Error Compensation Analysis of Three-Axis Magnetic Sensor Based on M-estimation

In the error compensation algorithm of the three-axis magnetic sensor, an M-estimation supplementary strategy is introduced to solve the problem that the abnormal sampling point will affect the results of geomagnetic data correction. M-estimation calculates the weight of each sampling point through the selected cost function, thereby reducing the influence of outliers. The Huber, Hampel and Tukey cost functions are selected to complete the error compensation algorithm of three-axis magnetic sensor based on M-estimation, and these three methods are compared in terms of mean square error, average error and running time through simulation. The simulation results show that the three methods are similar in the case of small deviation and small number of outliers. And the compensation effect based on the Tukey cost function is the best when the outliers are offset large and the number is large.