dynamic programming algorithm for satellite orbit task merging problem

Paper number

IAC-09.B6.2.12

Author

Ms. Liu Xiaolu, China

Coauthor

Prof. Chen Yingwu, China

Coauthor

Dr. Bai Baocun, China

Coauthor

Dr. Jufang Li, National University of Defense Technology, China

Year

2009

Abstract

Remote sensing satellites are platforms equipped with imaging instruments that orbit the Earth in order to take photographs of specific areas at the request of users. To get required photographs each target is associated with a special time window and a given look angle. Due to the constraint of satellite’s field of view (fov), a satellite has to roll its camera to get target images. However, some remote sensing satellites have rigid constraints on slew activities. Take HJ1A Satellite as an example, it can slew four times at most in a single orbit. That means the satellite can image no more than four times by different look angles, which greatly limits the satellite’s capability. 
Generally, a satellite can carry out only one task in a single shot. When multiple targets located nearby, which means that the intervals between their corresponding observations are not long and differences between their best look angles are not prominent, they might be observed together in one swath by the same look angle. Accordingly, none of targets would be abandoned and opportunities would be left for other observations.   
As satellites are still scanty resources, it is necessary and effective to combine adjacent tasks into one, which can make full efficiency of satellites. Therefore, Satellite Orbit Task Merging Problem (SOTMP) is proposed. To solve this problem the paper gives out a concept of combined task. The combined task is featured by angle-dependent effects and time sequence characteristics. So SOTMP can be partitioned into multi-phase according to the satellite’s maximum slew times in the single orbit, and then for each phase an optimal combination strategy can be get based on the principle of maximizing total priority. A dynamic programming approach is developed to find global optimal solution for this problem. The combination of the tasks is dynamically carried out during scheduling, which is different from precombination. This approach includes two search processes: forward and backward search. This bi-orientation search mechanism can ensure that the solution is optimal. Finally, a computational experiment is executed to test the proposed approach and the results show its effectiveness. Compared to traditional algorithms, it can get better solutions in shorter time.

Abstract document

IAC-09.B6.2.12.pdf

Manuscript document

IAC-09.B6.2.12.pdf (🔒 authorized access only).

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