Array antenna design system and method based on deep reinforcement learning in complex environment

The invention discloses an intelligent array antenna design system and method based on deep reinforcement learning in a complex environment, relates to the technical field of radar communication, and can better solve the intelligent optimization problem of the radiation performance of an array antenna in the complex environment. The system comprises an execution module and an evaluation module. The execution module is used for simulating the radiation performance of the array antenna in an actual environment, and comprises an array antenna simulation unit and a working environment simulation unit. The evaluation module comprises an algorithm unit and a data interface, and the algorithm unit executes a phase regulation and control algorithm based on deep reinforcement learning and outputs phase distribution of corresponding array antennas. The execution module pre-processes radiation performance data of the simulated array antenna and then sends the radiation performance data to the algorithm unit through the