PURPOSE: To perform the reverse analysis of an unknown parameter with a high precision and high efficiency.

CONSTITUTION: Based on measurement data of a structure and a given assumed value containing the assumed value of an unknown parameter to be estimated, extension Kalman's filter processing is repeatedly executed. A weighting means 44 effects weighting of the error coveriance value of an estimate obtained from the result. A second processing means 45 repeatedly effects extension Kalman's filter processing by means of an estimate, determined by a first processing means 42, and a weighted dispersion value, serving as an initial value. A convergence deciding means 48 judges convergence of the estimate and when convergence is not effected, an error covariance value determined by the second processing means 45 is weighted by the weighting means 44. The result and an estimate determined by the second processing means 45 are set as a new initial value, and the second processing means 45 is caused to effect processing again.