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dc.contributor.authorTang, X.
dc.contributor.authorChen, X.
dc.contributor.authorMcDonald, M.
dc.contributor.authorMahler, Ronald
dc.contributor.authorTharmarasa, R.
dc.contributor.authorKirubarajan, T.
dc.date.accessioned2017-08-24T02:17:50Z
dc.date.available2017-08-24T02:17:50Z
dc.date.created2017-08-23T07:21:50Z
dc.date.issued2015
dc.identifier.citationTang, X. and Chen, X. and McDonald, M. and Mahler, R. and Tharmarasa, R. and Kirubarajan, T. 2015. A Multiple-Detection Probability Hypothesis Density Filter. IEEE Transactions on Signal Processing. 63 (8): pp. 2007-2019.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/55249
dc.identifier.doi10.1109/TSP.2015.2407322
dc.description.abstract

© 1991-2012 IEEE. Most conventional target tracking algorithms assume that one target can generate at most one detection per scan. However, in many practical target tracking applications, one target may generate multiple detections in one scan, because of multipath propagation, or high sensor resolution or some other reason. If the multiple detections from the same target can be effectively utilized, the performance of the multitarget tracking system can be improved. However, the challenge is that the uncertainty in the number of targets and the measurement set-to-target association will increase the complexity of tracking algorithms. To solve this problem, the random finite set (RFS) modeling and the random finite set statistics (FISST) are used in this paper. Without any extra approximation beyond those made in the standard probability hypothesis density (PHD) filter, a general multi-detection PHD (MD-PHD) update formulation is derived. It is also established in this paper that, with certain reasonable assumptions, the proposed MD-PHD recursion can function as a generalized extended target PHD or multisensor PHD filter. Furthermore, a Gaussian Mixture (GM) implementation of the proposed MD-PHD formulation, called the MD-GM-PHD filter, is presented. The proposed MD-GM-PHD filter is demonstrated on a simulated over-the-horizon radar (OTHR) scenario.

dc.publisherIEEE
dc.titleA Multiple-Detection Probability Hypothesis Density Filter
dc.typeJournal Article
dcterms.source.volume63
dcterms.source.number8
dcterms.source.startPage2007
dcterms.source.endPage2019
dcterms.source.issn1053-587X
dcterms.source.titleIEEE Transactions on Signal Processing
curtin.departmentDepartment of Electrical and Computer Engineering
curtin.accessStatusFulltext not available


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