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Proceedings Paper

Multisensor-multitarget sensor management with target preference
Author(s): Adel I. El-Fallah; Mike Perloff; B. Ravichandran; Tim R. Zajic; Chad Stelzig; Ronald P. S. Mahler; Raman K. Mehra
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Paper Abstract

Multisensor-multitarget sensor management is viewed as a problem in nonlinear control theory. This paper applies newly developed theories for sensor management based on a Bayesian control-theoretic foundation. Finite-Set-Statistics (FISST) and the Bayes recursive filter for the entire multisensor-multitarget system are used with information-theoretic objective functions in the development of the sensor management algorithms. The theoretical analysis indicate that some of these objective functions lead to potentially tractable sensor management algorithms when used in conjunction with MHC (multi-hypothesis correlator)-like algorithms. We show examples of such algorithms, and present an evaluation of their performance against multisensor-multitarget scenarios. This sensor management formulation also allows for the incorporation of target preference, and experiments demonstrating the performance of sensor management with target preference will be presented.

Paper Details

Date Published: 9 August 2004
PDF: 11 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.543822
Show Author Affiliations
Adel I. El-Fallah, Scientific Systems Co., Inc. (United States)
Mike Perloff, Scientific Systems Co., Inc. (United States)
B. Ravichandran, Scientific Systems Co., Inc. (United States)
Tim R. Zajic, Lockheed Martin Tactical Defense Systems (United States)
Chad Stelzig, Lockheed Martin Tactical Defense Systems (United States)
Ronald P. S. Mahler, Lockheed Martin Tactical Defense Systems (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)


Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)

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