基于扩展集员滤波与信息几何的机动目标跟踪  

Maneuvering target tracking with the extended set-membership filter and information geometry

作　　者：孙伟[1] 赵心悦 张玉玺[2] 孙进平[2] SUN Wei;ZHAO Xinyue;ZHANG Yuxi;SUN Jinping(Nanjing Electronic Technology Research Institute,Nanjing Jiangsu 210039,China;School of Electronic and Information Engineering,Beihang University,Beijing 100191,China)

机构地区：[1]南京电子技术研究所,江苏南京210039 [2]北京航空航天大学电子信息工程学院,北京100191

出　　处：《太赫兹科学与电子信息学报》2018年第5期786-790,795,共6页Journal of Terahertz Science and Electronic Information Technology

基　　金：国家自然科学基金资助项目(61471019)

摘　　要：面对当前日益复杂的雷达跟踪目标和环境,广泛应用的卡尔曼滤波及其扩展类算法虽然能以较少的计算量得到较好的跟踪效果,但其要求过程噪声与量测噪声符合零均值高斯分布,否则会导致滤波发散。为解决系统状态及噪声未知但有界情况下的机动目标跟踪问题,介绍了一种扩展集员滤波机动目标跟踪算法,并辅以基于信息几何的跟踪性能监测处理。通过仿真分析验证了基于集员滤波与信息几何的机动目标跟踪边界约束性能及跟踪准确度较好,且能通过统计流形距离的变化来探测目标是否发生机动。With the increasingly complex tracking targets and environment in radar application,the widely used Kalman filter and extended versions can track targets with less few calculations.However,it requires the system noises including process noise and measurement noise in a zero mean and Gaussian case,otherwise,it may lead to poor performance.In order to solve the problem of tracking a maneuvering target,when process and measurement noises are unknown-but-bounded,an extended set-membership filter and the tracking quality method based on information geometry are proposed.Simulation analysis shows that the set-membership filter provides distinct advantages in tracking performance including state bounding and tracking accuracy,and the maneuver behaviors of target can be identified through counting the changes of distances on the manifold.

关 键 词：目标跟踪 集员滤波 信息几何 机动监测 

分 类 号：TN953[电子电信—信号与信息处理]