A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites
Joint Authors
Dong, Yunfeng
Wei, Xiaona
Tian, Lu
Liu, Fengrui
Xu, Guangde
Source
International Journal of Aerospace Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-09
Country of Publication
Egypt
No. of Pages
15
Abstract EN
The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM), which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA.
To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM) is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components.
Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM).
In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence.
The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM.
And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.
American Psychological Association (APA)
Dong, Yunfeng& Wei, Xiaona& Tian, Lu& Liu, Fengrui& Xu, Guangde. 2017. A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites. International Journal of Aerospace Engineering،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1158143
Modern Language Association (MLA)
Dong, Yunfeng…[et al.]. A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites. International Journal of Aerospace Engineering No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1158143
American Medical Association (AMA)
Dong, Yunfeng& Wei, Xiaona& Tian, Lu& Liu, Fengrui& Xu, Guangde. A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites. International Journal of Aerospace Engineering. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1158143
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1158143