【摘要】 为有效合理利用雷达资源和解决雷达测量值与运动状态间的非线性关系以及目标状态本身可能出现的非线性,提出了一种基于交互式多模型粒子滤波(IMMPF)的相控阵雷达自适应采样目标跟踪方法。将交互式多模型粒子滤波一步预测值的后验克拉美罗矩阵代替预测协方差矩阵,通过该矩阵的迹与某一门限值比较来更新采样周期以适应目标运动状态的变化。将该方法与基于量测转换的IMM自适应采样算法进行仿真实验,表明了该算法的有效性。更多还原

【Abstract】 In order to effectively utilize the resources of radar and solve the nonlinear relationship between radar measurement and target motion state,an adaptive sample target tracking algorithm for phased array radar based on interacting multiple model particle filter(IMMPF) is proposed.This algorithm first predicts Posterior Cramer-Rao Bound(PCRB) matrix of the target state,then updates the sample interval adapted to changing target dynamics by comparing the trace of the predicted PCRB with a certain threshold.Performances of constant and adaptive data rates are compared.Simulation results demonstrate the effectiveness of this algorithm.更多还原