ROSPAug 11, 2018

Fast RodFIter for Attitude Reconstruction from Inertial Measurements

arXiv:1808.03817v131 citations
Originality Incremental advance
AI Analysis

This is an incremental improvement for applications requiring efficient onboard attitude computation.

The paper tackles the high computational load of the RodFIter method for attitude reconstruction from gyroscope measurements by reformulating it using Chebyshev polynomial iteration with truncation, achieving significantly reduced complexity while maintaining almost the same accuracy.

Attitude computation is of vital importance for a variety of applications. Based on the functional iteration of the Rodrigues vector integration equation, the RodFIter method can be advantageously applied to analytically reconstruct the attitude from discrete gyroscope measurements over the time interval of interest. It is promising to produce ultra-accurate attitude reconstruction. However, the RodFIter method imposes high computational load and does not lend itself to onboard implementation. In this paper, a fast approach to significantly reduce RodFIter's computation complexity is presented while maintaining almost the same accuracy of attitude reconstruction. It reformulates the Rodrigues vector iterative integration in terms of the Chebyshev polynomial iteration. Due to the excellent property of Chebyshev polynomials, the fast RodFIter is achieved by means of appropriate truncation of Chebyshev polynomials, with provably guaranteed convergence. Moreover, simulation results validate the speed and accuracy of the proposed method.

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