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An extended time horizon search technique for cooperative unmanned vehicles to locate mobile RF targets

In this paper, we present a behavior-based, distributed, cooperative search algorithm for multiple unmanned aerial vehicles (UAVs) to cooperatively find sub-optimal search patterns to detect moving radio frequency (RF) signal emitting targets. The overall goal of the search algorithm is to compute sub-optimal flight trajectories for participating UAVs to minimize the combined search cost: search coverage, time, fuel usage, and communication overhead. The focus for this paper is to extend our existing search algorithm 's ability to incorporate evaluations of flight path options beyond the immediate time horizon. The paper explores the trade-offs over the additional computation cost and the reduction of the total search time. In addition to finding a set of sub-optimal UAV search paths, the search algorithm also generates a priority list of possible, search paths. The list is then used by an individual UAV to adjust its path selection to minimize a global search cost. Collectively, the selected UAV paths produce sub-optimal search patterns for a group of UAVs. The validity of the search algorithm is demonstrated using computer simulation