光电跟踪的非线性卡尔曼滤波算法  

Nonlinear Kalman Filter Method for Electro-optical Tracking

作　　者：王秋平[1] 周原[1] 康顺[1] 

机构地区：[1]东北电力大学自动化工程学院,吉林吉林132012

出　　处：《光电工程》2009年第12期7-10,26,共5页Opto-Electronic Engineering

基　　金：东北电力大学博士基金资助项目;吉林省教育厅项目;吉林市科技发展计划资助项目(20090601)

摘　　要：为得到最小方差意义下的光电跟踪目标的最优状态估计,提出将部分状态卡尔曼滤波和非线性系统的一阶线性化思想相结合,构成一种适用于非线性光电跟踪目标的卡尔曼滤波算法,并总结出详细算法结构。同时将此方法应用到非线性测量光电跟踪系统中,并与扩展卡尔曼滤波和U卡尔曼滤波进行性能对比。仿真实验结果证明,将部分状态卡尔曼滤波和非线性系统的一阶线性化思想相结合是有效可行的,而且其性能明显优于扩展卡尔曼滤波和U卡尔曼滤波。In order to obtain the optimal minimum variance state estimation for electro-optical tracking, a nonlinear Kalman filter algorithm is provided by combining reduced state Kalman filter and first-order linear in nonlinear system and the algorithm structure is summarized in detail. Then, it is applied in nonlinear measurement electro-optical tracking system and compared the performances of reduced state Kalman filter with extended Kalman filter and unscented Kalman filter. The Matlab simulation results show that combining reduced state Kalman filter and first-order linear in nonlinear system is valid, and the performance outperforms the extended Kalman filter and unscented Kalman filter

关 键 词：卡尔曼滤波 光电跟踪 最小方差估计 非线性滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] V556.7[自动化与计算机技术—计算机科学与技术]