基于集合Kalman滤波的目标被动跟踪系统  

Passive Target Tracking System Based on Ensembly Kalman Filter

作　　者：崔波[1] 张家树[1] 杨宇[2] 

机构地区：[1]西南交通大学,成都610031 [2]中国电子科技集团公司第三十研究所,成都610041

出　　处：《火力与指挥控制》2013年第1期7-9,17,共4页Fire Control & Command Control

基　　金：国家自然科学基金(60572027);西南交通大学青年教师科研起步基金资助项目(2009Q048)

摘　　要：针对传统的目标被动跟踪技术计算量大和滤波不稳定的问题,引入了基于集合预报思想的集合Kalman滤波算法,联合利用到达角和多普勒频率信息实现机动目标被动跟踪,探讨了不同条件下集合成员的数量和初始集合的差异对目标被动跟踪性能的影响。仿真结果表明,集合Kalman滤波能够应用到目标被动跟踪系统中,并且跟踪性能更好。To the problem of expensive computation and instable filter,the ensembly Kalman filter（EnKF） based on the ensemble forecasted thought is introduced to passive target tracking system.The algorithm uses the measurements of Doppler frequency and direction-of-arrival to estimate position and velocity of the target,and the affection of target tracking performance from different number of ensemble members and initial ensemble is verified respectively.Simulation shows that the ensembly Kalman filter can be applied to passive target tracking system and offer much advantage in tracking performance.

关 键 词：集合KALMAN滤波 目标被动跟踪 非线性 跟踪性能 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]