摘要
机载预警雷达采用脉冲多普勒体制,具有良好的低空探测性能,但其存在不可忽略的多普勒盲区问题。在目标跟踪的过程中,该盲区容易造成目标航迹暂消和重起批甚至断批。针对多普勒盲区条件下的目标连续跟踪问题,提出了一种基于交互式多模型的盲区粒子滤波(Interacting Multiple Model-Blind Doppler Particle Filtering, IMM-BDPF)算法。该算法将多普勒盲区的先验信息并入到IMM-PF中,在模型集中的每个运动模型上分别完成盲区粒子滤波,再进行交互式处理,得到盲区内的目标状态估计值。仿真结果表明该算法对盲区内做机动的目标具有较高的状态估计精度,解决了多普勒盲区条件下的机动目标连续跟踪问题。
Airborne early warning radar, which adopts pulse Doppler (PD) system, has good detection performance for low altitude targets, but the problem about Doppler blind zone (DBZ) cannot be ignored. In the process of target tracking, the blind zone causes temporary disappearance, new initiation and even loss of tracks easily. To solve the problem of target tracking in DBZ, an interacting multiple model-blind Doppler particle filtering (IMM-BDPF) algorithm is proposed. In this algorithm, the prior information about DBZ is incorporated into IMM-PF, and then BDPF is performed for each motion model in a model set. After that, interacting processing is performed, and the estimated value of target state in DBZ can be acquired. Simulation results show that the algorithm has high state estimation accuracy for maneuvering targets in DBZ, which accordingly solves the problem of continuous maneuvering target tracking on the condition of DBZ.
作者
韩伟
何成伟
朱沛
HAN Wei;HE Chengwei;ZHU Pei(Air Force Early Warning Academy, Wuhan 430019))
出处
《火控雷达技术》
2019年第2期9-15,共7页
Fire Control Radar Technology
关键词
多普勒盲区
交互式多模型
粒子滤波
目标连续跟踪
Doppler blind zone
interacting multiple-model
particle filtering
continuous target tracking
