Augmented target tracking algorithm based on SRCKF for joint estimation of state and sensor systematic error

被引：0
|
作者：
Liu, Yu [1 ]
He, You [1 ]
Wang, Hai-Peng [1 ]
Dong, Kai [1 ]
机构：
[1] Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai,264001, China
来源：
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition) | 2015年 / 45卷 / 01期
关键词：
Clutter (information theory) - State estimation - Kalman filters - Errors - Target tracking - Bandpass filters - Numerical methods - Tracking radar;
D O I：
10.13229/j.cnki.jdxbgxb201501046
中图分类号：
学科分类号：
摘要：
Considering three dimensional target tracking systems with unknown systematic error, in order to obtain the joint estimation of target state and sensor systematic error, an augmented target tracking algorithm based on Square-root Cubature Kalman Filter (SRCKF) is proposed. The performance of proposed estimation method is analyzed with a numerical example taking account the root mean square error and average computational cost. Simulation results show that the effectiveness of the proposed algorithm is higher than that of the algorithm based on extended Kalman filter in the aspects of estimation accuracy and filtering stability. ©, 2014, Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition). All right reserved.
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页码：314 / 321
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