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惯性测量单元(IMU)与传感器视准轴的偏心角和偏心矢量是造成航空线阵列高光谱数据几何校正误差的主要原因之一。在分析偏心角与偏心矢量误差来源之后提出该误差由IMU主轴与传感器主轴的角度偏差、测区固定偏差、GPS中心与传感器投影中心相对偏差组成,在此基础上建立了较为严密的检校模型。针对模型解算时需要大量高精度控制点的问题,提出了一种高分影像辅助下的亚像元精度控制点自动提取方法。通过多地区、多传感器高光谱航测实验表明,亚像元精度控制点能有效提高模型解算精度。新检校模型可获得亚像元校正精度,推扫式传感器——应用型机载成像光谱仪(AISA)建模中误差约为0.39个像元,摆扫式传感器——实用型模块化成像光谱仪(OMIS)建模中误差约为0.23个像元,校正后的影像可直接进行拼接。
Offset angle and eccentricity vector of inertial measurement unit (IMU) and sensor collimation axis are one of the main reasons for the geometric correction error of hyperspectral data of aeronautical line array. After analyzing the sources of eccentric angle and eccentricity vector error, this error is proposed by the angle deviation of IMU spindle and sensor spindle, the fixed deviation of measurement zone and the relative deviation of GPS center and sensor projection center. On this basis, a more rigorous calibration model . Aiming at the problem that a large number of high-precision control points are needed in solving the model, a sub-pixel precision control point automatic extraction method with the help of high score image is proposed. Multi-regional, multi-sensor hyperspectral airborne experiments show that the sub-pixel precision control points can effectively improve the model solution accuracy. The new calibration model can achieve sub-pixel correction accuracy, the error of the push-broom sensor-applied AISA model is about 0.39 pixels, and the swept-swept sensor-practical modular imaging spectrometer (OMIS) modeling error of about 0.23 pixels, the corrected image can be directly spliced.