基于IMM的改进去偏转换测量目标跟踪算法  

An IMM Based Modified De-Biased Converted Measurement Target Tracking Algorithm

作　　者：张新宇[1] 吴盘龙[1] 张廉政 

机构地区：[1]南京理工大学自动化学院,南京210094

出　　处：《电光与控制》2014年第12期40-44,共5页Electronics Optics & Control

基　　金：国家自然科学基金(61104196);江苏省自然科学基金(BK20131352)

摘　　要：针对机动目标跟踪,提出一种基于交互式多模型的改进去偏转换测量卡尔曼滤波算法(IMM-MDCMKF),该算法在多模型中使用了改进的去偏转换测量卡尔曼滤波算法(MDCMKF)。MDCMKF算法先通过引入状态估计值对转换误差协方差进行修正,有效地降低了测量噪声对此协方差的影响,然后将修正的转换误差协方差用于目标跟踪问题中的去偏转换测量卡尔曼滤波算法。最后进行的Monte Carlo仿真结果表明,所提算法跟踪精度优于IMM-EKF算法和IMM-DCMKF算法。To the issue of maneuvering target tracking,a modified de-biased converted measurement Kalman filter was proposed based on Interacting Multiple Model （IMM-MDCMKF）,which used a Modified De-biased Converted Measurement Kalman Filter （MDCMKF） in multi-model.The MDCMKF algorithm improved the converted error covariance matrix by introducing state estimated value,and effectively reduced the effect of measurement noise on the covariance.Then the modified converted error covariance matrix was utilized to implement the DCMKF algorithm for a target tracking scenario.Finally,Monte Carlo simulation was carried out,and the results show that the accuracy of algorithm is superior to that of the IMM-EKF algorithm and IMM-DCMKF algorithm.

关 键 词：机动目标跟踪 状态估计值 IMM MDCMKF IMM—MDCMKF 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计] TP274[自动化与计算机技术—检测技术与自动化装置]