被动目标自适应跟踪算法仿真研究

针对纯方位被动目标跟踪中，直角坐标系下的扩展卡尔曼滤波器容易发散，而导致滤波精度很差，该文提出了一种直角坐标系下的自适应卡尔曼滤波算法，对虚拟噪声进行估计，动态补偿观测模型线性化误差，消减系统的观测误差，并对其滤波理论及其算法进行了研究和仿真。仿真结果表明，该算法提高了滤波的稳定性、快速性和精确性，优于一般的扩展卡卡尔曼滤波算法，收到了良好的效果。

Simulation and Research of Passive Target Adaptive Tracking Algorithm

Concerning the problem of instability and low accuracy of the passive filter in bearings-only target tracking, a modified polar coordinate adaptive extended Kalman filter(MPAEKF) algorithm is presented. Owing to estimating the statistics of the state virtual noise on-line, it overcomes the bad effect caused by linearization of nonlinear state model. The simulation result shows that the MPAEKF improves the filter convergence rate and the accuracy.