4.7 Article

Sequential multilayer fusion based assessment model for spacecraft launch success ratio

Journal

AEROSPACE SCIENCE AND TECHNOLOGY
Volume 48, Issue -, Pages 223-233

Publisher

ELSEVIER FRANCE-EDITIONS SCIENTIFIQUES MEDICALES ELSEVIER
DOI: 10.1016/j.ast.2015.11.005

Keywords

Launch success ratio (LSR); Assessment model; Inheritance factor; Sequential multilayer fusion

Funding

  1. Program of [National Natural Science Foundation of China] [71401136]
  2. China Postdoctoral Science Foundation [2014M5523751]

Ask authors/readers for more resources

When assessing a spacecraft's launch success ratio (LSR), it is difficult to conduct many real flight tests before an actual mission because of the high costs, so various simulations must be used to comprehensively assess the LSR. However, during such simulations, problems can occur because the test data do not necessarily come from the same population, so the simulation samples may dominate the flight test samples. To overcome these issues, this paper proposes a sequential multilayer fusion based assessment model for spacecraft LSR. This model introduces an inheritance factor and an updating factor to correct the experimental simulation information, thus ensuring that the corrected information and the flight test information approximately obey the same population, which greatly reduces the influences of the different populations on the LSR. The sequential multilayer fusion model is an effective way to efficiently use prior information to obtain an accurate estimate. A numerical example illustrates how the proposed model can solve the problem of large sample data domination over small sample data and avoid the volatility effects of small flight test samples on the estimated LSR value. (C) 2015 Elsevier Masson SAS. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available