Abstract
In recent years, joint radar and communication (JRC) has gained substantial attention due to its high spectrum efficiency and equipment utilization. In this paper, we consider a JRC-enabled multi-UAV cooperative detection scenario, in which each UAV equipped with a JRC unit simultaneously performs the detection function to sense multiple targets and the communication function to transmit the detected data to a fusion center. To strike a trade-off between radar sensory and communication performance for all UAVs, we optimize the transmit power, resource allocation and navigation for each UAV to maximize their sensing scores and the geographical fairness of the targets on the condition of the quality requirements of communication and radar sensing. This problem is a mixed integer non-convex optimization that is challenging to be solved in practice. Considering the complexity of the optimization and dynamics of the UAV environment, we design a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">l</u> earning based <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</u> rajectory <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</u> lanning and <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</u> esource <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</u> llocation (LTPRA) algorithm that leverages multiple learning agents to find effective policies from experiences while guaranteeing communication and sensing performance. To improve the environmental exploration of agents, we design an incentive mechanism for their detection behavior and introduce a policy regularization method to mitigate policy overfitting in multi-agent cooperation. Numerical results reveal the convergence performance of the proposed algorithm and show the improvement on detection and communication performance in JRC-enabled multi-UAV detection systems compared with state-of-the-art approaches.
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