自适应高阶容积卡尔曼滤波在目标跟踪中的应用

doi:10.7527/S1000-6893.2015.0180

Abstract

Abstract:

An improved high-degree cubature Kalman filter(HCKF)combined with strong tracking filter (STF) algorithm is proposed to overcome the decreasing estimation precision of conventional cubature Kalman filter (CKF) when system states suddenly change and an adaptive high-degree cubature Kalman filter (AHCKF) is established. Based on the high-degree spherical-radial cubature rule, the new method can obtain better accuracy than conventional CKF. Meanwhile, by introducing the STF into HCKF and modifying the predicted states' error covariance with a fading factor, the residual sequence is forced to be orthogonal so that the robustness of the filter and the capability to deal with uncertainty factors are improved. A maneuvering target tracking problem with unknown sudden states' changes in system states is used to test the performance of the proposed filter. The simulation results indicate that AHCKF can achieve good filtering performance and effectively overcome the precision decrease of filters when states' changes suddenly occur, with greater robustness and better system adaptive capacity than the conventional CKF, HCKF, interacting multiple mode-based CKF (IMM-CKF) and adaptive cubature Kalman filter (ACKF).

Key words: nonlinear estimation, target tracking, adaptive filtering, cubature Kalman filtering, high-degree spherical-radial cubature rule

CLC Number:

V557

CUI Naigang, ZHANG Long, WANG Xiaogang, YANG Feng, LU Baogang. Application of adaptive high-degree cubature Kalman filter in target tracking[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(12): 3885-3895.

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Application of adaptive high-degree cubature Kalman filter in target tracking

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