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Proceedings Paper

Advances in displaying uncertain estimates of multiple targets
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Paper Abstract

Both maximum likelihood estimation as well as minimum mean optimal subpattern assignment (MMOSPA) estimation have been shown to provide meaningful estimates in instances of target identity uncertainty when the number of targets present is known. Maximum likelihood measurement to track association (2D assignment) has been widely studied and is reviewed in this paper. However, it is widely believed that approximate MMOSPA estimation can not be performed in real time except when considering a very small number of targets. This paper demonstrates the MMOSPA estimator arises as a special case of a minimum mean Wasserstein metric estimator when the number of targets is unknown. Additionally, it is shown that approximate MMOSPA estimates can be calculated in microseconds to miliseconds without extensive optimization, making MMOSPA estimation a practicable alternative to more traditional estimators.

Paper Details

Date Published: 23 May 2013
PDF: 31 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874504 (23 May 2013); doi: 10.1117/12.2015147
Show Author Affiliations
David Frederic Crouse, U.S. Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)

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