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Blurred Star Image Processing for Star Sensors under Dynamic Conditions

机译:动态条件下星传感器的星图像模糊处理

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摘要

The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions.
机译:恒星点定位的精度对于识别恒星图和获取恒星传感器的飞机姿态非常重要。在动态条件下,星图不仅会受到各种噪音的破坏,而且还会由于星传感器的角速度而模糊。针对动态条件下不同的角速率,提出了一种新的方法,包括基于自适应小波阈值的去噪方法和基于大角速率的恢复方法。当角速率在动态范围内时,采用自适应阈值对星图进行降噪。然后,推导运动模糊的数学模型,以恢复大角速率导致的模糊星图。仿真结果验证了该方法的有效性。该方法适用于模糊星图像处理,在动态条件下适用于卫星姿态确定。

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