基于变分贝叶斯的星载雷达非线性滤波

doi:10.7527/S1000-6893.2020.24395

Abstract

Abstract: Spaceborne radars play an important role in early warning defense systems because of their unique advantages such as wide detection range, long distance and all-weather surveillance capability. Due to the high-speed movement of the platform and the strong nonlinear observation function, high-accuracy target tracking for spaceborne radars is difficult. In this paper, we propose a variational Bayes-based nonlinear filtering method, which transforms the nonlinear state estimation problem into an optimization problem. The analytical solution is obtained via a closed-loop iteration manner. Moreover, a pitch angle estimation method is presented using the a priori information of target height. Simulation results show that, compared with the extended Kalman filter, unscented Kalman filter, and the converted measurement Kalman filter, the proposed variational Bayes-based nonlinear filtering method achieves the best estimation accuracy.

Key words: spaceborne radars, target tracking, variational Bayes, nonlinear filtering, pitch estimation

CLC Number:

YAN Wenxu, LAN Hua, WANG Zengfu, JIN Shuling, PAN Quan. Nonlinear filtering for spaceborne radars based on variational Bayes[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020, 41(S2): 724395-724395.

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Nonlinear filtering for spaceborne radars based on variational Bayes

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