UKF算法及其在纯方位目标跟踪中的应用  

UKF Algorithm and its Application to Bearing-only Target Tracking

作　　者：李景熹[1] 谷美邦[1] 王树宗[2] 王宇 

机构地区：[1]海军驻426厂军代室,辽宁大连116005 [2]海军工程大学海军兵器新技术应用研究所,湖北武汉430033 [3]总参陆航部军代局,北京100083

出　　处：《火力与指挥控制》2007年第6期91-93,共3页Fire Control & Command Control

基　　金："十五"国防重点预研基金资助项目(413040202)

摘　　要：为克服扩展卡尔曼滤波算法的缺陷,将UKF算法应用于纯方位目标跟踪问题中。该算法是一种以扩展卡尔曼滤波算法为基本框架,以贝叶斯理论和UT变换为理论基础的新型滤波算法。对UKF算法进行了深入的研究,并给出了一个纯方位目标跟踪的算例。仿真结果表明,该算法提高了滤波的稳定性和精确性,优于一般的扩展卡尔曼滤波算法,具有广泛的应用前景。For overcoming the shortcoming of extended Kalman filter, the paper applies unscented Kalman filter on bearing-only target tracking problem. This algorithm has its theory basis consisted of Bayesian theory and UT transform, and implements according to the frame of EKF. The paper studies the UKF algorithm deeply, and brings forward a simulation example about bearing-only target tracking. The simulation results shows that the UKF algorithm improves stability and accuracy of filter, and its performance excelled general extended Kalman filter, and the UKF has broad application prospect.

关 键 词：扩展卡尔曼滤波 纯方位 目标跟踪 平淡卡尔曼滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]