A Multi-Target Tracking Formulation of SVSF With the Joint Probabilistic Data Association Technique

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31222

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DC Field	Value	Language
dc.contributor.author	Attari M	-
dc.contributor.author	Gadsden SA	-
dc.contributor.author	Habibi SR	-
dc.date.accessioned	2025-02-27T20:09:29Z	-
dc.date.available	2025-02-27T20:09:29Z	-
dc.date.issued	2014-10-22	-
dc.identifier.isbn	978-0-7918-4619-3	-
dc.identifier.uri	http://hdl.handle.net/11375/31222	-
dc.description.abstract	Target tracking scenarios offer an interesting challenge for state and parameter estimation techniques. This paper studies a situation with multiple targets in the presence of clutter. In this paper, the relatively new smooth variable structure filter (SVSF) is combined with the joint probability data association (JPDA) technique. This new method, referred to as the JPDA-SVSF, is applied on a simple multi-target tracking problem for a proof of concept. The results are compared with the popular Kalman filter (KF).	-
dc.publisher	ASME International	-
dc.subject	40 Engineering	-
dc.subject	4001 Aerospace Engineering	-
dc.title	A Multi-Target Tracking Formulation of SVSF With the Joint Probabilistic Data Association Technique	-
dc.type	Article	-
dc.date.updated	2025-02-27T20:09:29Z	-
dc.contributor.department	Mechanical Engineering	-
dc.identifier.doi	https://doi.org/10.1115/dscc2014-5866	-
Appears in Collections:	Mechanical Engineering Publications

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