Method and system for joint estimation and compensation of space-time deviation based on sequential filtering

Abstract

The invention relates to a sequential filtering-based space-time deviation joint estimation and compensation method and system. The method includes the following steps that: a UKF filtering algorithmis adopted to estimate a target state, and non-sensitive transformation is adopted to calculate a state sampling point and a corresponding weight; a prediction state sampling point, a prediction stateand a prediction state error covariance matrix are calculated with the state sampling point and the corresponding weight; a prediction measurement sampling point and a prediction measurement vector at a k-th measurement time point are calculated with the prediction state sampling point; an innovation matrix and a cross-covariance matrix between states and observations are calculated with the prediction measurement sampling point and the prediction measurement vector at the k-th measurement time point, and Kalman gain is obtained; and the estimates of an augmented state vector and an augmentedstate error covariance matrix are updated. According to the method and system of the invention, space-time deviation is adopted to augment the target state; sequential processing is performed on received sensor measurement data; the augmented state vector is estimated on the basis of a UKF method; and therefore, the simultaneous estimation of the target state and the space-time deviation is realized.

Description

technical field [0001] The invention relates to the technical field of radar target tracking, in particular to a sequential filtering-based space-time deviation joint estimation and compensation method and system. Background technique [0002] In a multi-sensor information fusion system, the possible systematic error of sensor measurement data and the time asynchrony of sensor information will affect the correct fusion of information. At present, most algorithms study the problems of time alignment and spatial deviation registration. [0003] In the prior art, a method of using Kalman filter to estimate the spatial deviation parameter of the sensor is proposed. This method uses a sensor as a reference, and uses the differential of the measured value of the target position by multiple sensors to estimate the spatial deviation parameter of the sensor. Register the other sensors to the reference coordinate system of the sensor to eliminate the sensor space deviation, which is s...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to propose a method for joint estimation and compensation of space-time deviation based on sequential filtering to realize the target state and Simultaneous Estimation of Space-Time Bias

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