Tracking Rectangular and Elliptical Extended Targets Using Laser Measurements
2011 (English)In: Proceedings of the 14th International Conference on Information Fusion, 2011, 592-599 p.Conference paper (Refereed)
This paper considers tracking of extended targets using data from laser range sensors. Two types of extended target shapes are considered, rectangular and elliptical, and a method to compute predicted measurements and corresponding innovation covariances is suggested. The proposed method can easily be integrated into any tracking framework that relies on the use of an extended Kalman filter. Here, it is used together with a recently proposed Gaussian mixture probability hypothesis density (GM-PHD) filter for extended target tracking, which enables estimation of not only position, orientation, and size of the extended targets, but also estimation of extended target type (i.e. rectangular or elliptical). In both simulations and experiments using laser data, the versatility of the proposed tracking framework is shown. In addition, a simple measure to evaluate the extended target tracking results is suggested.
Place, publisher, year, edition, pages
2011. 592-599 p.
Multiple target tracking, Extended targets, Probability hypothesis density, PHD, Gaussian mixture, Kalman filter, Laser range data, Rectangle, Ellipse, Intersection over union
IdentifiersURN: urn:nbn:se:liu:diva-70031ISBN: 978-1-4577-0267-9OAI: oai:DiVA.org:liu-70031DiVA: diva2:434601
14th International Conference on Information Fusion, Chicago, IL, USA, 5-8 July, 2011
FunderSwedish Research Council
©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Karl Granström, Christian Lundquist and Umut Orguner, Tracking Rectangular and Elliptical Extended Targets Using Laser Measurements, 2011, Proceedings of the 14th International Conference on Information Fusion, 592-599.2011-08-232011-08-152014-03-27Bibliographically approved