In consideration of the radiation control for target detection and tracking, a non-myopic scheduling algorithm for multi-sensor collaborative dectection and tracking is proposed. Firstly, the model of target tracking and radiation control is formulated as a partially observable Markov decision process(POMDP). Then, the probability of detecting new targets is calculated by the randomly distributed particles, the non-myopic tracking accuracy is predicted by the posterior carmér-rao lower bound (PCRLB), and the non-myopic radiation cost is derived by the hidden Markov model (HMM) filter. Finally, the non-myopic optimization function of radiation control is set up with the constraints of the new target detection probability and the existing target tracking accuracy. And the optimal scheduling sequence is obtained by the branch and bound algorithm based on greedy search. Simulation results show the effectiveness of the proposed algorithm.