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Scheduling for single agile satellite, redundant targets problem using complex networks theory

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  • Wang, Xin-Wei
  • Chen, Zhen
  • Han, Chao

Abstract

Scheduling for the Earth observation satellites (EOSs) imaging mission is a complicated combinatorial optimization problem, especially for the agile EOSs (AEOSs). The increasing observation requirements and orbiting satellites have exacerbated the scheduling complexity in recent years. In this paper, the single agile satellite, redundant observation targets scheduling problem is studied. We introduce the theory of complex networks and find similarities between AEOS redundant targets scheduling problem and the node centrality ranking problem. Then we model this problem as a complex network, regarding each node as a possible observation opportunity, and define two factors, node importance factor and target importance factor, to describe the node/target importance. Based on the two factors, we propose a fast approximate scheduling algorithm (FASA) to obtain the effective scheduling results. Simulation results indicate the FASA is quite efficient and with broad suitability. Our work is helpful in the EOSs and AEOSs scheduling problems by using complex network knowledge.

Suggested Citation

  • Wang, Xin-Wei & Chen, Zhen & Han, Chao, 2016. "Scheduling for single agile satellite, redundant targets problem using complex networks theory," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 125-132.
  • Handle: RePEc:eee:chsofr:v:83:y:2016:i:c:p:125-132
    DOI: 10.1016/j.chaos.2015.12.003
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    1. Jiawei Chen & Ming Chen & Jun Wen & Lei He & Xiaolu Liu, 2022. "A Heuristic Construction Neural Network Method for the Time-Dependent Agile Earth Observation Satellite Scheduling Problem," Mathematics, MDPI, vol. 10(19), pages 1-21, September.
    2. Aaron B. Hoskins & Hugh R. Medal & Eghbal Rashidi, 2017. "Satellite constellation design for forest fire monitoring via a stochastic programing approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(8), pages 642-661, December.
    3. Ben-Loghfyry, Anouar & Charkaoui, Abderrahim, 2023. "Regularized Perona & Malik model involving Caputo time-fractional derivative with application to image denoising," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).

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