A GRAPH-THEORETIC METRIC FOR DISTRIBUTED DATA FUSION IN MULTITARGET TRACKING

被引：0
作者：
MAURER, DE
OATES, KL
CHRYSOSTOMOU, AK
机构：
[1] The Applied Physics Laboratory, Johns Hopkins University, Laurel, MD 20723, Johns Hopkins Road
来源：
CONTROL ENGINEERING PRACTICE | 1994年 / 2卷 / 05期
关键词：
DISTRIBUTED CONTROL; TARGET TRACKING; KNOWLEDGE ENGINEERING; GRAPH THEORY; MONTE CARLO METHODS;
D O I：
10.1016/0967-0661(94)90350-6
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents properties of a graph-theoretic metric developed to measure the difference between two surveillance pictures in multiple target tracking. The metric is an essential component of a distributed data fusion architecture allowing geographically separated processing sites to form local surveillance pictures and, by exchanging information, derive a consistent global view. The metric is used to control communication between the sites. Information is exchanged only if the difference between a local picture and the common global picture exceeds a dissimilarity threshold.
引用
收藏
页码：865 / 873
页数：9
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