發(fā)布時間：2019-08-20 11:59

【摘要】：標(biāo)準(zhǔn)粒子濾波(PF)的重要性函數(shù)的選取方法會導(dǎo)致狀態(tài)估計過于依賴模型,且在重采樣過程中可能會發(fā)生粒子貧化現(xiàn)象,針對PF在角閃爍背景下的目標(biāo)跟蹤過程中精度不足的問題,提出了一種改進(jìn)的擴(kuò)展卡爾曼粒子濾波(EKPF)算法,并將其應(yīng)用在角閃爍噪聲背景下的目標(biāo)跟蹤問題中,仿真結(jié)果表明該算法的可行性和優(yōu)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.
【作者單位】： 海軍航空工程學(xué)院;92941部隊;
【分類號】：TN713;TN953
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本文編號：2528606