Satellite imaging planning method based on improved cuckoo search

doi:10.7523/j.ucas.2021.0014

Abstract

Abstract: This paper proposes a satellite mission planning method of multi-satellite regional targets based on improved cuckoo search(ICS) in order to maximize the use of satellite resources. Firstly, the regional target is decomposed into strips based on a single satellite transit activity. Secondly, the satellite attitude constraints, sensor usage constraints, transit time constraints, cloud cover and illumination constraints during imaging, etc. are considered to establish a constraint satisfaction model, for which coding and updating strategies are designed. Finally, an improved cuckoo search algorithm, with nonlinear inertia weight, is used to solve the constraint satisfaction model. The results of the experiment show that compared with genetic algorithm (GA), the proposed algorithm in this paper has better convergence, higher target completion rate and stronger stability, which proves the effectiveness of the method proposed in this paper.

Key words: satellite imaging planning, constraint satisfaction model, cuckoo search

CLC Number:

TP301

LI Xiaomu, TIAN Miaomiao, MA Guangbin, LIN Youming, CHENG Bo. Satellite imaging planning method based on improved cuckoo search[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(1): 101-108.

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