Conservative Estimation of Inertial Sensor Errors Using Allan Variance Data

Conservative Estimation of Inertial Sensor Errors Using Allan Variance Data

Blog Article

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 a sensor.Recent work has sought to overcome the graphical arrethe bush balm nature and visual-inspection 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 read more using the Allan variance.Results of using this method to characterize a low-cost MEMS IMU (Analog Devices ADIS16470) are presented, demonstrating the efficacy of the proposed approach.