基于超球体单形采样的BS-UKF算法在单站无源目标跟踪中的应用  

Application of spherical simplex sampling based backward-smoothing UKF to single observer passive tracking

作　　者：朱联祥[1] 况卢娟[1] 

机构地区：[1]重庆邮电大学信号与信息处理重点实验室,重庆400065

出　　处：《重庆邮电大学学报（自然科学版）》2010年第3期298-301,391,共5页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

基　　金：重庆市科委自然科学基金项目(CSTC;2008BB2087);重庆市教委自然科学基金项目(KJ080502);重庆邮电大学博士启动项目(A2007-56)~~

摘　　要：根据单站无源目标定位跟踪模型,提出了一种基于超球体采样策略的BS-UKF(backward-smoothing unscent-ed Kalman filter)算法,并将其应用于单站无源目标跟踪。仿真分析表明,与标准比例采样的UKF(unscented kalmanfilter)和基于超球体单形采样的UKF相比,该算法在滤波精度上有显著的提高,在时间复杂度上有一定的增加,适合用于对定位精度要求较高的情况。According to the model of single observer passive location and tracking,a backward-smoothing unscented kalman filter（BS-UKF）algorithm based on spherical simplex sampling was proposed,and it was applied to single observer passive target tracking.Simulation results show that BS-UKF outperforms unscented kalman filter based on standard scale sampling and spherical simplex sampling in accuracy significantly,the BS-UKF has higher time complexity,and that it is more feasible for high accuracy application.

关 键 词：超球体单形采样 单站无源定位跟踪 后向平滑滤波 

分 类 号：TN953[电子电信—信号与信息处理] TN958.97[电子电信—信息与通信工程]