基于概率假设密度滤波与无迹Kalman滤波的多目标跟踪与识别

doi:10.3969/j.issn.1000-1093.2020.08.004

摘要/Abstract

摘要： 为提高导引头末制导阶段抗干扰能力，针对典型的欺骗式距离-速度联合拖引干扰模型，研究了基于概率假设密度（PHD）滤波的多目标跟踪与基于无迹Kalman滤波（UKF）的多目标识别技术。为说明导引头目标识别原理，给出了距离-速度联合拖引干扰模型；根据导引头测量原理，通过导引头框架角、导弹-目标相对距离、径向速度建立系统跟踪模型，给出了基于PHD滤波的多目标跟踪与基于UKF的多目标识别的基本原理；基于典型的目标运动模型（匀速直线与匀速转弯模型），针对目标施加的4次距离-速度联合拖引干扰，采用目标跟踪结果以及估计的目标速度和加速度信息进行多目标跟踪与识别分析，能够很快实现真假目标识别。仿真实验结果表明，利用PHD滤波与UKF信息能够有效实现对距离-速度拖引干扰下的多目标跟踪与识别。

关键词: 导引头, 航迹滤波, 目标跟踪, 目标识别, 抗干扰, 概率假设密度滤波, 无迹Kalman滤波

Abstract: For the typical range-velocity simultaneous pull-off jamming model, the multi-target tracking technology based on probability hypothesis density (PHD) filter and the multi-target recognition technology based on unscented Kalman filter (UKF) are studied to improve the anti-jamming capability of seeker in terminal guidance phase. A range-velocity simultaneous pull-off jamming model is established to explain the principle of target recognition. According to the principle of seeker measurement, a system tracking model is established， in which the frame angle of seeker, missile-target relative distance, radial velocity, elevatiom angle and azimuth angle are considered. The basic principle of multi-target tracking based on PHD filter and multi-target recognition based on UKF filter is presented. Finally, in the typical target motion model (uniform rectilinear and uniform turning model), the target velocity and acceleration information estimated by filtering can be used to identify real and false targets quickly in view of the four target range-velocity simultaneous pull-off jammings. The simulated results show that the PHD and UKF filters presented in this paper can effectively realize the multi-target recognition and tracking under range-velocity simultaneous pull-off jamming, and verify the feasibility and effectiveness of the proposed algorithm.

Key words: seeker, trackfiltering, targettracking, targetrecognition, anti-jamming, probabilityhypothesisdensityfilter, unscentedKalmanfilter

中图分类号:

TJ765.3⁺31

邹汝平，刘建书. 基于概率假设密度滤波与无迹Kalman滤波的多目标跟踪与识别[J]. 兵工学报, 2020, 41(8): 1502-1508.

ZOU Ruping， LIU Jianshu. Multi-target Tracking and Recognition Technology Based on PHD and UKF[J]. Acta Armamentarii, 2020, 41(8): 1502-1508.

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