Aiming at the issue of multi-target tracking in a clutter environment,a non-myopic scheduling method of sensor radiation control is proposed to improve the tracking accuracy and reduce the usage cost.Based on the partially observable Markov decision process (POMDP) and random finite set (RFS),the target state model and observation model are established;according to the idea of Interception Probability,an improved radiation risk quantification method is proposed;for balancing the tracking accuracy and radiation risk effectively,an optimization function is created.The Gaussian mixture probability hypothesis density (GM-PHD) smoothing filter is used to update the multi-target state,and optimal subpattern assignment (OSPA) distance is used as the measurement index to propose the prediction method of multi-target non-myopic tracking accuracy;combined with the maximum range of target radiation warning,the prediction method of non-myopic radiation cost is proposed;and the sensor scheduling process is designed.The feasibility and effectiveness of the scheduling model and method are verified by simulation experiments.The results show that using the improved radiation risk quantification method for scheduling can further improve the utilization efficiency of sensor resources on the basis of realizing radiation control.The proposed scheduling method can ensure the accuracy of multi-target tracking,effectively reduce the radiation risk and switching times of sensors,and realize the reasonable scheduling of multi-sensor multi-target tracking in clutter environment.