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Author Li, Wenling ♦ Jia, Yingmin ♦ Meng, Deyuan ♦ Du, Junping
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2015
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Other branches of engineering
Subject Keyword Target tracking ♦ Probability density function ♦ Covariance matrices ♦ Density functional theory ♦ Bayes methods ♦ Sensor fusion ♦ Random matrix ♦ Extended target tracking ♦ Distributed estimation ♦ Kullback-Leibler divergence
Abstract This paper studies the problem of extended target tracking using multiple sensors in a distributed manner. The approach of using a random matrix for the target extension is used. The weighted Kullback-Leibler divergence is applied to fuse sensor-based estimates via exchanging information among neighboring sensors. It is shown that closed form solutions can be derived to fuse sensor-based estimates of the target state and the extension matrix, respectively. In particular, the resulting solutions coincide with the same recursive form for the posterior density functions of the target state and the extension matrix. A numerical example is provided to verify the effectiveness of the proposed filter.
Description Author affiliation: Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, School of Computer Science and Technology, Beijing University of Posts and Telecommunications, 100876, China (Du, Junping) || Seventh Research Division, Beihang University (BUAA), Beijing 100191, China (Li, Wenling; Jia, Yingmin; Meng, Deyuan)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2015-12-15
Publisher Place Japan
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479978861
Size (in Bytes) 268.35 kB
Page Count 6
Starting Page 3044
Ending Page 3049

Source: IEEE Xplore Digital Library