An Improved Interacting Multiple Model Filtering Algorithm Based on the Cubature Kalman Filter for Maneuvering Target Tracking

被引:60
|
作者
Zhu, Wei [1 ]
Wang, Wei [1 ]
Yuan, Gannan [1 ]
机构
[1] Harbin Engn Univ, Coll Automat, 145 Nantong St, Harbin 150001, Peoples R China
来源
SENSORS | 2016年 / 16卷 / 06期
基金
中国博士后科学基金;
关键词
target tracking; cubature Kalman filter; unscented Kalman filter; interacting multiple models;
D O I
10.3390/s16060805
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
In order to improve the tracking accuracy, model estimation accuracy and quick response of multiple model maneuvering target tracking, the interacting multiple models five degree cubature Kalman filter (IMM5CKF) is proposed in this paper. In the proposed algorithm, the interacting multiple models (IMM) algorithm processes all the models through a Markov Chain to simultaneously enhance the model tracking accuracy of target tracking. Then a five degree cubature Kalman filter (5CKF) evaluates the surface integral by a higher but deterministic odd ordered spherical cubature rule to improve the tracking accuracy and the model switch sensitivity of the IMM algorithm. Finally, the simulation results demonstrate that the proposed algorithm exhibits quick and smooth switching when disposing different maneuver models, and it also performs better than the interacting multiple models cubature Kalman filter (IMMCKF), interacting multiple models unscented Kalman filter (IMMUKF), 5CKF and the optimal mode transition matrix IMM (OMTM-IMM).
引用
收藏
页数:12
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