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Proceedings Paper

Overview of design of experiments performance assessment of multitarget tracking algorithms
Author(s): Erik Blasch; Chun Yang; Ivan Kadar; Genshe Chen; Li Bai
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Paper Abstract

There are hosts of target tracking algorithm approaches, each valued with respect to the scenario operating conditions (e.g. sensors, targets, and environments). Due to the application complexity, no algorithm is general enough to be widely applicable, nor is a tailored algorithm able to meet variations in specific scenarios. Thus, to meet real world goals, multitarget tracking (MTT) algorithms need to undergo performance assessment for (a) bounding performance over various operating conditions, (b) managing expectations and applicability for user acceptance, and (c) understanding the constraints and supporting information for reliable and robust performance. To meet these challenges, performance assessment should strive for three goals: (1) challenge problem scenarios with a rich variety of operating conditions, (2) a standard, but robust, set of metrics for evaluation, and (3) design of experiments for sensitivity analysis over parameter variation of models, uncertainties, and measurements.

Paper Details

Date Published: 18 May 2012
PDF: 12 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 839207 (18 May 2012); doi: 10.1117/12.919031
Show Author Affiliations
Erik Blasch, AFRL/RIEA (United States)
Chun Yang, Sigtem Technology, Inc. (United States)
Ivan Kadar, Interlink Sciences Systems, Inc. (United States)
Genshe Chen, I-Fusion Technologies, Inc. (United States)
Li Bai, Temple Univ. (United States)


Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)

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