An anytime branch and bound algorithm for agile earth observation satellite onboard scheduling. Issue 9 (1st November 2017)

• Record Type: Journal Article
• Authors: Chu, Xiaogeng; Chen, Yuning; Tan, Yuejin
• Is Part Of: Advances in space research. Volume 60:Issue 9(2017)
• Page Start: 2077
• Page End: 2090
• Publication Date: 2017-11-01
• Subjects: Targets recognition over sea -- Agile satellite onboard scheduling problem -- Anytime branch and bound algorithm; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2017.07.026
• Languages: English
• ISSNs: 0273-1177

Abstract

Highlights: We consider a bi-satellite cluster for targets recognition over sea. We propose a mathematical model for the agile satellite scheduling problem. We develop an anytime branch and bound (AB&B) algorithm for problem solution. AB&B helps the cluster improve the efficiency of targets recognition over sea. Abstract: To fulfill the mission of targets recognition over sea, a bi-satellite cluster composed of an autonomous low resolution satellite (LRS) leading the formation for targets detection and a trailing agile high resolution satellite (HRS) for targets recognition is considered. This paper focuses on the development of a method that is able to generate a schedule plan onboard the HRS taking into account the information received from the LRS, which amounts to solving an agile earth observation satellite (AEOS) scheduling problem. The main contributions of this paper are two folds: a mathematical model for formulating the AEOS scheduling problem, and an anytime branch and bound algorithm for problem solution. Experimental results on a set of representative scenarios show that the proposed algorithm is effective which promotes significantly the bi-satellite cluster to improve the efficiency of targets recognition over sea as opposed to traditional methods where a large number of satellites are required to work coordinately. In particular, in a scenario over a 500 km × 2000 km sea area involving 25 targets, the performance of the bi-satellite cluster amounts to the coordination of 30 high resolution satellites.