Method for overcoming radar extended Kalman track filtering divergence

Abstract

The invention discloses a method for overcoming radar extended Kalman track filtering divergence. The method comprises the following steps: carrying out system modeling according to a conventional extended Kalman filtering method; assuming that the state of the track filtering k moment is X(k|k), and the covariance matrix is P(k|k); performing one-step prediction on the state at the moment k to obtain a prediction state and a prediction covariance matrix at the moment k + 1; using the correction matrix or the correction coefficient to carry out anti-divergence processing on the prediction covariance matrix to obtain a corrected prediction covariance matrix; updating a prediction state through a measured value of a radar detection target system at the k + 1 moment, calculating an innovation vector, an innovation covariance matrix and a Kalman gain matrix, and replacing an original prediction covariance matrix with the corrected prediction covariance matrix in the calculation process; and calculating a target state and a covariance matrix at the k + 1 moment. According to the invention, the filtering output trend is corrected, the precision of the filtering result is improved, and the divergence condition in the track filtering is effectively overcome.

Description

technical field [0001] The invention relates to the technical field of Kalman track filter data processing, in particular to a method for overcoming the divergence of radar extended Kalman track filter. Background technique [0002] Track filtering is an important part of the radar data processing algorithm, which can filter the radar detection points to form a continuous track output, effectively improving the accuracy of radar target detection and tracking. The extended Kalman filter is the most commonly used track filtering algorithm. The conventional extended Kalman filter algorithm realizes the optimal estimation of the system state by establishing the system state equation and combining the actual observation data of the system. [0003] Problems and shortcomings of current technology: [0004] 1) In the field of radar air-to-air detection, especially in military scenarios, the detection target is often a high-speed, high-maneuvering target, and conventional target mo...

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Problems solved by technology

[0008] Purpose of the invention: In order to solve the problem that the target motion equation model in the radar track filter cannot accurately describe the target motion characteristics for a long time, resulting in the divergence of the target filter track, the present invention provides a method for overcoming the divergence of the radar extended Kalman track filter. Correct the filtering output trend, improve the accuracy of filtering results, and overcome the divergence that may occur in track filtering

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