DARPA Integrated Sensing and Processing (ISP) Program. Approximation Methods for Markov Decision Problems in Sensor Management
Final rept. 1 Jul 2002-30 Jun 2006
BAE SYSTEMS BURLINGTON MA
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This work addresses problems of sensor resource management SRM in which one or more sensors obtain measurements of the state of one or more targets. For example, an airborne radar may be attempting to track several ground targets, which are sometimes stationary requiring a synthetic aperture radar mode and sometimes moving requiring a ground moving target indication radar mode. The challenge is to schedule the radar modes as the scenario evolves. Such problems can generally be formulated as partially observable Markov decision processes POMDPs, which can express essential characteristics of the SRM problem such as uncertainty and dynamics. This work emphasizes a farsighted approach the highest long-term payoff may not be generated by the action providing the highest immediate payoff. Accomplishments of this effort include the establishment of a boundary on optimal SRM performance, analysis of farsighted SRM strategies for controlling a multimode sensor, and the derivation of a novel set of sufficient conditions for optimality in Markov decision processes.
- Statistics and Probability
- Active and Passive Radar Detection and Equipment
- Target Direction, Range and Position Finding