Target tracking algorithm based on improved unscented Kalman filter

被引：0
|
作者：
Yingyan, Wang [1 ]
Rui, Zeng [1 ]
机构：
[1] School of Electro-Mechanical and Information Technology, Yi Wu Industrial & Commercial College, Yi Wu,Zhejiang,322000, China
来源：
Open Automation and Control Systems Journal | 2015年 / 7卷
关键词：
Bandpass filters - Clutter (information theory) - Wavelet transforms - Kalman filters;
D O I：
10.2174/1874444301507010991
中图分类号：
学科分类号：
摘要：
In order to improve the performance of target tracking and solve the defects of unscented Kalman filter, a target tracking algorithm based on improved unscented Kalman filter is proposed in this paper. Firstly, the fading factor is introduced into the filter based on strong tracking filter to avoid the filter divergence, and then wavelet transform is used to estimate the statistical characteristics of measurement noise to improve unscented Kalman filter tracking ability, finally the simulation experiment is used to test the performance of algorithm. The results show that the proposed algorithm increases adaptive ability of target tracking, and obtain good performance for weak maneuvering and non maneuvering target tracking, and fastens the tracking speed. © Yingyan and Rui; Licensee Bentham Open.
引用
收藏
页码：991 / 995
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