| Citation: | QIAO Chenglin, DUAN Xiusheng, SHAN Ganlinet al. Scheduling algorithm for multi-sensor collaboration tracking and radiation control[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(7): 1472-1480. doi: 10.13700/j.bh.1001-5965.2017.0555(in Chinese)
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Active sensors obtain the target continuous measurements that can be intercepted by enemy system. To reduce the interception risk, a scheduling algorithm for multi-sensor collaboration tracking and radiation control is proposed. Firstly, the sensor radiation is represented by the emission level impact (ELI) and the processes of target tracking and radiation control are formulated as a partially observable Markov decision process (POMDP). Secondly, the hidden Markov model (HMM) filter is utilized to update the sensor radiation state and derive the non-myopic radiation risk. Meanwhile, the target state is updated by the unscented Kalman filter (UKF) which is also used to evaluate the target tracking accuracy. Finally, considering the tracking task requirement, the non-myopic scheduling model of radiation control is set up with tracking accuracy constraint and the scheduling problem is translated to a decision tree optimization problem. Then, the suboptimal lower bound of each decision tree node is given and the optimal scheduling sequence is obtained by improved branch and bound (IB & B) technique. Simulation results prove the validity of the proposed algorithm.
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