Title :
Magnetometer Calibration Using Kalman Filter Covariance Matrix for Online Estimation of Magnetic Field Orientation
Author :
Beravs, Tadej ; Begus, Samo ; Podobnik, J. ; Munih, Marko
Author_Institution :
Lab. of Robot., Univ. of Ljubljana, Ljubljana, Slovenia
Abstract :
The inertial/magnetic measurement units are an affordable instrument for the determination of orientation. The sensors embedded in the system are affected by nonidealities that can be greatly compensated by proper calibration, by determining sensor parameters, such as bias, misalignment, and sensitivity/gain. This paper presents an online calibration method for a three-axial magnetometer using a 3-D Helmholtz coil. The magnetometer is exposed to different directions of the magnetic field created by the 3-D coil. The parameters are estimated by using an unscented Kalman filter. The directions are calculated online by using a sensor parameter covariance matrix. The method evaluation is achieved by first running numerous simulations, followed by experiments using a real magnetometer, finally resulting in better accuracy of parameter estimation with a low number of measurement iterations compared with the method where magnetic field directions are determined manually.
Keywords :
Kalman filters; calibration; coils; covariance matrices; iterative methods; magnetic field measurement; magnetic sensors; magnetometers; nonlinear filters; 3D Helmholtz coil; embedded sensor; inertial-magnetic measurement unit; magnetic field orientation online estimation; measurement iteration number; online calibration method; sensor parameter covariance matrix; three-axial magnetometer; unscented Kalman filter; Calibration; Coils; Covariance matrices; Magnetic sensors; Magnetometers; Parameter estimation; Magnetometer calibration; orientation determination; sensor parameter estimation; unscented Kalman filtering (UKF); unscented Kalman filtering (UKF).;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2014.2302240