Multisensor-multitarget sensor management with target preference
Adel I. El-Fallah, M. Perloff, Bharadwaj Ravichandran, Tim R. Zajic, Chad A. Stelzig, Ronald Mahler, Raman K. Mehra · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
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.