基于收敛方差跟踪的水下目标运动分析

An Algorithm for Underwater Target Motion Analysis(TMA) Based on Convergence Variance Tracking

水下目标的被动跟踪由于隐蔽性好, 有着很强的需求背景。本文提出了基于收敛方差跟踪的水下目标运动分析算法, 由于采用方位频率Kalman滤波, 可以得到速度渐近无偏估计, 利用速度估计值对目标位置初值进行线性估计, 进而估计目标运动状态, 采用该方法可以有效消除直接应用伪线性Kalman滤波算法引起的初值偏差, 仿真结果表明, 该方法对目标运动要素具有良好的估计性能。

Underwater TMA algorithm based on convergence variance tracking is presented in this paper. With Kalman filtering of azimuth-frequency, the asymptotic unbiased estimation of velocity is obtained to linearly estimate the target initial position and to further make the target motion estimation. Using the above algorithm, we can eliminate the initial position bias value resulted from using direct Kalman filtering algorithm of pseudo-linear estimation. Computer simulation results show that the method has a good estimation performance for the elements of target motion.