Electronics and Electrical Engineering and Control

Dynamic topology optimization of navigation satellite inter-satellite links network based on improved genetic algorithm

  • HAN Kai ,
  • DONG Richang ,
  • SHAO Fengwei ,
  • GONG Wenbin ,
  • CHANG Jiachao
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  • 1. University of Chinese Academy of Sciences, Beijing 100049, China;
    2. Innovation Academy for Microsatellites of Chinese Academy of Sciences, Shanghai 201210, China

Received date: 2021-07-13

  Revised date: 2021-08-06

  Online published: 2021-09-06

Supported by

Shanghai "Post-Qi-Ming-Xing Plan" (18QA1404000);Shanghai Scientific Research Projects (18DZ1112001)

Abstract

Due to the limitation of the satellite platform, the number of Ka-band Inter-Satellite Links (ISLs) antennas is usually less than that of visible satellites. A topology processing mechanism is proposed based on Finite State Automata (FSA) to link topology optimization with inter-satellite link constraints. Considering the inter-satellite visibility, number of links, and other constraints, a link optimization model is proposed to minimize the maximum Position Dilution of Precision (PDOP) of ranging performance. To solve the problem that the gene mutation mechanism and chromosome crossover mechanism of the traditional genetic algorithm cannot meet the constraints of the optimization model and thus lead to a large number of link conflicts, the Single Point and Traceable Variation (SPTV) mechanism and the chromosome crossover mechanism including Time Slots Crossover (TSX) and Position Self-Crossover (PSX) based on the "hybridization+self-crossover" are proposed. The simulation results show that TSX-PSX mechanism reduces the maximum PDOP by 27.28% compared with TSX mechanism and avoids the conflict problem, verifying the effectiveness of the improved genetic algorithm for link topology optimization.

Cite this article

HAN Kai , DONG Richang , SHAO Fengwei , GONG Wenbin , CHANG Jiachao . Dynamic topology optimization of navigation satellite inter-satellite links network based on improved genetic algorithm[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022 , 43(9) : 326095 -326095 . DOI: 10.7527/S1000-6893.2021.26095

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