TMR Angle Sensor Calibration with 3D Misalignment Compensation

This paper introduces an efficient tilt calibration and compensation method for tunnel magnetoresistive (TMR) angle sensors. The approach models the sensor's response and, using Bayesian design of experiments, optimizes calibration conditions to minimize predictive uncertainty. A symmetric arrangement of six calibration field vectors with strong out-of-plane components is found to ensure optimal calibration. The cross-sensitivity of the inferred azimuthal angle of applied 3D $B$ fields to sensor misalignment is thereby efficiently suppressed. For $B$ fields with polar angles of 45°, rms angle errors are reduced from about 2.6°to about 0.12. In addition, the standard deviation of the residual angle error under random sensor misalignment is reduced by factors between 3 and 12.