摘要
针对分布式目标跟踪过程中出现数据丢包和不完全量测现象,提出一种分布式目标跟踪算法。该算法由统计意义下局部滤波器和基于协方差交叉算法融合滤波器构成,其中局部滤波器利用邻域内各节点测量信息计算局部滤波值,融合滤波器则将邻域内各节点局部滤波值进行融合处理,得到该节点的目标坐标信息;最后,利用典型目标航迹模型对该算法进行仿真分析。仿真结果表明:该算法可有效抑制不完全信息发生时对目标跟踪结果的不利影响,可为分布式目标跟踪系统在实际工程中的设计与研制提供有益的参考。
A distributed target tracking algorithm is proposed for the data packet dropouts and missing measurement indistributed target tracking process.The algorithm is composed of a local filter under statistics and a fusion filter based oncovariance crossover algorithm.At first,the local filter used neighborhood node to measure information and calculate localfilter value,adopted fusion filter to carry out fusion processing of neighborhood node local filter value,and acquired nodetarget coordinate information.At last,use typical target tracking model to carry out simulation analysis for the algorithm.Thesimulation model showed that,the method can effectively restrain the bad influence of incomplete information on targettracking result.It can provide reference for design and research of distributed target tracking system in practical engineering.
作者
楚天鹏
Chu Tianpeng(School of Automation, Nanjing University of Science & Technology, Nanjing 210094, China)
出处
《兵工自动化》
2017年第9期39-44,共6页
Ordnance Industry Automation
关键词
不完全量测
数据丢包
分布式目标跟踪
missing measurements
data packet dropouts
distributed target tracking
