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改进扩展卡尔曼滤波算法的目标跟踪算法
引用本文:杨鹏生,吴晓军,张玉梅. 改进扩展卡尔曼滤波算法的目标跟踪算法[J]. 计算机工程与应用, 2016, 52(5): 71-74
作者姓名:杨鹏生  吴晓军  张玉梅
作者单位:1.陕西师范大学 计算机科学学院,西安 7100622.西北工业大学 自动化学院,西安 710072
摘    要:为了获得更加理想的运动目标跟踪效果,提出了一种基于改进扩展卡尔曼滤波的目标跟踪算法。构建时间差和信号到达方向的观测方程,利用几何和代数关系化简得到伪线性模型,通过改进卡尔曼滤波算法对目标运动轨迹进行跟踪,采用仿真实验对算法性能进行测试。结果表明,相对于传统扩展卡尔曼滤波算法,在相同条件下,该算法不仅提高了目标跟踪精度,而且使目标跟踪结果更加稳定。

关 键 词:单站无源定位  扩展卡尔曼滤波  目标跟踪  方位角变化率  

Target tracking method based on improved Kalman filter algorithm
YANG Pengsheng,WU Xiaojun,ZHANG Yumei. Target tracking method based on improved Kalman filter algorithm[J]. Computer Engineering and Applications, 2016, 52(5): 71-74
Authors:YANG Pengsheng  WU Xiaojun  ZHANG Yumei
Affiliation:1.College of Computer Science, Shaanxi Normal University, Xi’an 710062, China2.School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Abstract:In order to obtain more ideal effect of moving target tracking, a target tracking method for tracking based on improved Kalman filter algorithm is proposed in this paper. The observation equation is constructed based on the time difference of arrival and the direction of arrival of the emitter, and pseudo linear model is obtained by using geometry and algebra simplification, Kalman filter algorithm is used to track target, the simulation experiment is carried out to test the performance of the algorithm. The simulation results show that, compared with the traditional extended Kalman filtering algorithm, this proposed algorithm not only improves the accuracy of target tracking but also improves the stability of target tracking under the same conditions.
Keywords:single station passive location  extended Kalman filter  target tracking  azimuth angle changing rate  
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