Kalman Filtering for Attitude Estimation with Quaternions and Concepts from Manifold Theory.

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ID: 20324
2019
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Abstract
The problem of attitude estimation is broadly addressed using the Kalman filter formalism and unit quaternions to represent attitudes. This paper is also included in this framework, but introduces a new viewpoint from which the notions of "multiplicative update" and "covariance correction step" are conceived in a natural way. Concepts from manifold theory are used to define the moments of a distribution in a manifold. In particular, the mean and the covariance matrix of a distribution of unit quaternions are defined. Non-linear versions of the Kalman filter are developed applying these definitions. A simulation is designed to test the accuracy of the developed algorithms. The results of the simulation are analyzed and the best attitude estimator is selected according to the adopted performance metric.
Reference Key
bernalpolo2019kalmansensors Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Bernal-Polo, Pablo;Martínez-Barberá, Humberto;
Journal sensors
Year 2019
DOI
E149
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Keywords Keywords not found

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