The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Satellite Constellation Design with Adaptively Continuous Ant System Algorithm
Open accessAbstract
The ant system algorithm (ASA) has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methods.
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Citations
Cites
Ant colony system: a cooperative learning approach to the traveling salesman problem
Dorigo, M., & Gambardella, L. M. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585892 · Cited by 8,081
Research works printed but not linked: 6
- Hanson, 1992, Designing good partial coverage satellite constellations, Journal of the Astronautical Sciences, 40, 215
- Wang, 2003, Distributed genetic algorithm used in optimization of regional coverage satellite constellations, Chinese Space Science and Technology, 2, 38
- Zhang J, Deng F Y, He X S, et al. Designing LEO retrograde orbit satellite constellation for regional coverage. 22nd AIAA International Communications Satellite Systems Conference and Exhibit, California: AIAA, 2004: 3159–3165. · DOI
- de A Silva R M, Ramalho G L. Ant system for the set covering problem. Proceedings of the 2001 IEEE International Conference on System, Man, and Cybernetics. Tucson, USA: IEEE, 2001: 3129–3133. · DOI
- Gao, 2003, Research on ant colony algorithm for continuous optimization problem, Microcomputer Development, 13, 21
- Ye, 2005, Algorithm for low altitude penetration aircraft path planning with improved ant colony algorithm, Chinese Journal of Aeronautics, 18, 304, 10.1016/S1000-9361(11)60249-5 · DOI
Cited by
Design of Regional Coverage Low Earth Orbit (LEO) Constellation with Optimal Inclination
Shin, J., Park, S.-Y., Son, J., & Song, S.-C. (2021) · Journal of Astronomy and Space Sciences · doi:10.5140/jass.2021.38.4.217 · Cited by 13
Metadata
- Authors
- He, Q., & Han, C.
- Affiliations
- Beihang University (CN)
- Corresponding author
- He, Quan
- ORCID
- Han, Chao
- Venue
- Chinese Journal of Aeronautics
- Publisher
- Elsevier BV
- Published
- 2007-08
- Volume
- 20
- Issue
- 4
- Pages
- 297-303
- ISSN
- 1000-9361 (ISSN-L)
- OpenAlex
- W1998899623
- Cited by
- 23
- References
- 1
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 4 · 2020: 1 · 2019: 2 · 2017: 1 · 2016: 1 · 2015: 2 · 2014: 4 · 2013: 1 · 2012: 2
- FWCI
- 0.37
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Chinese Journal of Aeronautics (publishedVersion, cc-by-nc-nd)
- Chinese Journal of Aeronautics
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
- Physical Sciences › Engineering › Aerospace Engineering › Satellite Communication Systems
- Physical Sciences › Engineering › Aerospace Engineering › Spacecraft Dynamics and Control
- Keywords
- constellation design, ant system algorithm, Earth coverage, coverage rate, metaheuristic optimization, convergence rate
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- He, Q., & Han, C. (2007). Satellite Constellation Design with Adaptively Continuous Ant System Algorithm. Chinese Journal of Aeronautics. https://doi.org/10.1016/s1000-9361(07)60047-8
