TRIAD+Filtering Approach for Complete Magnetometer Calibration

This paper proposes using TRIAD and Unscented Kalman Filter (UKF)algorithms in a sequential architecture as a part of the small satellite attitude estimation algorithm. This TRIAD+UKF approach can provide accurate attitude estimates for the satellite by calibrating the magnetometers in real-time. A complete calibration model for the magnetometers, considering bias, scale factor, soft iron and nonorthogonality errors, is assumed. In algorithm's first stage, the TRIAD uses the available vector measurements (e.g. from Sun sensor and magnetometers)to estimate a coarse attitude. In the second stage, these estimated values are used as quaternion measurements in the UKF algorithm, together with angular rate measurements provided by a triad of gyros. The state vector for the UKF is composed of the attitude, gyro biases and the magnetometer error terms. In result, we get fine attitude estimate for the satellite by calibrating the magnetometers against scaling, soft iron, nonorthogonality and bias errors in real-time. We evaluate the algorithm for a hypothetical nanosatellite by numerical simulations. The results show that the attitude of the satellite can be estimated with accuracy better than 1deg and the magnetometers can be fully calibrated.