Sigma point transformation for Gaussian mixture distributions applied to attitude estimation

Richard Linares, John L. Crassidis

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper describes the development of an approximate method for propagating uncertainty through stochastic dynamical systems using a quadrature rule integration based method. The development of quadrature rules for Gaussian mixture distributions is discussed. A numerical solution to this problem is considered that uses a Gram-Schmidt process. The new approach is applied to the attitude estimation problem. The proposed method outperforms the unscented Kalman filter for attitude estimation for scenario with large initial error.

Original languageEnglish (US)
Pages (from-to)3735-3753
Number of pages19
JournalAdvances in the Astronautical Sciences
Volume148
StatePublished - 2013
Event23rd AAS/AIAA Space Flight Mechanics Meeting, Spaceflight Mechanics 2013 - Kauai, HI, United States
Duration: Feb 10 2013Feb 14 2013

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