Abstract

In this study, a weighted estimation algorithm is proposed for food transporting two-axis magnetic compass. This method is based on ellipse fitting algorithm and compensates the combined effort of all linear time-invariant distortions, namely bias, scale factor, hard iron, non-orthogonality and so on. In contrast to the direct ellipse fitting method for estimating ellipse coefficient, which achieves best estimate based on minimizing the mean square algebraic distance from collected data points to ellipse in mathematical model, this procedure presents a new estimator in least-square sense where the weighted approximate distance is presented. The algorithm is simulated to verify robustness and further validated on collected experimental data using a low-cost fluxgate compass. The results indicate that the calibration algorithm is effective and superior to the direct ellipse fitting method, the heading error after calibration is less than.

Keywords:

Calibration algorithm, ellipse fitting, food magnetic compass, weighted approximate distance,

References