Based on the manned aerial vehicle(MAV)/unmanned aerial vehicle(UAV)intelligent cooperation platform,the search of multiple interfered signal sources with unknown locations and trajectory planning were studied.Considering the real-time and dynamic nature of the search process,a MAV/UAV intelligent collaborative target search and trajectory planning(MUICTSTP)algorithm based on multi-agent deep reinforcement learning(MADRL)was proposed.Each UAV made online decision on trajectory planning by sensing the received interference signal strength(RISS)values,and then transmitted the sensing information and decision-making actions to the MAV to obtain the global evaluation.The simula-tion results show that the proposed algorithm exhibits better performance in long-term RISS,collision,and other aspects compared to other algorithms,and the learning strategy is better.
维普
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