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首页> 外文期刊>Acta astronautica >A new star tracker concept for satellite attitude determination based on a multi-purpose panoramic camera
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A new star tracker concept for satellite attitude determination based on a multi-purpose panoramic camera

机译：一种基于多功能全景摄像机的新恒星跟踪器概念，用于卫星姿态确定

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摘要

This paper presents an innovative algorithm developed for attitude determination of a space platform. The algorithm exploits images taken from a multi-purpose panoramic camera equipped with hyper-hemispheric lens and used as star tracker. The sensor architecture is also original since state-of-the-art star trackers accurately image as many stars as possible within a narrow- or medium-size field-of-view, while the considered sensor observes an extremely large portion of the celestial sphere but its observation capabilities are limited by the features of the optical system. The proposed original approach combines algorithmic concepts, like template matching and point cloud registration, inherited from the computer vision and robotic research fields, to carry out star identification. The final aim is to provide a robust and reliable initial attitude solution (lost-in-space mode), with a satisfactory accuracy level in view of the multi-purpose functionality of the sensor and considering its limitations in terms of resolution and sensitivity. Performance evaluation is carried out within a simulation environment in which the panoramic camera operation is realistically reproduced, including perturbations in the imaged star pattern. Results show that the presented algorithm is able to estimate attitude with accuracy better than 1 degrees with a success rate around 98% evaluated by densely covering the entire space of the parameters representing the camera pointing in the inertial space.
机译：本文提出了一种创新的算法，用于确定空间平台的姿态。该算法利用从配备了超半球镜的多功能全景相机拍摄的图像用作星跟踪器。传感器架构也是独创的，因为最先进的恒星跟踪仪可在狭窄或中等大小的视场内准确成像尽可能多的恒星，而考虑的传感器可观测到很大的天球区域但是其观察能力受到光学系统功能的限制。提出的原始方法结合了从计算机视觉和机器人研究领域继承来的模板匹配和点云配准等算法概念，以进行恒星识别。最终目的是提供一种可靠且可靠的初始姿态解决方案（空间丢失模式），鉴于传感器的多功能性并考虑其在分辨率和灵敏度方面的局限性，因此具有令人满意的精度水平。性能评估是在模拟环境中进行的，在该环境中可以真实地再现全景相机的操作，包括对成像星型的干扰。结果表明，所提出的算法能够通过密集覆盖代表惯性空间的摄像机参数的整个空间，来估计精度优于1度的姿态，其成功率约为98％。

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