Radar and communication integrated unmanned aerial vehicle cooperative multi-target detection method

Abstract

The invention provides a radar communication integrated unmanned aerial vehicle cooperative multi-target detection method, and the method comprises the steps: carrying out the cooperative detection through employing a plurality of unmanned aerial vehicles to carry out the radar communication integrated equipment, setting each unmanned aerial vehicle as an intelligent agent, and training a stable detection strategy, and a trained strategy is used to control flight tracks of a plurality of unmanned aerial vehicles and resource allocation between the radar and communication, and finally a given detection task is rapidly completed. Radar, communication and unmanned aerial vehicle flight states observed by each agent are used as input of the strategy generation module, the state and action observed by each agent are mapped into a random strategy by using a deep neural network, and the strategy of each agent is evaluated by using the strategy evaluation module. And a better cooperation strategy is obtained through module training. According to the invention, through efficient planning of resources of radars, communication and the like on multiple unmanned aerial vehicles, multiple targets in a designated area are searched, and the multi-target searching and finding efficiency is greatly improved.

Description

technical field [0001] The invention belongs to the field of radar communication integration and cluster cooperative detection, and in particular relates to an unmanned aerial vehicle cooperative multi-target detection method integrated with radar communication. Background technique [0002] / The same detection work only considers the resource allocation in the static environment, and no work considers the trajectory design of the UAV, and the trajectory design of the UAV is an important step to exert maneuverability and flexibility. For example, Fei Zesong, Liu Peng and Wang Xinyi designed a power control-based static radar communication integration UAV network utility optimization method; Chen Peng, Wang Min and Yang Zihan invented a UAV cluster static radar communication integration under reinforcement learning method of resource allocation. 3) UAVs often need time-varying channels and limited observation information when allocating radar communication resources in a dy...

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Problems solved by technology

3) UAVs often have time-varying channels and limited observation information when allocating radar communication resources in a dynamic environment, and traditional optimization methods are difficult to solve such problems

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