NDLI: Factor graph aided multiple hypothesis tracking

Content Provider	Springer Nature Link
Author	Wang, Huan Sun, JinPing Lu, SongTao Wei, ShaoMing
Copyright Year	2013
Abstract	Since closely moving targets exist extensively in the ground moving target tracking, the uncertainty of data association greatly increases making the measurement-to-track association more difficult. Especially, traditional multiple hypothesis tracking (MHT) has high false tracking rate and track swap. This paper first investigates the measurement based factor graph in data association, and gives the corresponding message passing algorithm. Then, a factor graph aided multiple hypothesis tracking (FGA-MHT) method is proposed, which introduces factor graph based m-best hypothesis producing technique and exploits factor graph based probability refinement algorithm to reduce the uncertainty of measurement-to-track association. Experiment results demonstrate that FGA-MHT reduces times of track swap and increases the correct data association rate in closely moving target tracking.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	56
Issue Number	10
e-ISSN	18691919
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-10-04
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	multiple hypothesis tracking (MHT) data association factor graph message passing algorithm sum-product algorithm factor graph aided multiple hypothesis tracking (FGA-MHT) Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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