标准粒子滤波(PF)的重要性函数的选取方法会导致状态估计过于依赖模型,且在重采样过程中可能会发生粒子贫化现象,针对PF在角闪烁背景下的目标跟踪过程中精度不足的问题,提出了一种改进的扩展卡尔曼粒子滤波(EKPF)算法,并将其应用在角闪烁噪声背景下的目标跟踪问题中,仿真结果表明该算法的可行性和优越性。 The selection method of the importance function of the standard particle filter (PF) leads to the state estimation being too dependent on the model, and the phenomenon of particle depletion may occur during the resampling process. In view of the lack of accuracy in PF target tracking under the angle scintillation Problem, an improved Extended Kalman Filter (EKPF) algorithm is proposed and applied to the target tracking problem under the background of angular flicker noise. The simulation results show the feasibility and superiority of this algorithm.