An analytic solution to Wahbaʼs problem

All spacecraft attitude estimation methods are based on Wahbaʼs optimization problem. This problem can be reduced to finding the largest eigenvalue and the corresponding eigenvector for Davenportʼs K-matrix. Several iterative algorithms, such as QUEST and FOMA, were proposed, aiming at reducing the...

Full description

Saved in:
Bibliographic Details
Published in:Aerospace science and technology 2013-10, Vol.30 (1), p.46-49
Main Authors: Yang, Yaguang, Zhou, Zhiqiang
Format: Article
Language:English
Subjects:
Analytical solution
Applied sciences
Attitude estimation
Exact sciences and technology
Ground, air and sea transportation, marine construction
Miscellaneous transportation
Spacecraft
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:All spacecraft attitude estimation methods are based on Wahbaʼs optimization problem. This problem can be reduced to finding the largest eigenvalue and the corresponding eigenvector for Davenportʼs K-matrix. Several iterative algorithms, such as QUEST and FOMA, were proposed, aiming at reducing the computational cost. But their computational time is unpredictable because the iteration number is not fixed and the solution is not accurate in theory. Recently, an analytical solution, ESOQ was suggested. The advantages of analytical solutions are that their computational time is fixed and the solution should be accurate in theory if there is no numerical error. In this paper, we propose a different analytical solution to Wahbaʼs problem. We use simple and easy to be verified examples to show that this method is numerically more stable than ESOQ, potentially faster than QUEST and FOMA. We also use extensive simulation test to support this claim.
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2013.07.002