Multisensor-multitarget sensor management using geometric objective functions

Multisensor-multitarget sensor management is at root a problem in nonlinear control theory. We apply 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 indicates that some of these objective functions are geometric, and lead to potentially tractable sensor management algorithms when used in conjunction with MHC (multihypothesis correlator)-like algorithms. We show examples of such algorithms, and present a preliminary evaluation of their performance against simulated scenarios.