Aas 08-219 an Expectation-maximization Approach to Attitude Sensor Calibration

An Expectation-Maximization approach to sensor calibration is presented and applied to three-axis-magnetometer calibration. This approach is different from the existing attitude-independent approaches mainly in how the attitude parameters in the attitude sensor measurement model are handled. The attitude-independent approaches rely on a conversion of the body and reference representations of the Earth’s magnetic field vector into an attitude-independent scalar observation based on scalar checking. The Expectation-Maximization (EM) algorithm essentially maximizes the expectation of the complete likelihood function with respect to the probability distribution of the attitude parameters. Comparisons of the EM algorithm and the attitudeindependent approach using simulated magnetometer data are presented.