Conservative Estimation of Inertial Sensor Errors using Allan Variance Data

Kyle Lethander and Clark Taylor

Abstract: To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952- 2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in an inertial sensor. Recent work has sought to overcome the graphical nature and visualinspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but also conservative, i.e., that the estimated noise parameters overbound truth. In this paper, we propose a novel method for automatically estimating conservative noise parameters using Allan variance.
Published in: Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021)
September 20 - 24, 2021
Union Station Hotel
St. Louis, Missouri
Pages: 2556 - 2564
Cite this article: Lethander, Kyle, Taylor, Clark, "Conservative Estimation of Inertial Sensor Errors using Allan Variance Data," Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021), St. Louis, Missouri, September 2021, pp. 2556-2564.
https://doi.org/10.33012/2021.17921
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