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