Evolutionary search for deep-space science mission orbits

被引:3
|
作者
Gurfil, P [1 ]
Kasdin, NJ
机构
[1] Technion Israel Inst Technol, Fac Aerosp Engn, IL-32000 Haifa, Israel
[2] Princeton Univ, Princeton, NJ 08544 USA
基金
美国国家航空航天局;
关键词
D O I
10.2514/1.14109
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
We present an application of an evolutionary programming method, niching genetic algorithms, to the search for orbits in the spatial elliptic restricted three-body problem (ER3BP) that is suitable for deep-space science missions. The niching method used is deterministic crowding, which renders a global optimization while permitting for several optimal and suboptimal solutions to coexist. This novel approach yields diverse probing of the state space of the ER3BP. From the practical standpoint, the orbits found remain within a bounded distance from Earth, thus allowing high data-rate communication while ensuring safe operational environment, far from thermal perturbations and visual occultation as well as Earth's magnetic and radiation fields.
引用
收藏
页码:332 / 341
页数:10
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