Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration

11/16/2019
by   Stéphane Guerrier, et al.
0

The task of inertial sensor calibration has required the development of various techniques to take into account the sources of measurement error coming from such devices. The calibration of the stochastic errors of these sensors has been the focus of increasing amount of research in which the method of reference has been the so-called "Allan variance slope method" which, in addition to not having appropriate statistical properties, requires a subjective input which makes it prone to mistakes. To overcome this, recent research has started proposing "automatic" approaches where the parameters of the probabilistic models underlying the error signals are estimated by matching functions of the Allan variance or Wavelet Variance with their model-implied counterparts. However, given the increased use of such techniques, there has been no study or clear direction for practitioners on which approach is optimal for the purpose of sensor calibration. This paper formally defines the class of estimators based on this technique and puts forward theoretical and applied results that, comparing with estimators in this class, suggest the use of the Generalized Method of Wavelet Moments as an optimal choice.

READ FULL TEXT
research
05/04/2019

Multivariate Signal Modelling with Applications to Inertial Sensor Calibration

The common approach to inertial sensor calibration for navigation purpos...
research
06/30/2021

Scale-wise Variance Minimization for Optimal Virtual Signals: An Approach for Redundant Gyroscopes

The increased use of low-cost gyroscopes within inertial sensors for nav...
research
06/09/2023

Bayesian Calibration of MEMS Accelerometers

This study aims to investigate the utilization of Bayesian techniques fo...
research
03/31/2023

Accounting for Vibration Noise in Stochastic Measurement Errors

The measurement of data over time and/or space is of utmost importance i...
research
03/15/2022

Trustworthy Deep Learning via Proper Calibration Errors: A Unifying Approach for Quantifying the Reliability of Predictive Uncertainty

With model trustworthiness being crucial for sensitive real-world applic...
research
08/02/2019

Secure Calibration for High-Assurance IoT: Traceability for Safety Resilience

Traceable sensor calibration constitutes a foundational step that underp...
research
06/14/2021

Generalizations to Corrections for the Effects of Measurement Error in Approximately Consistent Methodologies

Measurement error is a pervasive issue which renders the results of an a...

Please sign up or login with your details

Forgot password? Click here to reset