角闪烁背景下基于改进EKPF算法的目标跟踪
发布时间：2019-08-20 11:59
【摘要】：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。
[Abstract]:The selection method of importance function of standard particle filter (PF) will lead to state estimation being too dependent on the model, and particle dilution may occur in the process of resampling. An improved extended Kalman particle filter (EKPF) algorithm is proposed to solve the problem that PF is not accurate in the process of target tracking in the background of angular flicker, and it is applied to the problem of target tracking in the background of angular flicker noise. The simulation results show the feasibility and superiority of the algorithm.
【作者单位】： 海军航空工程学院;92941部队;
【分类号】：TN713;TN953
，
本文编号：2528606
[Abstract]:The selection method of importance function of standard particle filter (PF) will lead to state estimation being too dependent on the model, and particle dilution may occur in the process of resampling. An improved extended Kalman particle filter (EKPF) algorithm is proposed to solve the problem that PF is not accurate in the process of target tracking in the background of angular flicker, and it is applied to the problem of target tracking in the background of angular flicker noise. The simulation results show the feasibility and superiority of the algorithm.
【作者单位】： 海军航空工程学院;92941部队;
【分类号】：TN713;TN953
，
本文编号：2528606
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