基于状态矢量融合的多基地无源目标运动分析

Passive target motion analysis of multiple arrays based on state vector fusion

在多基地独立观测估计的基础上,采用对状态矢量进行数据融合的方法对无源目标运动分析(以下简称ＴＭＡ)问题进行了研究。在双基地的条件下,讨论了当双基地的无源声呐匀采用容易得到的目标方位角、频率的数据测量为输入时的无源ＴＭＡ问题。利用伪线性方法或扩展Ｋａｌｍａｎ滤波方法作预处理后,将所得到的各状态矢量的预估计送入融合中心再进行数据融合,最后实现对目标的最终估计。计算机仿真结果表明:状态矢量融合的方法能够进一步提高对目标运动参数的估计精度,能有效地实现无源ＴＭＡ问题的估计。

The method for the state vector fusion which used to solve the problem of passive target motion analy-sis(TMA) is studied in this paper based on respective passive sensor measurement and estimation of multiple arrays. In the condition of two arrays, bearings and frequency of target gained easily by each sensor in arrays are input. The results of the state vector using peseudolinear processing and extended Kalman filter is transmitted to the fusion center, then the optimal estimation of target is presented. The results of simulation experiment shows that the performance of target motion parameter estimation by the state vector fusion algorithm can be improved forthcoming.