Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (5): 931-945.doi: 10.21629/JSEE.2019.05.11

• Systems Engineering • Previous Articles     Next Articles

Earth observation satellite scheduling for emergency tasks

Haiquan SUN1,2(), Wei XIA1,2,*(), Xiaoxuan HU1,2(), Chongyan XU3()   

  1. 1 School of Management, Hefei University of Technology, Hefei 230009, China
    2 Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei 230009, China
    3 Graduate School, Beijing Institute of Remote Sensing Information, Beijing 100192, China
  • Received:2019-03-15 Online:2019-10-08 Published:2019-10-09
  • Contact: Wei XIA E-mail:sunhaiquan2015@163.com;xiawei@hfut.edu.cn;xiaoxuanhu@hfut.edu.cn;xuchongy1970@sina.com
  • About author:SUN Haiquan was born in 1993. He received his B.S. degree from Hefei University of Technology in 2016. He is currently working for his M.S. degree in management science and engineering at Hefei University of Technology. His research interest is satellite intelligent scheduling. E-mail: sunhaiquan2015@163.com|XIA Wei was born in 1983. He received his Ph.D. degree from Hefei University of Technology in 2014. Currently he is working in Hefei University of Technology as a lecturer. His research interests include satellite intelligent scheduling and controlling. E-mail: xiawei@hfut.edu.cn|HU Xiaoxuan was born in 1978. He received his B.S. degree and Ph.D. degree from Hefei University of Technology in 1999 and 2007, respectively. He is a professor at Hefei University of Technology. His research interests include satellite scheduling and UAV planning. E-mail: xiaoxuanhu@hfut.edu.cn|XU Chongyan was born in 1970. She received her B.S. degree from Beijing Institute of Technology in 2003. Now she is working in Beijing Institute of Remote Sensing Information. Her research interest is space remote sensing satellite application. E-mail: xuchongy1970@sina.com
  • Supported by:
    the National Natural Science Foundation of China(71671059);This work was supported by the National Natural Science Foundation of China (71671059)

Abstract:

The earth observation satellites (EOSs) scheduling problem for emergency tasks often presents many challenges. For example, the scheduling calculation should be completed in seconds, the scheduled task rate is supposed to be as high as possible, the disturbance measure of the scheme should be as low as possible, which may lead to the loss of important observation opportunities and data transmission delays. Existing scheduling algorithms are not designed for these requirements. Consequently, we propose a rolling horizon strategy (RHS) based on event triggering as well as a heuristic algorithm based on direct insertion, shifting, backtracking, deletion, and reinsertion (ISBDR). In the RHS, the driven scheduling mode based on the emergency task arrival and control station time window events are designed to transform the long-term, large-scale problem into a short-term, small-scale problem, which can improve the schedulability of the original scheduling scheme and emergency response sensiti-vity. In the ISBDR algorithm, the shifting rule with breadth search capability and backtracking rule with depth search capability are established to realize the rapid adjustment of the original plan and improve the overall benefit of the plan and early completion of emergency tasks. Simultaneously, two heuristic factors, namely the emergency task urgency degree and task conflict degree, are constructed to improve the emergency task scheduling guidance and algorithm efficiency. Finally, we conduct extensive experiments by means of simulations to compare the algorithms based on ISBDR and direct insertion, shifting, deletion, and reinsertion (ISDR). The results demonstrate that the proposed algorithm can improve the timeliness of emergency tasks and scheduling performance, and decrease the disturbance measure of the scheme, therefore, it is more suitable for emergency task scheduling.

Key words: emergency task, rolling horizon, shifting rule, backtracking rule