Cooperative aerial search by an innovative optimized map-sharing algorithm

Abstract

In this paper, the problem of cooperative search and tracking by multiple flying vehicles is studied. An algorithm is proposed based on optimal planning by minimizing a suitably defined cost function. In order to define the cost function, three maps are proposed: uncertainty map, detection probability map, and emitter map. In the uncertainty map, the geometrical status of the vehicle with respect to the region is considered and its suitability is measured. The detection probability map is defined such that the group of vehicles can detect new emitters that appear in their sensors’ coverage. Finally, the emitter map is a tool to keep tracking the detected emitters with acceptable error while searching the region. The assumption that the vehicles are equipped with only one commonly used radar range indicator sensor makes the proposed algorithms more applicable in the real world for a cost-effective system. The efficiency of the proposed method from the search, detection, and tracking points of view is verified through simulations.

Keywords

• cooperative search and tracking
• unmanned aerial vehicles
• emitter detection
• Bayesian theory
• map sharing
• trajectory optimization