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|Title:||Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA, and association-based MeMBer|
|Citation:||IEEE Transactions on Aerospace and Electronic Systems, 2015; 51(3):1664-1687|
|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|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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