Journal of Systems Engineering and Electronics ›› 2018, Vol. 29 ›› Issue (1): 74-85.doi: 10.21629/JSEE.2018.01.08

• Systems Engineering • Previous Articles     Next Articles

Using approximate dynamic programming for multi-ESM scheduling to track ground moving targets

Kaifang WAN(), Xiaoguang GAO*(), Bo LI(), Fei LI()   

  • Received:2016-10-19 Online:2018-02-26 Published:2018-02-23
  • Contact: Xiaoguang GAO E-mail:wankaifang@nwpu.edu.cn;cxg2012@nwpu.edu.cn;libo803@nwpu.edu.cn;nwpulf@mail.nwpu.edu.cn
  • About author:WAN Kaifang was born in 1987. He received his B.E. in degree detection homing and control technology from Northwestern Polytechnical University (NPU), Xi'an in 2010. He was awarded with an admission from B.E. to Ph.D. directly in 2010 and he was awarded with Ph.D degree in system engineering in 2016. And now he is an assistant researcher of the Key Laboratory of Aerospace Information Perception and Photoelectric Control, Ministry of Education, NPU. His current research interests include sensor management application, multi-agent theory, approximate dynamic programming and reinforcement learning theory. E-mail: wankaifang@nwpu.edu.cn|GAO Xiaoguang was born in 1957. She received her B.E. degree in detection homing and control technology from NPU in 1982. She completed her master degree in system engineering from NPU in 1986. She was awarded with Ph.D. degree from NPU in 1989. She is currently a professor and the head in the Key Laboratory of Aerospace Information Perception and Photoelectric Control, Ministry of Education, NPU. Her research interests are machine learning theory, Bayesian network theory, and multi-agent control application. E-mail: cxg2012@nwpu.edu.cn|LI Bo was born in 1978. He received his B.E. degree in detection homing and control technology from NPU in 2000. He obtained his master degree in system engineering from NPU in 2003. He was awarded with Ph.D. degree from NPU in 2008. He is an associate professor of NPU now. Her research interests are machine learning theory, and multi-agent control application. E-mail: libo803@nwpu.edu.cn|LI Fei was born in 1988. He received his B.E. degree in detection homing and control technology from NPU, Xi'an in 2010. He obtained his master degree in 2012 and he has been working for his Ph.D. degree in system engineering, NPU, since 2012. His current research interests include machine learning theory and deep learning theory. E-mail: nwpulf@mail.nwpu.edu.cn
  • Supported by:
    the National Natural Science Foundation of China(61573285);the National Natural Science Foundation of China(61305133);This work was supported by the National Natural Science Foundation of China (61573285; 61305133)

Abstract:

This paper researches the adaptive scheduling problem of multiple electronic support measures (multi-ESM) in a ground moving radar targets tracking application. It is a sequential decision-making problem in uncertain environment. For adaptive selection of appropriate ESMs, we generalize an approximate dynamic programming (ADP) framework to the dynamic case. We define the environment model and agent model, respectively. To handle the partially observable challenge, we apply the unsented Kalman filter (UKF) algorithm for belief state estimation. To reduce the computational burden, a simulation-based approach rollout with a redesigned base policy is proposed to approximate the long-term cumulative reward. Meanwhile, Monte Carlo sampling is combined into the rollout to estimate the expectation of the rewards. The experiments indicate that our method outperforms other strategies due to its better performance in larger-scale problems.

Key words: sensor scheduling, target tracking, approximate dynamic programming, non-myopic, rollout, belief state