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Abstract:The drift angle caused by the Earth's self-rotation may introduce rotational displacement artifact on the geolocation results of imagery acquired by an Earth observing sensor onboard the International Space Station (ISS). If uncorrected, it would cause a gradual degradation of positional accuracy from the center towards the edges of an image. One correction method to account for the drift angle effect was developed. The drift angle was calculated from the ISS state vectors and positional information of the ground nadir point of the imagery. Tests with images acquired by the International Space Station Agriculture Camera (ISSAC) using Google Earth TM as a reference indicated that applying the drift angle correction can reduce the residual geolocation error for the corner points of the ISSAC images from over 1000 to less than 500 m. The improved geolocation accuracy is well within the inherent geolocation uncertainty of up to 800 m, mainly due to imprecise knowledge of the ISS attitude and state parameters required to perform the geolocation algorithm.

Light plane deviation and motion direction deviation of stage systems are the two main sources of systematic errors in circle-structured light inner surface measurement systems. In this paper, we propose a new two-step calibration method to compensate these systematic errors. In the first step, a more accurate initial light plane calibration result is obtained by multi-position binocular-structured light calibration. Then, in the second step, the initial result is optimized by measuring the inner radius of a standard ring gauge to obtain the optimal light plane calibration result. Based on this result, the real motion direction is also calibrated by optimization using the inner surface scanning measurement data of the standard ring gauge. The proposed method improves the system calibration accuracy through the second calibration step, making it convenient to operate without using complex calibration targets or expensive equipment. Therefore, this calibration method has the potential to be used in actual measurements. The experimental results show that the mean relative measurement error can reach 0.015% in our homemade measurement system and validate that the measurement system calibrated by our proposed method realizes high-precision and high-repeatability measurements for inner surfaces.

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