Efficient Simultaneous Calibration of a Magnetometer and an Accelerometer

TL;DR

This paper presents a calibration algorithm that simultaneously calibrates magnetometers and accelerometers using only sensor readings, achieving high accuracy in simulations and real-world tests.

Contribution

The novel algorithm calibrates both sensors simultaneously with a linear model and maximum likelihood, without requiring additional information.

Findings

Errors less than 0.1 standard deviations in simulation

High-quality estimates with real sensors

Robust performance despite assumption violations

Abstract

This paper describes a calibration algorithm to simultaneously calibrate a magnetometer and an accelerometer without any information besides the sensors readings. Using a linear sensor model and maximum likelihood cost, the algorithm is able to estimate both sensors' biases, gains, and covariances, besides sensor orientations and Earth's fields. Results show errors of less than 0.1 standard deviations in simulation, and high-quality estimates with real sensors even when the algorithm's assumptions are violated.