illustrated in FIG. 12, one or more telemetry packets may include a preamble section. The preamble section may be used for acoustic packet detection and synchronization by the receiver array 304. The preamble section may prepended to ensure acoustic transmitter 308 and receiver array 304 are able to synchronize. This concept is illustrated in FIG. 19. Specifically, a multi-preamble architecture is shown where one or more preambles may be associated with a telemetry mode or a specific acoustic transmitter type, where a correlation with a first preamble 1902 and up to preamble N 1904 are directed to a preamble search 1906. If preamble i is detected, a location of subsea unmanned vehicle 302 may be estimated (referred to as“compute” in FIG. 19) 1908 using preamble where preamble i may consists of a short duration signal in an asynchronous system. The short duration signal may be used to synchronize acoustic transmitter 308 and subsea unmanned vehicle 302 using receiver array 304. Specifically, preamble i may be a“known” signal which may be transmitted by acoustic transmitter 308 to at least one of the three receiver elements located on receiver array 304. Preamble i may be used to estimate one or more of time, frequency and channel relatively between acoustic transmitter 308 and receiver array 304. Further, preamble search 1906 may be done on one or more of the at least three receiver arrays.

[0099] In some embodiments, identical preambles may be used for both the uplink and the downlink packets. As result, subsea unmanned vehicle localization process 10 may detect one or more packets transmitted by subsea unmanned vehicle 302 to reference unit 306. Additionally, in the context of multiple acoustic agents, an acoustic channel might be shared among all agents. The acoustic agent may be understood as an active acoustic device. For example, this may include one or more of an underwater vehicle, a simple acoustic transmitter, and a ship. In this context, it is important that subsea unmanned vehicle 302 only focuses on the packets transmitted by reference unit 306. Therefore, subsea unmanned vehicle localization process 10 may include the ability to differentiate one or more acoustic packets received from acoustic transmitter 308 located on reference unit 306. For example, one or more of the following techniques may be included singularly or in combination. First, a network solution may be provided if the acoustic channel is shared using a common network scheme, such as Time-Division Multiplexing Access (TDMA), then the TDMA information may be used by subsea unmanned vehicle localization process 10 to only process acoustic streams on relevant time slots. Additionally, an outlier rejection technique may be applied if reference unit 306 can be assumed to be located in a cone, and that no other acoustic agent is located in that cone. Therefore, only subsea unmanned vehicle localization process 10 update given in that cone can be considered. Further, a feature recognition may be applied if one or more signal properties are assigned to reference unit 306. In this technique, it may be possible to filter out one or more signals that do not match with the above noted. For example, if the acoustic amplitude is expected in a certain range, then any signal showing out of range amplitude may be rejected.

[00100] In some embodiments, integration with telemetry systems may focus only on one or more signals emitted by reference unit 306. In this example, integration with telemetry systems may require integration with a networking layer.

[00101] In some embodiments, subsea unmanned vehicle localization process 10 may be agnostic of one or more telemetry systems. For example, this may be done by identifying automatically a signal of interest, based on feature detection, as described above. Subsea unmanned vehicle localization process 10 may include signal processing in order to extract one or more preambles from existing telemetry infrastructure. On one or more telemetry packets, the preamble may comprise the first few milliseconds of the one or more telemetry packets. The identified one or more preambles may then be used to compute one or more location updates. One or more of the following features may be used to extract the one or more preambles. For example, SNR may be used if subsea unmanned vehicle 302 is not too far off in terms of distance from reference unit 306 where the one or more acoustic packets received by receiver array 304 may include very good SNR. Additionally, the one or more preambles may be repeated. Further, the one or more preambles are unique for a telemetry mode. Signal processing may be implemented so that subsea unmanned vehicle localization process 10 may recognize one or more signals that repeat over time. An additional feature may be based on packet frequency rate. In this feature, depending on the networking layer, the one or more telemetry packets may be transmitted at a fixed frequency. This frequency of“pinging” may be used to isolate the one or more preambles. For example, if the frequency of pinging is 0.1 Hz, a preamble may be configured to be received every 10 seconds. This information may be used to select one or more correct preambles. Further, a direction of arrival feature may be used there is relative to subsea unmanned vehicle 302. If the location information is available, the information may be used for preamble extraction. For example, subsea unmanned vehicle 302 may be constrained in a cone of +/- 45 degree below reference unit 306 (i.e. a ship in this example). In extracting one or more, as described above, this feature may be used to process the one or more acoustic signals 310 accordingly. Further, a frequency content feature may be used. In this feature, the one or more preambles may be located in one or more defined frequency bands. The one or more frequency bands may be specified by a telemetry system provider. Subsea unmanned vehicle localization process 10 may include this feature in order focus only on one or more relevant frequency bands. As result, any out-of-the- band signal may be rejected. For example, assuming one of the one or more signals of interest is located in between a range of 20 kHz and 80 kHz, a digital pass-band filter may be implemented as a first stage of subsea unmanned vehicle localization process 10. Additionally, a timing feature may be included. In the timing feature, if one or more timings of the one or more telemetry packets are controlled by any kind of networking layer, the timing information of the one or more timings may be used to extract the one or more preambles. Further, depending on the exact configuration, a combination of the previous features may be used to extract the one or more preambles of interest for subsea unmanned vehicle localization process 10. For example, and not to be construed as a limitation, an identification phase may be added at the early stage of the mission. Subsea unmanned vehicle 302 may not be too far away from reference unit 306 and a relative velocity may be low to ensure good reception quality. During the phase, one or more telemetry systems may transmit one or more acoustic packets. It may then be possible to extract a first few millisecond of the one or more acoustic signals 310, which may comprise the one or more preambles for the remainder of the mission.

[00102] In some embodiments, a first step of processing one or more acoustic signals 310 may include detecting the one or more preambles. This step may be performed in parallel on one or a plurality of the one or more preambles. Given sufficient orthogonality on the one or more preambles, there may be a very low risk of mis-detection of the transmitted one or more preambles. Highly efficient computation architecture exists to perform such parallel tasks. Each of the one or more preambles may be associated with an acoustic transmitter (i.e., acoustic transmitter 308) located on a reference unit (i.e., reference unit 306). Each of the one or more preambles may be associated to one or more telemetry modes using one or more modems. Once one of the one or more preambles is detected, the location of subsea unmanned vehicle 302 may be estimated based on the detected one or more preambles. As a result, subsea unmanned vehicle localization process 10 may be run with multiple acoustic transmitter types, which may significantly increase the location performance, as a diversity of acoustic packets going from reference unit 306 to subsea unmanned vehicle 302 may be leveraged for location purpose. An example is illustrated in FIG. 20, where two telemetry systems may be used, using a Time-Division Multiplexing channel sharing solution. The time-Division Multiplexing channel sharing solution may include one or more of the following. First, Telemetry Scheme 1 (TS1) may be used, which may include, for example, working from a range from 20 kHz to 40 kHz. In this example, one acoustic packet may be provided every minute. Further, since TS1 works at rather low frequency, it is efficient for long range communication. Second, Telemetry Scheme 2 (TS2) may be used. TS2 may include working in a range from 30 kHz to 80 kHz. In this example, three acoustic packets may be provided every minute. This telemetry scheme may work at higher frequency, which may results in a greater signal bandwidth and provide better timing resolution. Further, providing three times more packet per cycle in the TS2 scheme as compared to the TS1 scheme may allow for subsea unmanned vehicle localization process 10 to provide an update rate that is three times higher.

[00103] In one or more embodiments, subsea unmanned vehicle localization process 10 may combine the TS1 scheme and the TS2 scheme, as described above. The combination may result in the best use of acoustic energy transmitted from reference unit 306 to subsea unmanned vehicle 302.

[00104] Further, FIG. 21 illustrates how one or more broad angles may have a direct effect on one or more times of arrival of one or more acoustic signals. For example, three receiver elements, 2102, 2104, and 2106, may be configured to receive one or more signals from three different angles of -45°, 0°, and +45°, respectively, due to one or more wave fronts transmitted by an acoustic transmitter. In this configuration, one or more time delays between the time when the one or more acoustic signals are transmitted by the acoustic transmitter to the time when the three receiver elements, 2102, 2104, and 2106, may occur. The one or more time delays may be due to inducements of each of the three receiver elements by one or more broad angles from the one or more wave fronts. Further, roll and depression of the three different angles 2108 of the one or more signals received by the three receiver elements, 2102, 2104, and 2106, may be taken into account by direct problem 2112 with one or more positions 2110 of the three receiver elements, which may be comprised of one or more hydrophones. Specifically, direct problem 2112 may consider acoustic propagation assuming one or more plane waves in order to generate one or more relative times of arrival 2114 of one or more acoustic signals on each of the three receiver elements (i.e. hydrophones).

[00105] In accordance with one or more of the above embodiments, an example of unmanned vehicle localization process 10 is illustrated in FIG. 22. One or more locations of one or more of the at least three receiver elements, which may be comprised of one or more hydrophones, 2202 may be taken with one or more relative times of arrival 2204 of the one or more acoustic signals 310 on each of the one or more hydrophones to be processed through inverse problem processing 2206. Inverse problem processing 2206 may use, for example, one or more of a Gauss-Newton method, a gradient descent method, and a Bayesian method. One or more angles may then be provided 2208. The one or more angles may include one or more of roll and depression.

[00106] In some embodiments, a Bayesian approach may be used to better estimate the location of subsea unmanned vehicle 302, as illustrated in FIG. 23. For example, where one or more hydrophones are used, a location of a PDF of the one or more hydrophones 2302, relative times of arrival of the one or more acoustic signals 310 on each hydrophone 2304, and vehicle location PDF 2306 of subsea unmanned vehicle 302 may be directed to inverse problem processing 2308. Inverse problem processing 2308 may use a Bayesian approach. The Bayesian approach may include a Monte-Carlo Markov Chain. As a result, the location of subsea unmanned vehicle 302 and each of the one or more hydrophones may be better estimated 2310.

[00107] In another embodiment of the present disclosure, a method for localizing a subsea unmanned vehicular system is provided. The method for localizing a subsea unmanned vehicular system may include receiving, via an acoustic transmitter located on a reference unit, one or more acoustic signals on a subsea unmanned vehicular system. The method for localizing a subsea unmanned vehicular system may include calculating one or more broad angles using the one or more acoustic signals. The method for localizing a subsea unmanned vehicular system may include calculating a sound velocity profile using the one or more acoustic signals. The method for localizing a subsea unmanned vehicular system may include estimating the location of the subsea unmanned vehicular system using the calculated broad angles and calculated sound velocity profile. The sound velocity profile may also be measured directly using a probe measuring the time of flight between two known positions.

[00108] With regards to calibration methods, in existing USBL systems, a calibration of a sound velocity profile must be done. The processing is typically done at a surface of a ship. As a result, the sound velocity profile is often done as a prior step of the mission, which this takes time and any update must be done with a new calibration step, involving new time and equipment.

[00109] In some embodiments one or more“in situ” calibration methods may be used. The one or more“in situ” calibration methods may use one or more onboard instrumentations on subsea unmanned vehicle 302 to improve the estimated location of subsea unmanned vehicle with very limited overhead. Specifically, as mentioned above, a sound velocity profile may be calculated The estimated location of subsea unmanned vehicle 302 based on acoustic devices (e.g., USBL, LBL, SBL, or the inverted equivalent) may be biased by an acoustic velocity gradient between reference unit 306 and subsea unmanned vehicle 302. In this example, the calibration method may be configured to measure the acoustic velocity gradient and compute a correction on an estimated angle of arrival based on the an acoustic propagation model. The acoustic propagation model may be based on one or more of Ray Tracing algorithms and one or more look-up tables to apply a correction. Further, if subsea unmanned vehicle 302 is equipped with a sound velocity probe, a sound velocity profile may be measured during the mission and a profile can be built while running the mission. As a result, any corrections due to ray bending may be calculated and applied during the mission, with limited overhead time. Further, a CTD instrument may be used to obtain the sound velocity profile versus depth, which may be used to correct for the effects of ray bending. The sound velocity profile may be inferred from one or more measurements performed by the CTD instrument. Alternatively, a sound velocity probe may be used for direct measurement of the sound velocity profile.

[00110] Since the sound velocity profile may change over time, one of the following features may be included. First, the sound velocity may be assumed to be constant. Second, if a user can interact with subsea unmanned vehicle 302 via one or more telemetry systems, the user may have information indicating that a new sound velocity profile should be measured by subsea unmanned vehicle 302. In this example, a control signal may be sent to subsea unmanned vehicle 302 to trigger one or more new measurements. Additionally, the mission may be autonomously adapted to ensure the sound velocity profile measurement is updated at one or more relevant times. If needed, an underwater path the one or more acoustic signals 310 travel along may be adapted to take one or more new measurements. The one or more relevant times may be based on an autonomy management of subsea unmanned vehicle 302. Further, the one or more relevant times may be at a fixed frequency that depends on the location of subsea unmanned vehicle 302. Additionally, the one or more relevant times may be triggered by one or more external sensors that indicate that one or more conditions have changed.

[00111] However, the estimated location of subsea unmanned vehicle 302 based on one or more acoustic devices (USBL, LBL, SBL, or the inverted equivalent) may be off due to an error on the location of the array elements. In a known USBL system, calibration methods which are part of the manufacturing process of the device are used. In this known system, the required accuracy is high, which is expensive and, further, the USBL device must be designed in such a way that the calibration results remain valid over time, involving high costs. Additionally, known SBL and LBL systems often involve the use of an external active acoustic device to measure the location of the array elements.

[00112] To solve the above problem, receiver array 304 may be calibrated by leveraging on one or more redundant array elements and by using specific behavior of subsea unmanned vehicle 302. For example, receiver array 304 may include at least three receiver elements for estimating the location of subsea unmanned vehicle 302. Additional array elements may be used to reduce an estimation error and to better estimate a location of each of the at least three receiver elements. Each time subsea unmanned vehicle localization process 10 computes the one or more broad angles, a re-calibration may be performed, as illustrated below in using Equation 4:

In Equation 4, X defines the location of the array elements, t _t refers to a relative time of arrival on each of the at least three receiver elements i, t _t refers to an expected time of arrival for one or more given broad angles (azimuth and elevation) and each of the at least three receiver elements locations. If the broad angles are not known, they may and must be found in the resolution of Equation 4. In one example, one or more element locations may be constrained around an initial estimate. Therefore, an additional term be added, as illustrated in Equation 5 below:

In Equation 5, one or more estimations of the location of subsea unmanned vehicle 302 may be calculated. Specifically, argmin x (f(x)) finds x which gives a minimal value of f(x). X represents the positions of the at least three receiver elements located on receiver array 304. Xo represents an initial estimate of the at least three receiver elements located on receiver array 304.

[00113] In some embodiments, one measurement may not be enough to resolve Equation 5. In response, controlling one or more behaviors of underwater movement, while accumulating measurements for subsea unmanned vehicle localization process 10. As a result, Equation 5 may be completed with one or more the additional terms coming from one or more new measurements, giving rise to equation 6, as illustrated below: argmin

In Equation 6, l refers to a regularization parameter. For example, l may refer to a Thikhonov regularization parameter t; refers to the one or more new measurements taken, which include one or more estimated times of arrival of the one or more acoustic signals 310. Further, to add additional information to the system, one or more locations of subsea unmanned vehicle may cover a wide range of angular movements. For example, one or more of the calibration methods may use one or more specific navigation patterns combined with an ability to localize subsea unmanned vehicle 302. It may be assumed that subsea unmanned vehicle 302 is equipped with an INS. An INS may be made of an EVTU, a DVL and a Kalman filter, which may each provide a good estimation of the location of subsea unmanned vehicle 302 on a short period of time. For example, an INS localization estimate on one or more short periods may be used to feed a calibration process for unmanned vehicle localization process 10. As a result, in the case of multiple measurement over a short duration, only the initial broad angles may be unknown. Further, some of the initial broad angles may be derived from the INS data.

[00114] With regards to the calibration method used in conjunction with unmanned vehicle localization process 10, FIG. 24 provides an illustration of the calibration step 2402. Specifically, after the calibration occurs, the calibration results may be used to determine a location of one or more of the at least three receiver elements, which may be comprised of one or more hydrophones. The locations of the one or more hydrophones 2404 may be taken with one or more relative times of arrival 2406 of one or more acoustic signals 310 on each of the one or more hydrophones to be processed through inverse problem processing 2408. Inverse problem processing 2408 may use, for example, a Gauss-Newton method. One or more angles may then be provided 2410. The one or more angles may include one or more of roll and depression. In this example, calibration step 2402 may be done prior to a mission. However, calibration step 2402 may also be done at a beginning of a mission.

[00115] In one embodiment, a calibration method may be implemented. The calibration may be done before each new deployment of subsea unmanned vehicle by including one or more of the following steps. First, subsea unmanned vehicle 302 may be deployed. Next, a dive at distance in open-water from acoustic transmitter 308, which may be located at a surface, may be conducted. Sound speed velocity may be recorded during the dive. The sound speed velocity may be used to create a sound speed velocity profile with respect to one or more of subsea unmanned vehicle 302 and reference unit 306 One or more calibration behaviors may be performed on subsea unmanned vehicle 302. Subsea unmanned vehicle 302 perform a predefined set or rotations and translations and may further estimate a time of arrival of one or more surface pings on each of the at least three receiver elements. Further, local calibration on subsea unmanned vehicle 302 may be performed based on the received time of arrival of the one or more surface pings on each of the at least three receiver elements. Bending of one or more rays may be estimated using the measured sounds velocity profile on either reference unit 306 or subsea unmanned vehicle 302. Further, a global calibration may be performed by compensating for an ending of one or more rays.

[00116] In some embodiments, the above discussed calibration method may be expanded to a clock offset calibration per sensor. Depending on the hardware architecture, one or more time offsets may occur among one or more data streams coming from at least three receiver elements. The time offset variable may be added into Equation 5.

[00117] In one embodiment according to the present disclosure, one or more behaviors of subsea unmanned vehicle 302 may be altered using a calculated sound velocity profile.

[00118] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems and methods and according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[00119] The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting of the disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

[00120] The corresponding structures, materials, acts, and equivalents of means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present disclosure has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the disclosure in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the disclosure. The embodiment was chosen and described in order to best explain the principles of the disclosure and the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.

[00121] Although a few example embodiments have been described in detail above, those skilled in the art will readily appreciate that many modifications are possible in the example embodiments without materially departing from the scope of the present disclosure, described herein. Accordingly, such modifications are intended to be included within the scope of this disclosure as defined in the following claims. In the claims, means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Thus, although a nail and a screw may not be structural equivalents in that a nail employs a cylindrical surface to secure wooden parts together, whereas a screw employs a helical surface, in the environment of fastening wooden parts, a nail and a screw may be equivalent structures. It is the express intention of the applicant not to invoke 35 U.S.C. § 112, paragraph 6 for any limitations of any of the claims herein, except for those in which the claim expressly uses the words‘means for’ together with an associated function.

[00122] Having thus described the disclosure of the present application in detail and by reference to embodiments thereof, it will be apparent that modifications and variations are possible without departing from the scope of the disclosure defined in the appended claims.