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Proceedings Paper

Comparison of information theoretic divergences for sensor management
Author(s): Chun Yang; Ivan Kadar; Erik Blasch; Michael Bakich
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Paper Abstract

In this paper, we compare the information-theoretic metrics of the Kullback-Leibler (K-L) and Renyi (α) divergence formulations for sensor management. Information-theoretic metrics have been well suited for sensor management as they afford comparisons between distributions resulting from different types of sensors under different actions. The difference in distributions can also be measured as entropy formulations to discern the communication channel capacity (i.e., Shannon limit). In this paper, we formulate a sensor management scenario for target tracking and compare various metrics for performance evaluation as a function of the design parameter (α) so as to determine which measures might be appropriate for sensor management given the dynamics of the scenario and design parameter.

Paper Details

Date Published: 5 May 2011
PDF: 10 pages
Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 80500C (5 May 2011); doi: 10.1117/12.883745
Show Author Affiliations
Chun Yang, Sigtem Technology, Inc. (United States)
Ivan Kadar, Interlink Systems Sciences, Inc. (United States)
Erik Blasch, Air Force Research Lab./RYAAX (United States)
Michael Bakich, Air Force Research Lab./RYAAX (United States)


Published in SPIE Proceedings Vol. 8050:
Signal Processing, Sensor Fusion, and Target Recognition XX
Ivan Kadar, Editor(s)

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