Allan Variance (AVAR) is a method to study the underlying noises residing in a stochastic random process. Devised by David W. Allan to characterise the stability of oscillators, it has been adopted later to investigate MEMS (Micro-Electro-Mechanical Systems) stability over time. Having a good knowledge about the noises that influence a sensor helps to devise better filters and have better estimates of the physical quantities we want to measure. In this regard underwater navigation is a sensitive topic of research: in the absence of a Global Navigation Satellite System (GNSS) signal, the underwater position of an Autonomous Underwater Vehicle (AUV) is estimated through sensor fusion; but in this environment, having the necessity of a small and watertight space, electronic devices are strongly coupled with each other, worsening their overall performance. AVAR can help study these interconnections, understanding how sensors are influenced and what is their behavior in complex structures as an underwater vehicle.

Analysis and Modeling of an IMU and a FOG of an Underwater Vehicle Using Allan Variance / Liverani, Gherardo; Bucci, Alessandro; Ridolfi, Alessandro. - ELETTRONICO. - (2023), pp. 1-5. (Intervento presentato al convegno 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea) tenutosi a La Valletta, Malta nel 4-6 October 2023) [10.1109/MetroSea58055.2023.10317122].

Analysis and Modeling of an IMU and a FOG of an Underwater Vehicle Using Allan Variance

Liverani, Gherardo
;
Bucci, Alessandro;Ridolfi, Alessandro
2023

Abstract

Allan Variance (AVAR) is a method to study the underlying noises residing in a stochastic random process. Devised by David W. Allan to characterise the stability of oscillators, it has been adopted later to investigate MEMS (Micro-Electro-Mechanical Systems) stability over time. Having a good knowledge about the noises that influence a sensor helps to devise better filters and have better estimates of the physical quantities we want to measure. In this regard underwater navigation is a sensitive topic of research: in the absence of a Global Navigation Satellite System (GNSS) signal, the underwater position of an Autonomous Underwater Vehicle (AUV) is estimated through sensor fusion; but in this environment, having the necessity of a small and watertight space, electronic devices are strongly coupled with each other, worsening their overall performance. AVAR can help study these interconnections, understanding how sensors are influenced and what is their behavior in complex structures as an underwater vehicle.
2023
Proceedings of 2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
2023 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea)
La Valletta, Malta
4-6 October 2023
Goal 9: Industry, Innovation, and Infrastructure
Liverani, Gherardo; Bucci, Alessandro; Ridolfi, Alessandro
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1347672
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