"System for distributed mapping of atmospheric attenuation in satellite communications"

Technical Field

The present invention describes a system for distributed mapping of atmospheric attenuation in satellite communications .

Background art

A typical Radio Frequency (RE) propagation model provides information about the expected attenuations that a communication link suf fers . Predicting the attenuations of satellite communications is even more hard to obtain due to the di f ficulty of isolating the di f ferent attenuation phenomena ( Ionospheric scintillation, Rain attenuation, Gaseous Absorption, ... ) . Moreover, there are other attenuating ef fects on the ground soil such as di f fraction, shadowing and multi-path, that depend on the urban environment where the receiver is located .

Presently, there are several propagation models that quanti fy the attenuation that a satellite signal suf fers in urban and rural environments for di f ferent frequency ranges such as the Okumura model , the Hata model , the COST-231 model , Ericsson 9999 , etc . The models used for other existing bands are speci fic to certain environment characteristics ( e . g . urban canyon or open sky environment ) . As a result , there is a need for more realistic model that takes in to account the various local conditions a vehicle faces . Moreover, there is the need for the model to be adapted in relation to local conditions to be more accurate in the presence of any set of attenuation ef fects , Besides the di f ferent attenuation phenomena at ground level , this modeling also should reflect the various atmospheric attenuations that impact the signal .

To distribute the correction service information by satellite , there are broadcast satellites used that are located on geostationary positions around the globe . Their technical conditions ( e . g . signal power/ strength) are defined by the service provider . So , the goal of evaluating the loss of signal over the earth' s orbit , in particular the signal attenuation on over the atmosphere , can also be determined by the Free Space Path Loss ( FSPL ) . Nowadays , the existing models that may help to estimate the said signal attenuation over the atmosphere , have been derived from information of speci fic receiving stations that are distributed on earth at fixed positions . In between, these fixed stations estimations are made to define the signal attenuation, but their precision is limited .

The proposed system aims to overcome the above-mentioned limitations of know prior art as described hereafter .

Summary

The present invention describes a system for distributed mapping of atmospheric attenuation in satellite communications comprising a satellite receiver and an antenna, said antenna being connected to the satellite receiver, and both being comprised in a vehicle ; and a storage unit and a data transmis sion module , said storage unit being connected both to the satellite receiver and to the transmission module ; wherein the satellite receiver is configured to collect a satellite RF signal data and transmit it to a remote server through the data transmission module .

In a proposed embodiment of present invention, the storage unit is configured to store satellite RF signal data collected by the satellite receiver .

Yet in another proposed embodiment of present invention, the data transmission module is configured to transmit the satellite RF signal data to the server through a communication link .

Yet in another proposed embodiment of present invention, the transmitted satellite RF signal data to a remote server through the data transmission module , is processed in a processing unit resorting to machine learning algorithms and/or statistical analysis , configured to provide an improved signal attenuation estimation propagation model .

Yet in another proposed embodiment of present invention, the server comprises a dataset conditioning unit configured to perform the conversion of a provided date from the satellite RF signal data, and to trans fer said converted date to the processing unit .

Yet in another proposed embodiment of present invention, the processing unit is configured to calculate a signal attenuation value for each point and/or location of the provided satellite RF signal data and generate real world geographical maps with real time information based on filtered data and/or unfiltered data, said filtered data comprising at least one of an astronomic phenomena, weather phenomenon, ionospheric conditions and daytime .

Yet in another proposed embodiment of present invention, the machine learning algorithms and statistical analysis , to ensure the proces sing, decisioning and statistical treatment of exponential growing amounts of data .

Yet in another proposed embodiment of present invention, the collected satellite RF signal data comprises at least one of a C/NO measurement , vehicle info and timestamp .

The present invention further describes the method to improve distributed mapping of atmospheric attenuation in satellite communications , according to the system previously described, comprising the steps of creating a real world geographical map ; merging the calculated signal attenuation information into the created geographical map ; define a position in the geographical map based on maps/position standards ; allocate the signal attenuation based on the defined position; apply a color code for the attenuation value ; update the geographical map with the related color code .

In a proposed embodiment of the above-mentioned method, the color code for the attenuation value is related to the latitude , longitude and elevation known values .

General Description

The present invention describes a system for distributed mapping of atmospheric attenuation in satellite communications . The created system allows to obtain an RF propagation model through the data collection of satellite signals , via receivers implemented in vehicles .

The vehicles , through normal driving/operation, will receive RF signals from the satellites , measure the quality of said RF signal and store the related data . The vehicle will operate as a replacement for the fixed receiving stations . The satellite RF signal data wil l be then transmitted to a Central Processing Unit ( CPU) installed in a data server for processing in order to create an RF propagation model , with additional details for speci fic land regions in the globe . This allows to obtain a more accurate RF propagation model for all the regions that are under observation .

The RF propagation model , obtained through the herein proposed solution, accounts for all the attenuations that impact the signal from the satellite to the receiver , for both urban and open-sky environments . Knowing the signal loss present in the vehicles ' receiving elements , it is possible to determine the signal condition when sent out at the satellites , so it is possible to calculate the atmosphere signal attenuation for the position . The RF propagation model can be obtained for whatever frequency band the satellite is transmitting .

For the proposed invention, it should be considered a fleet of vehicles comprising satellite receivers configured to determine the Carrier-to-noise-ratio ( C/No ) of a satellite signal received at a time interval tacquisition, and storing said information, together with the vehicle identi fication ( ID) , vehicle position, vehicle spatial orientation and timestamp, on a physical storage device . The vehicle position is used to determine the signal elevation angle , and the vehicle spatial orientation provides the azimuth angle in which the signal is received .

With the two angles , elevation angle and azimuth angle , the antenna gain in the signal direction is obtained, which is an important factor in the signal reception .

All vehicles are also equipped with a communication transmitter that allow said vehicles to deliver the collected data, through mobile communications ( e . g . 4G, 5G, ... ) to a centrali zed database . I f a stable mobile connection is available for a determined period of time , the data can also be trans ferred without being stored in the vehicle . All the signal data is formed into a dataset that can then be processed statistically . The timestamp can be used as a time reference to acquire atmospheric data at the time of the measurements and use the data to enhance the dataset .

The dataset can also be used as input to a Machine learning algorithm to extrapolate the model for locations that have the same conditions , as the places where the vehicles have travelled ( example : highways with the same elevation angles ) .

Therefore , the use of vehicles equipped with signal receivers on board aims to collect data from the satellites , like a swarm of data collectors , in order to to send the collected data signals and generate the maps of signal attenuation . The more vehicles participate in providing information on received signals the better data quality can be achieved in a computing center . Brief description of the drawings

For better understanding of the present application, figures representing preferred embodiments are herein attached which, however, are not intended to limit the technique disclosed herein.

Fig. 1 - illustrates the proposed system for distributed mapping of atmospheric attenuation in satellite communications, wherein the reference numbers refer to:

100 - vehicle;

101 - antenna;

102 - satellite receiver;

103 - storage unit;

104 - data transmission module;

105 - satellite RF signal data, i.e., C/No measurement, vehicle info and timestamp;

150 - communication link / data transfer;

200 - server;

201 - processing unit;

2011 - machine learning algorithms;

2012 - statistical analysis;

202 - dataset conditioning unit;

300 - propagation model.

Fig. 2 - illustrates a practical application of the system for distributed mapping of atmospheric attenuation in satellite communications, wherein the reference numbers refer to:

100 - vehicle;

101 - antenna;

150 - communication link / data transfer; 200 - server;

400 - satellite;

403 - atmosphere attenuation.

Description of Embodiments

With reference to the figures, some embodiments are now described in more detail, which are however not intended to limit the scope of the present application.

A particular embodiment of the proposed system disclosed herein is intended for the distributed mapping of atmospheric attenuation in satellite communications. The proposed system resorts to the use of a vehicle (100) to obtain and collect the data from RF satellite signals (105) , said vehicle (100) being equipped with a satellite receiver (102) further connected to an antenna (101) . Additionally, the vehicle (100) also incorporates a storage unit (103) , a data transmission module (104) and additional position information from different sensors, e.g., from an Inertial Measurement Unit (IMU) processed by a microcontroller, being said storage unit (103) connected to the additional sensormodules and the satellite receiver (102) to collect satellite signal data (105) , which includes C/No signal measurements, vehicle info and timestamps. The satellite signal data (105) can be transferred directly through the transmission module (104) to a server (200) if stable mobile or wireless connection is available for a determined period of time, or it can also be transferred to said server (200) through the same transmission module (104) after it being stored in the storage unit (103) . The server (200) is mainly composed of a processing unit (201) and a dataset conditioning unit (202) , which after receiving the satellite signal data (105) through the communication link (150) established by the data transmission module (104) , promotes the data (105) processing. The satellite signal data (105) will be analyzed in the processing unit (201) , in particular through incorporated machine learning algorithms (2011) and/or through statistical analysis (2012) , which, afterwards, will be conditioned in the dataset conditioning unit (202) .

As the data provided to the server (200) contains positioning information, a time stamp, as well as the satellite signal data, the signal processing unit (201) is able to generate a map of an area (landscape) for the signal attenuation at different locations. This data allows the calculation/processing of different kind of maps:

- real world maps with real time information on signal attenuation by dynamic processing (big data)

- maps with filtered data over time, e.g. : a) If an astronomic phenomena like sun eruption (causing sun winds) takes place, or a heavy weather phenomenon will occur (like thunderstorms) b) Over seasons of the year (ionospheric conditions are expected to change within the periods of the year) c) By differentiation btw. Night and daytime (this is expected to have an impact as well) .

The mentioned map information can be used to develop / adapt models for signal attenuation in different locations, e.g., a map with model for above mentioned a) , b) and/or c) for Europe, Americas, Asia, but not limited to these areas, and