A new method for attitude refinement of earth observation satellite with asynchronous images

2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Pub Date : 2016-07-10 DOI:10.1109/IGARSS.2016.7729309

Tao Sun, Li Huang, Hui Long, Bao-Cheng Liu

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Abstract

The accuracy of attitude observation is always the main contributor to geometric performance of earth observation satellites (EOSs). Given the ground process requirement, linear pushbroom and asynchronous imaging sensors are widely used in EOSs, such as multispectral sensor with sequential line arrays, three-line array sensor in stereo mapping satellite, panchromatic sensor with multiple non-collinear CCD chip in some high-resolution optical satellite. By using the images of those sensors, this paper proposes a method, which is based on image registration approach, rigorous forward intersection and bundle adjustment technology, to refine attitude data of satellite for improving geometric performance of images. Preliminary experiments, which used multi-sensors asynchronous images of Chinese Mapping Satellite-1-02, demonstrate that the proposed method is capable of improving internally coincident precision of attitude data without ground control points. In particular, relative positioning accuracy of images can be directly improved, and absolute positioning accuracy can consequently be improved via additionally using a few GCPs in the stripe image data.

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一种基于异步图像的对地观测卫星姿态优化方法

姿态观测精度一直是影响对地观测卫星几何性能的主要因素。考虑到地面工艺的要求，线性推进式和异步成像传感器在eos中得到了广泛的应用，如序列线阵列的多光谱传感器、立体测绘卫星中的三线阵列传感器、一些高分辨率光学卫星中带有多个非共线CCD芯片的全色传感器。利用这些传感器的图像，提出了一种基于图像配准方法、严格前向交会和束平差技术的卫星姿态数据细化方法，以提高图像的几何性能。利用中国测绘卫星1-02的多传感器异步图像进行初步实验，结果表明，该方法能够提高无地面控制点的姿态数据内部重合精度。特别是，通过在条纹图像数据中额外使用少量gcp，可以直接提高图像的相对定位精度，从而提高图像的绝对定位精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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