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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Autonomous Star Camera Calibration and Spacecraft Attitude Determination
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Autonomous Star Camera Calibration and Spacecraft Attitude Determination

机译：自主星相机校准和航天器姿态确定

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This paper presents two methods of star camera calibration to determine camera calibrating parameters (like principal point, focal length etc) along with lens distortions (radial and decentering). First method works autonomously utilizing star coordinates in three consecutive image frames thus independent of star identification or biased attitude information. The parameters obtained in autonomous self-calibration technique helps to identify the imaged stars with the cataloged stars. Least Square based second method utilizes inertial star coordinates to determine satellite attitude and star camera parameters with lens radial distortion, both independent of each other. Camera parameters determined by the second method are more accurate than the first method of camera self calibration. Moreover, unlike most of the attitude determination algorithms where attitude of the satellite depend on the camera calibrating parameters, the second method has the advantage of computing spacecraft attitude independent of camera calibrating parameters except lens distortions (radial). Finally Kalman filter based sequential estimation scheme is employed to filter out the noise of the LS based estimation.
机译：本文介绍了两种星形相机校准方法，以确定相机校准参数（例如主点，焦距等）以及镜头畸变（径向和偏心）。第一种方法自主地利用三个连续图像帧中的星形坐标，因此独立于星形标识或偏向的姿态信息。在自主自校准技术中获得的参数有助于识别已分类恒星的成像恒星。基于最小二乘的第二种方法利用惯性星坐标来确定卫星姿态和具有镜头​​径向畸变的星相机参数，两者彼此独立。通过第二种方法确定的照相机参数比第一种照相机自校准方法更准确。而且，不同于大多数姿态确定算法，其中卫星的姿态取决于摄像机的校准参数，第二种方法的优势在于，除了镜头畸变（径向）外，航天器姿态的计算独立于摄像机的校准参数。最终，采用基于卡尔曼滤波器的顺序估计方案来滤除基于LS的估计的噪声。

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