一种水下静止平台对目标运动参数的联合估计方法

Combined Algorithm for Motion Parameter Estimation of Target on Underwater Static Platform

针对方位-频率目标运动分析在水下静止小平台上的应用,提出了一种基于方位-频率测量的目标运动参数联合估计方法。该方法以最小二乘估计算法估计结果作为卡尔曼滤波估计算法的初值,解决了迭代初值对卡尔曼滤波估计算法的估计性能影响较大的问题,从而提高了算法的收敛速度和估计精度。湖试结果表明:该算法具有较好的估计性能,可以作为解决水下静止平台对目标被动定位问题的一种有效方案。

For the purpose of the use of bearing-frequency target motion analysis on underwater static platform,a target motion parameter estimation method is proposed according to bearings and frequency information. The initial value in the iteration of the Kalman filter is set with the least square estimation,resulting in faster convergence and more accurate estimation results. Real test results show that the proposed method has good convergence rate and accuracy,which can be used effectively to achieve the underwater passive localization of target.