Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/97151
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Type: Journal article
Title: Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA, and association-based MeMBer
Author: Williams, J.
Citation: IEEE Transactions on Aerospace and Electronic Systems, 2015; 51(3):1664-1687
Publisher: IEEE
Issue Date: 2015
ISSN: 0018-9251
1557-9603
Statement of
Responsibility: 
Jason L. Williams
Abstract: Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and observes that data association is implicitly present, in a data structure similar to multiple hypothesis tracking (MHT). Subsequently, algorithms are obtained by approximating the distribution of associations. Two algorithms result: one nearly identical to joint integrated probabilistic data association (JIPDA), and another related to the multiple target multi-Bernoulli (MeMBer) filter. Both improve performance in challenging environments.
Rights: © 2015 IEEE
RMID: 0030039227
DOI: 10.1109/TAES.2015.130550
Appears in Collections:Electrical and Electronic Engineering publications

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