To make an optimal trade-off between the tracking accuracy and the radiation risk in a period of time
this paper studies the scheduling problem of selecting the active/passive sensors in the multi-platform for target tracking.The problem is formulated as a partially observable Markov decision process (POMDP)
which can take both target tracking and emission control into account.Based on the foresight optimization
the approximate accuracy reward and the radiation cost
which are derived from the unscented transformation sampling and hidden Markov model (HMM) filter respectively
transform our problem into a tree search problem
and the branch and bound method is used for problem solution.The simulation results demonstrate the effectiveness of our approach.