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A study of uncertainty analysis for formation satellite detection system in space science
Gao, Chen; Fischer, Philipp Martin; Gerndt, Andreas; Yang, Zhen; Gao, Chen (gaochen12@mails.ucas.ac.cn)
Department空间技术部
Source PublicationProceedings of the International Astronautical Congress, IAC
2017
Pages451-457
Language英语
ISSN0074-1795
ISBN9781510855373
AbstractA space science mission can be thought as a detection system of its scientific goals. Accuracy of positioning, timing and attitude adjusting, and margins of the payload specification are inevitable uncertainties in parameters which influence the achievement of a space mission goal. Accordingly, mission deviations need to be considered. In the early design phase of a space mission, space engineers are mainly interested whether the requirements of scientific goals are satisfied within specified margins. Thus, a quantitative analysis on how these uncertainties affect the goals would support evaluation and optimization of the mission. As an example, this paper addresses satellite formation missions which play a more and more important role in space science. Such missions provide a unique advantage in detecting high dimensional physical phenomena like the magnetic reconnection in the geo-magnetosphere while single satellites cannot. Merely satellite formation missions can distinguish spatial and temporal variations which are highly coupled parameters. However, this requires differential analysis which is hard to solve. Instead, stochastic-based simulations like the Monte Carlo method are applied where parameter uncertainties are expressed as a distribution formular. The parameter values are randomly generated by these distributions. Then, the simulations are performed multiple times. A massive number of results allows figuring out how the detection system is affected by these uncertainties. But, the resampling process of the Monte Carlo method is complex and time consuming. In this paper, the Weighted Regress Analysis (WRA) method is introduced to speed-up the computation. It approximates the detection system function by a linear function solving a series of coefficients from a set of Monte Carlo results. The drawback of this approach is that the estimation of uncertainties is less precise. To evaluate the availability and accuracy of both methods, we discuss our comparison results in this paper based on a simplified formation detection model. © International Astronautical Federation IAF. All rights reserved.
Conference Name68th International Astronautical Congress: Unlocking Imagination, Fostering Innovation and Strengthening Security, IAC 2017
Conference DateSeptember 25, 2017 - September 29, 2017
Conference PlaceAdelaide, SA, Australia
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/6413
Collection空间技术部
Corresponding AuthorGao, Chen (gaochen12@mails.ucas.ac.cn)
Recommended Citation
GB/T 7714
Gao, Chen,Fischer, Philipp Martin,Gerndt, Andreas,et al. A study of uncertainty analysis for formation satellite detection system in space science[C],2017:451-457.
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