Multiple Disturbance Analysis and Calibration of an Inspired Polarization Sensor

Abstract

Polarization light has been used as a key navigation cue by many animals under a stable celestial polarization pattern. Inspired by animals' unrivaled navigation skill, a bionic polarization sensor is designed previously to obtain the angle of polarization and degree of polarization. However, the accuracy and stability of the sensor are restricted by multi-source errors. In order to improve the accuracy of the sensor, in this paper, the multi-source errors are analyzed and modeled. A coarse calibration is presented to reduce the effect of inconsistency and interference. In addition, the extended Kalman filter and the unscented Kalman filter are designed to estimate the multi-source error or interference and compensate for the bionic polarization sensor. Finally, simulation and indoor experiments are conducted to validate the effectiveness of the proposed calibration method.