Study on Cooperative Air-to-Ground Surveillance Planning and Controlling for Unmanned Aerial Vehicles

The use of unmanned aerial vehicles (UAVs) for air-to-ground mission in complex environments has increased considerably in recent years. The numerous studies on UAVs cooperative air-to-ground mission controlling have been reported, but few have considered the impact of the communication instability due to electromagnetic interference (EMI) which is common in many air-to-ground applications. Under the influence of EMI, the air-to-ground mission stages are represented as a dynamic combination of several communication-available and communication-unavailable stages. Traditional cooperative surveillance algorithms cannot handle such situations well. In this study, we presented a method which based on Voronoi diagrams to solve the impact of communication outages, and an attention mechanism ant-colony optimization (AACO) algorithm was proposed for UAV path-planning control in air-to-ground surveillance missions. The controlling strategy is adaptively updated by introducing an attention mechanism for regular instruction information, a priori information, and emergent information of the mission to satisfy the mission target. Simulation results show that the proposed algorithm achieves better search performance than traditional algorithms in scenarios which include communication-available and communication-unavailable situations.