Polarization navigation is an autonomous navigation method that relies on stable polarization patterns in the sky. The polarization sensor for navigation is composed of a CMOS image sensor (CIS) and four-direction metal nanograting. The optical conversion deviation of the CIS and the transmittance deviation of metal nanograting are the main factors affecting the angle measurement accuracy of the polarization sensor. A full-parameter calibration method that can accurately calculate the performance parameters in the Mueller matrix of all pixels is proposed. To reduce the error of the sensor, a mode-based region extraction algorithm that can extract the effective region of the sensor according to the statistical law of these performance parameters is proposed. The experimental results demonstrate that the proposed algorithm can effectively improve the angle measurement accuracy of the sensor. Compared with the single-parameter calibration and the region selection method based on the light intensity graph, the proposed method reduces the angle measurement error by 27.89% and significantly improves the robustness.

中文翻译：

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用于导航的偏振传感器的校准和区域提取

极化导航是一种自主的导航方法，它依赖于天空中稳定的极化模式。用于导航的偏振传感器由CMOS图像传感器（CIS）和四向金属纳米光栅组成。CIS的光学转换偏差和金属纳米光栅的透射率偏差是影响偏振传感器角度测量精度的主要因素。提出了一种可以准确计算所有像素的Mueller矩阵中的性能参数的全参数校准方法。为了减少传感器的误差，提出了一种基于模式的区域提取算法，可以根据这些性能参数的统计规律提取传感器的有效区域。实验结果表明，该算法可以有效提高传感器的角度测量精度。与单参数校准和基于光强图的区域选择方法相比，该方法将角度测量误差降低了27.89％，显着提高了鲁棒性。