基于分布式信息融合的多传感器目标定位算法  

Research on Target Location Algorithm of Multi-Sensor Based on Distributed Information Fusion

作　　者：陈林秀 宋闯 范宇 张航 CHEN Lin-xiu;SONG Chuang;FAN Yu;ZHANG Hang(Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory,Beijing 100074,China)

机构地区：[1]复杂系统控制与智能协同技术重点实验室,北京100074

出　　处：《指挥控制与仿真》2020年第2期28-33,共6页Command Control & Simulation

摘　　要：针对单平台多传感器目标跟踪定位中的状态信息融合问题,以主/被动雷达为研究对象,基于分布式信息融合结构,首先分别探究了在主动和被动雷达探测条件下几种常用的非线性滤波算法的性能;然后选择对应性能最佳的方法,结合带反馈的协方差交叉融合(CI)算法,在考虑主/被动雷达正常工作和主动雷达在不同时间被干扰的情况下,进行了目标状态的融合。仿真结果表明,主/被动雷达正常工作条件下,利用信息融合算法得到的状态估计优于依赖单一雷达观测信息的目标状态估计。主动雷达在独自跟踪滤波收敛后被有源干扰时,基于信息融合方法得到的目标状态估计比仅依赖被动雷达量测信息得到的状态估计更稳定,且精度更高。Aiming at the problem of state information fusion in single platform multi-sensor tracking and positioning, and taking active/passive radar for example,based on distributed information fusion structure, firstly, the performance of several commonly used non-linear filtering algorithm under active and passive radar observation conditions is explored. Then, the corresponding best performance methods is selected separately, and combined with the fusion algorithm of covariance intersection(CI)with feedback, the target state fusion is carried out considering the normal operation of active and passive radar and the jamming of active radar at different times. The simulation results show that the state estimation based on active and passive radar information fusion is more stable and accurate than that based on single radar observation information when radars work normally. If the active radar is jammed by active interference after convergence of tracking filtering alone, the target state estimation based on information fusion method is more stable and accurate than that estimated by passion radar filtering alone.

关 键 词：多传感器 信息融合 非线性 状态估计 有源干扰 

分 类 号：TN953[电子电信—信号与信息处理]