Camera calibration method for an infrared horizon sensor with a large field of view

Abstract

Inadequate geometric accuracy of cameras is the main constraint to improving the precision of infrared horizon sensors with a large field of view (FOV). An enormous FOV with a blind area in the center greatly limits the accuracy and feasibility of traditional geometric calibration methods. A novel camera calibration method for infrared horizon sensors is presented and validated in this paper. Three infrared targets are used as control points. The camera is mounted on a rotary table. As the table rotates, these control points will be evenly distributed in the entire FOV. Compared with traditional methods that combine a collimator and a rotary table which cannot effectively cover a large FOV and require harsh experimental equipment, this method is easier to implement at a low cost. A corresponding three-step parameter estimation algorithm is proposed to avoid precisely measuring the positions of the camera and the control points. Experiments are implemented with 10 infrared horizon sensors to verify the effectiveness of the calibration method. The results show that the proposed method is highly stable, and that the calibration accuracy is at least 30% higher than those of existing methods.

摘要

相机的几何精度不足是制约大视场红外地球敏感器精度提升的主要因素。红外地球敏感器相机超大的视场与中心的盲区极大地限制了传统几何标定方法的准确性与可行性。本文提出并验证了一种新型的适用于红外地球敏感器的相机标定方法。三个红外靶标被用作控制点，而相机被安装于双轴转台上。随着转台的旋转，这些控制点将均匀地分布在整个相机视场中。与传统的平行光管与转台配合方法相比，传统方法无法有效覆盖大视场且需要苛刻的实验设备，而该方法更易于实施且成本较低。本文还提出了相应的三步参数估计算法，从而不需要精确测量相机和控制点的位置。本文用10台红外地球敏感器进行了实验，以验证标定方法的有效性。结果表明，所提出的方法是高度稳定可靠的，标定精度与现有其他方法相比提升至少30%。