基于有限集统计学理论的目标跟踪技术研究综述  

The FISST-Based Target Tracking Techniques:A Survey

作　　者：杨威[1] 付耀文[1] 龙建乾[1] 黎湘[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073

出　　处：《电子学报》2012年第7期1440-1448,共9页Acta Electronica Sinica

基　　金：国家自然科学基金(No.61101181)

摘　　要：有限集统计学理论为杂波背景下的目标跟踪问题提供了一种工程友好的理论工具.对近年来基于有限集统计学理论的目标跟踪技术研究现状进行了综述,包括最优多目标贝叶斯滤波器及其近似技术、参数未知与机动多目标跟踪技术、航迹生成方法、单目标联合检测与跟踪滤波器及基于有限集观测的单目标滤波器等,对相关应用亦有所介绍.最后在已有研究发展的基础上,着眼于提高目标跟踪精度和增强目标跟踪鲁棒性的发展需要,提出了基于有限集统计学理论的目标跟踪技术需重点解决和关注的若干问题,包括多目标跟踪性能评价、弱小目标跟踪、多机动目标跟踪、多传感器融合跟踪以及联合目标检测、跟踪与分类等方面.Finite Sets Statistics （FISST） provides an ＂engineering friendly＂ theoretic tool for target tracking in clutter. An overview of the studies on the FISST-based target tracking techniques is presented here. Special attention is paid to the following ar- eas：optimal multi-target Bayes filter and its principled approximations, multi-target filter under unknown parameters, multiple ma- neuvering targets tracking, track-valued estimation, Joint Target detection and Tracking Filter （JoTrF）, Bayesian filtering with ran- dom finite set observations, and also the relevant applications. Finally, based on the progress of existing research in these areas, some key issues to enhance the precision and robustness of target tracking further are introduced which deserve more attention of the re- searchers＇ for solution. These include：performance evaluation of multi-target filtering, dim/small target tracking, multiple maneuver- ing targets tracking, multi-sensor multi-target tracking, Joint target Detection, Tracking and Classification （JDTC）, and so on.

关 键 词：目标跟踪 有限集统计学理论 概率假设密度滤波器 联合目标检测、跟踪与分类 

分 类 号：TN911[电子电信—通信与信息系统]