A PHD Filter for Tracking Multiple Extended Targets using Random Matrices
2012 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, no 11, 5657-5671 p.Article in journal (Refereed) Published
This paper presents a random set based approach to tracking of an unknown number of extended targets, in the presence of clutter measurements and missed detections, where the targets extensions are modeled as random matrices. For this purpose, the random matrix framework developed recently by Koch et al. is adapted into the extended target PHD framework, resulting in the Gaussian inverse Wishart PHD (GIW-PHD) filter. A suitable multiple target likelihood is derived, and the main filter recursion is presented along with the necessary assumptions and approximations. The particularly challenging case of close extended targets is addressed with practical measurement clustering algorithms. The capabilities and limitations of the resulting extended target tracking framework are illustrated both in simulations and in experiments based on laser scans.
Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2012. Vol. 60, no 11, 5657-5671 p.
Gaussian distribution, PHD filter, Target tracking, Extended target, Inverse Wishart distribution, Laser sensor, Occlusion, Probability of detection, Random matrix, Random set
Signal Processing Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-82000DOI: 10.1109/TSP.2012.2212888ISI: 000310139900004OAI: oai:DiVA.org:liu-82000DiVA: diva2:557424
FunderSwedish Research Council, 621-2010-4301Swedish Foundation for Strategic Research
funding agencies|Swedish Research Council|621-2010-4301|Foundation for Strategic Research (SSF)||2012-10-012012-09-272014-03-27Bibliographically approved