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https://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 |
DOI: | 10.1109/TAES.2015.130550 |
Published version: | http://dx.doi.org/10.1109/taes.2015.130550 |
Appears in Collections: | Aurora harvest 7 Electrical and Electronic Engineering publications |
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