过程噪声方差实时补偿的非定轨目标跟踪  

A Non-orbit Target Tracking Filter Based on Variance Compensation of Process Noises

作　　者：田俊林[1,2,3] 付承毓[1,2] 唐涛[1,2] 于伟[1,2,3,4] 

机构地区：[1]中国科学院光电技术研究所,成都610209 [2]中国科学院光束控制重点实验室,成都610209 [3]中国科学院研究生院,北京100049 [4]徐州空军学院,江苏徐州221000

出　　处：《光电工程》2012年第1期68-73,共6页Opto-Electronic Engineering

基　　金：中国科学院重点实验室预研基金资助课题(A09K002)

摘　　要：针对非定轨目标跟踪问题中过程噪声统计特性未知的特点,提出了一种实用的对过程噪声方差进行实时补偿的目标跟踪算法。该算法根据强跟踪滤波器的思想,通过实时检测新息序列来修正卡尔曼滤波算法中的状态预测误差协方差矩阵,进而对未知的过程噪声方差矩阵进行实时地补偿。由于存在新息检测机制,该算法能够有效地规避表征建模不确定性的过程噪声统计特性未知的问题,对于建模不确定性具有一定的适应能力。通过对一旋转靶标跟踪问题的仿真试验,证明了该方法的有效性。In order to overcome the uncertainty of target motion in non-orbit target tracking problems,a practical filtering algorithm,which compensated the variance of process noises,was proposed in this work.Based on the principle of strong tracking filter,the prediction covariance in Kalman filtering equations was modified real-time by monitoring innovation sequence in the proposed algorithm.In this way,the unknown variance of process noises was compensated effectively.Due to innovation-monitoring procedure,the proposed algorithm was adaptive to the uncertainty of target motion model.Simulation results of a rotary target tracking problem show the validity of the proposed algorithm.

关 键 词：目标跟踪 非定轨 强跟踪滤波 新息序列 渐消因子 

分 类 号：TN953[电子电信—信号与信息处理]