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Asymptotically optimal attitude and rate bias estimation with guaranteed convergence

  • General Dynamics Integrated Space Systems
  • NASA Goddard Space Flight Center

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A recent advance in attitude filtering has been the formulation of a simple, asymptotically optimal attitude estimation algorithm with guaranteed convergence from almost any initial condition. The robust convergence of the algorithm relies on creating a linear measurement model from unit vector observations, and consistently mapping the 3 × 3 covariance estimate from one estimated quaternion tangent space to the next. This paper extends the algorithm to estimate both attitude and rate sensor bias.

Original languageEnglish
Title of host publicationThe F. Landis Markley Astronautics Symposium - Advances in the Astronautical Sciences
Subtitle of host publicationProceedings of the American Astronautical Society F. Landis Markley Astronautics Symposium
Pages465-475
Number of pages11
StatePublished - 2008
EventAmerican Astronautical Society F. Landis Markley Astronautics Symposium - Cambridge, MD, United States
Duration: Jun 29 2008Jul 2 2008

Publication series

NameAdvances in the Astronautical Sciences
Volume132
ISSN (Print)0065-3438

Conference

ConferenceAmerican Astronautical Society F. Landis Markley Astronautics Symposium
Country/TerritoryUnited States
CityCambridge, MD
Period06/29/0807/2/08

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