Tracking evasive objects via a search allocation game

Abstract

This paper outlines a strategy for tracking evasive objects in discrete space using game theory to allocate sensor resources. One or more searchers have to allocate the effort among the discrete cells to maximize the object detection probability within a finite time horizon or minimize the expected search time to achieve the desired detection probability under a false alarm constraint. We review the standard formulations under a sequential decision setting for finding stationary objects. Then we consider both robust and optimal search strategies and extend the standard search problem to a two-person zero-sum search allocation game where the object wants to hide from the searcher and the object has incomplete information about the searcher's remaining search time. We discuss how the results affect the sensor management and mission planning for cooperative unmanned aerial vehicle (UAV) search tasks and provide simulation examples to show the effectiveness of the proposed method compared with random search strategy.