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A robust astro-inertial integrated navigation algorithm based on star-coordinate matching

delete2017-12-01
delete7
PRE
AI
R
Rong Wang
熊
熊芝 (Zhi Xiong) *
J
Jianye Liu
L
Lijuan Shi
DOI：10.1016/j.ast.2017.09.013delete
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Abstract

Abstract

En 中文
The astro-inertial integrated navigation system has the characteristic of anti-electromagnetic interference but suffers from aero-optical starlight perturbation when applied to hypersonic cruise vehicles (HCVs). Because there is no strategy in the traditional loosely coupled astro-inertial integration framework for recognising and evaluating skew in star observation, this system cannot adapt to perturbations, and the navigation accuracy tends to degrade. In this study, a strongly coupled framework for an astro-inertial integrated system is designed, and a robust astro-inertial fusion algorithm based on star-coordinate matching is proposed; the skew degree of each observed star is quantified by matching with the virtual star image re-established from INS measurements. Based on star-coordinate matching, a robust weight tuning rule is designed according to the maximum-likelihood estimation theory, including a method to determine the star-coordinate confidence scope by statistically analysing the astronomical-observation perturbation rate. Compared with the traditional loosely coupled astro-inertial integration framework, the proposed strongly coupled framework and robust astro-inertial integrated navigation algorithm based on star-coordinate matching can significantly improve robustness against perturbations. (C) 2017 Elsevier Masson SAS. All rights reserved.
Keywords:
Integrated navigation
Robust fusion
Strongly coupled astro-inertial integration framework
Star-coordinate matching
Perturbation-rate statistics
Maximum-likelihood estimation
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Aerospace Science and Technology cover
Aerospace Science and Technology
IF:
5.8
Papers:
1.0W
Citations:
3.0W

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No organization information available
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