Disturbance analysis and performance test of the polarization sensor based on polarizing beam splitter

Purpose: Multiple-source disturbances exist in the polarization sensor, which severely affect the sensor accuracy and stability. Hence, the disturbance analysis plays a vital role in improving the sensor orientation performance. This paper aims to present a novel sensor error model, a disturbances quantitative analysis, a calibration and performance test of polarization sensor based on a polarizing beam splitter. Design/methodology/approach: By combining with the sensor coefficient errors, the Azimuth of Polarization (AoP) error model and the Degree of Polarization (DoP) error model are established, respectively. In addition, the multiple-source disturbances are classified, while the influence on the orientation accuracy is quantitative analyzed. Moreover, the least square optimization algorithm is employed to calibrate the sensor coefficients. Finally, an outdoor test is carried out to test the sensor long-term accuracy. Findings: The theoretical analysis and numerical simulations illustrate that the sensor accuracy is closely related to the disturbances. To eliminate the influence of the disturbances, the least square optimization algorithm, which can minimize the sum of squares of the residual difference of AoP and DoP, is used to calibrate the sensor coefficients. The outdoor test indicates that the sensor can maintain long-term accuracy and stability. Originality/value: The main contribution of this paper is to establish a novel sensor error model, where the sensor coefficient errors are introduced. In addition, the disturbances are classified and analyzed to evaluate the orientation accuracy of the sensor.