幅度及多普勒信息辅助的多目标跟踪算法  

Multi-target tracking algorithm based on amplitude and Doppler information

作　　者：彭华甫[1,2] 黄高明 田威[1] 邱昊 PENG Huafu;HUANG Gaoming;TIAN Wei;QIU Hao(College of Electronic Engineering,Naval University of Engineering,Wuhan 430033,China;Unit 92773 of PLA,Wenzhou 325807,China)

机构地区：[1]海军工程大学电子工程学院 [2]中国人民解放军92773部队

出　　处：《航空学报》2018年第10期229-236,共8页Acta Aeronautica et Astronautica Sinica

基　　金：中国博士后科学基金(2017M613370)~~

摘　　要：针对现有的多目标跟踪(MTT)算法在强杂波环境下会出现严重的性能衰退,利用目标的幅度及多普勒特征,基于随机有限集(RFS)理论,提出了一种幅度及多普勒信息辅助的δ广义标签多伯努利(ADI-δ-GLMB)滤波器。首先,利用幅度及多普勒信息对目标状态进行扩展,在此基础上建立了新的量测似然函数。然后,基于δ-GLMB滤波器框架推导了新的更新方程。最后,进行仿真验证,结果表明:强杂波下,ADI-δ-GLMB滤波器跟踪性能明显优于δ-GLMB滤波器,估计精度及稳定性更高,且计算量更低;同信息辅助的概率假设密度(PHD)、多目标多伯努利(MeMBer)滤波器相比,ADI-δ-GLMB滤波器状态估计精度更高。To address the severe performance degradation of the existing Multi-Target Tracking（MTT）in high clutter environment,a novel Amplitude and Doppler Information assistedδ-Generalized Labeled Multi-Bernoulli（ADI-δ-GLMB）filter is proposed based on the theory of Random Finite Set（RFS）.Firstly,the amplitude and Doppler information isintroduced to expand the target state,and a new function of measurement likelihood is established on this basis.Then,a new update equation is deduced based on the framework of theδ-GLMB filter.Finally,the simulation results show that the tracking performance of the proposed ADI-δ-GLMB filter is significantly better than that of the standardδ-GLMB filter,displaying higher estimation accuracy and stability,and a lower computational cost in dense clutter environment.In addition,the estimation accuracy of the proposed ADI-δ-GLMB filter is higher than that of the information assisted Probability Hypothesis Density（PHD）and Multi-target Multi-Bernoulli（MeMBer）filter.

关 键 词：多目标跟踪 随机有限集 幅度信息 多普勒信息 标签多伯努利 

分 类 号：V243[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]