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Association-free Tracking of Two Closely Spaced Targets

Baum, Marcus; Hanebeck, Uwe D.


This paper introduces a new concept for tracking closely spaced targets in Cartesian space based on position measurements corrupted with additive Gaussian noise. The basic idea is to select a special state representation that eliminates the target identity and avoids the explicit evaluation of association probabilities. One major advantage of this approach is that the resulting likelihood function for this special problem is unimodal. Hence, it is especially suitable for closely spaced targets. The resulting estimation problem can be tackled with a standard nonlinear estimator. In this work, we focus on two targets in two-dimensional Cartesian space. The Cartesian coordinates of the targets are represented by means of extreme values, i.e., minima and maxima. Simulation results demonstrate the feasibility of the new approach.

Volltext §
DOI: 10.5445/IR/1000035040
DOI: 10.1109/MFI.2010.5604450
Zitationen: 3
Cover der Publikation
Zugehörige Institution(en) am KIT Fakultät für Informatik – Institut für Anthropomatik (IFA)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2010
Sprache Englisch
Identifikator ISBN: 978-1-4244-5424-2
KITopen-ID: 1000035040
Erschienen in Proceedings of the 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2010), Salt Lake City, Utah, USA, 5-7 Sept. 2010
Verlag Institute of Electrical and Electronics Engineers (IEEE)
Seiten 62-67
Nachgewiesen in Dimensions
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