Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration

Roberto Molinari, James Balamuta, Stéphane Guerrier, Xinyu Zhang, Jan Skaloud

Abstract: The identification and selection of a small set of models that are able to well describe and predict the error signals coming from inertial sensors is of utmost importance to improve the navigation precision of these devices. For this reason, in this paper we describe the implementation of the WVIC model selection criterion by improving the computational efficiency of its associated algorithm. This criterion is based on the Generalized Method of Wavelet Moments that was recently proposed to estimate the parameters of inertial sensor error models. Using this approach, the model selection procedure is included within an algorithm that allows it to be executed more efficiently and is implemented within a new package in the opensource statistical platform R. The efficient implementation of this model selection procedure enables engineers and researchers to rapidly identify a restricted set of models for inertial sensor calibration.
Published in: Proceedings of the 28th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2015)
September 14 - 18, 2015
Tampa Convention Center
Tampa, Florida
Pages: 2003 - 2006
Cite this article: Molinari, Roberto, Balamuta, James, Guerrier, Stéphane, Zhang, Xinyu, Skaloud, Jan, "Automatic and Computationally Efficient Method for Model Selection in Inertial Sensor Calibration," Proceedings of the 28th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2015), Tampa, Florida, September 2015, pp. 2003-2006.
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