Accelerometer Calibration and Dynamic Bias and Gravity Estimation: Analysis, Design, and Experimental Evaluation

Abstract

Tri-axial linear accelerometers are key components in a great variety of applications and, in particular, in navigation systems. Nonidealities such as scale factors, cross coupling, bias, and other higher-order nonlinearities affect the output of this sensor, leading, in general, to prohibitive errors. On the other hand, these coefficients are often slowly time-varying, which renders offline calibration less effective. One such coefficient that usually varies greatly over time and between power-ons is the bias. This paper details the calibration of an accelerometer unit and presents also a dynamic filtering solution for the bias, which also includes the estimation of the gravity in body-fixed coordinates. Simulation and experimental results obtained with a motion rate table are presented and discussed to illustrate the performance of the proposed algorithms.