Cognitive radar often needs to deal with diverse task requirements in practical applications.Traditional radar systems are often designed and optimized for a single task.However,radar applications in real-world scenarios often need to meet the needs of multiple tasks at the same time.In this paper,a multi-task radar waveform design method is proposed,which can use multiple optimization criteria to design the transmitted waveform according to the prior knowledge of the environment.At the same time,a covariance matrix adaptive evolutionary strategy algorithm based on meta-knowledge transfer(MKT)is introduced to solve multiple radar tasks under limited radar resources by using a more general MKT method.This method improves the efficiency of each radar task by transferring the meta-knowledge generated during the radar task solving process.The simulation experiments verify the feasibility of the proposed algo-rithm for solving the transmitted waveform of multi-task radar.Compared with using evolutionary algorithms to solve a single radar task separately,the algorithm avoids the need to learn the optimization strategy from scratch for each task,saves a lot of computing resources and time,and speeds up the solution of the optimal transmission waveform.
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