Enhancing Inertial Navigation Performance via Fusion of Classical and Quantum Accelerometers

While quantum accelerometers sense with extremely low drift and low bias, their practical sensing capabilities face two limitations compared with classical accelerometers: a lower sample rate due to cold atom interrogation time, and a reduced dynamic range due to signal phase wrapping. In this paper...

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Bibliographic Details
Published in:arXiv.org 2021-03
Main Authors: Wang, Xuezhi, Kealy, Allison, Gilliam, Christopher, Haine, Simon, Close, John, Moran, Bill, Talbot, Kyle, Williams, Simon, Hardman, Kyle, Freier, Chris, Wigley, Paul, White, Angela, Szigeti, Stuart, Legge, Sam
Format: Article
Language:English
Subjects:
Accelerometers
Data integration
Inertial navigation
Interrogation
Performance enhancement
Online Access:Get full text
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Summary:While quantum accelerometers sense with extremely low drift and low bias, their practical sensing capabilities face two limitations compared with classical accelerometers: a lower sample rate due to cold atom interrogation time, and a reduced dynamic range due to signal phase wrapping. In this paper, we propose a maximum likelihood probabilistic data fusion method, under which the actual phase of the quantum accelerometer can be unwrapped by fusing it with the output of a classical accelerometer on the platform. Consequently, the proposed method enables quantum accelerometers to be applied in practical inertial navigation scenarios with enhanced performance. The recovered measurement from the quantum accelerometer is also used to re-calibrate the classical accelerometer. We demonstrate the enhanced error performance achieved by the proposed fusion method using a simulated 1D inertial navigation scenario. We conclude with a discussion on fusion error and potential solutions.
ISSN:2331-8422