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**Harvard**

Svensson, D., Svensson, L., Guerriero, M., Crouse, D. och Willett, P. (2011) *The multitarget Set JPDA filter with target identity*.

** BibTeX **

@conference{

Svensson2011,

author={Svensson, Daniel and Svensson, Lennart and Guerriero, Marco and Crouse, David and Willett, Peter},

title={The multitarget Set JPDA filter with target identity},

booktitle={Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition XX. Conference on Signal Processing, Sensor Fusion, and Target Recognition XX Orlando, FL, APR 25-27, 2011},

isbn={978-0-81948-624-0 },

abstract={The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relation
between the density of a random finite set and the ordinary density of a state vector to improve on the Joint
Probabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of the Gaussian
approximations of the JPDA, which result in avoidance of track coalescence. In the original presentation of the
SJPDA filter, the focus was on problems where target identity is not relevant, and it was shown that the filter
performs better than the JPDA filter for such problems. The improved performance of the SJPDA is due to
its relaxation of the labeling constraint that hampers most tracking approaches. However, if track identity is
of interest a record of it may be kept even with a label-free approach such as the SJPDA: label-free targets are
localized via the SJPDA, and then the identities are recalled as an overlay.},

year={2011},

keywords={Target tracking, estimation, target identity, finite set statistics, JPDA, SJPDA },

}

** RefWorks **

RT Conference Proceedings

SR Print

ID 140125

A1 Svensson, Daniel

A1 Svensson, Lennart

A1 Guerriero, Marco

A1 Crouse, David

A1 Willett, Peter

T1 The multitarget Set JPDA filter with target identity

YR 2011

T2 Proceedings of SPIE: Signal Processing, Sensor Fusion, and Target Recognition XX. Conference on Signal Processing, Sensor Fusion, and Target Recognition XX Orlando, FL, APR 25-27, 2011

SN 978-0-81948-624-0

AB The Set JPDA (SJPDA) filter is a recently developed multi-target tracking filter that utilizes the relation
between the density of a random finite set and the ordinary density of a state vector to improve on the Joint
Probabilistic Data Association (JPDA) filter. One advantage to the filter is the improved accuracy of the Gaussian
approximations of the JPDA, which result in avoidance of track coalescence. In the original presentation of the
SJPDA filter, the focus was on problems where target identity is not relevant, and it was shown that the filter
performs better than the JPDA filter for such problems. The improved performance of the SJPDA is due to
its relaxation of the labeling constraint that hampers most tracking approaches. However, if track identity is
of interest a record of it may be kept even with a label-free approach such as the SJPDA: label-free targets are
localized via the SJPDA, and then the identities are recalled as an overlay.

LA eng

DO 10.1117/12.886946

OL 30