双基阵纯方位TMA的一种自适应算法仿真

Research on an Adaptive Algorithm for Bearing-only TMA Using Two Arrays

为了改善普通卡尔曼滤波算法在观测噪声统计特性未知情形下处理双基阵纯方位TMA问题时的滤波性能,提出了一种在线估计观测噪声统计特性的自适应卡尔曼滤波算法,计算机仿真结果表明,该算法能够在线估计观测噪声统计特性,使Kalman滤波器始终处于稳定状态,并精确地估计目标的运动参数,同时指出了自适应算法的初值选取对滤波收敛速度的重要影响,当滤波初值选取恰当时会明显加快滤波收敛过程。

In order to improve the property of the normal Kalman filter when deal with the bearingonly TMA using two arrays in the situation which the measurement noise statistical property is unknown, an adaptive Kalman filter algorithm which estimates the measurement noise statistical property on line is given in this paper. The simulation results shows that by estimating the measurement noise statistical property on line the Kalman filter keep in stability all the time and estimate the movement elements of the target precisely. At the same time point out that the selection of the initial state affected the convergent rate greatly ,it would improve the convergent rate if the initial state is selected properly.