Stellar map denoising and centroid positioning, which directly determine the postpositioning accuracy of star trackers, are key technologies in stellar map processing. Due to the influence of a complex starry sky background, there is often a large amount of noise in stellar maps, which makes it difficult to accurately locate the stellar centroid. A stellar map processing method based on dark channel denoising and continuous multiframe stellar map centroid positioning combined with centroid trajectory constraints is proposed. First, a dark channel noise template is used for denoising, and the single-point and multipoint noises in the denoising result are filtered. Second, in the process of stellar map positioning, if the maximum gray value of the stellar is not unique, it is constrained by the previous stellar positioning result, an adaptive window is established, and the gray-scale centroid weighting method is used to locate the centroid. Then, the star angular distance is used to analyze the precision of the centroid positioning. Finally, the jitter frequency of the satellite platform based on the continuous multiframe centroid positioning result is used to detect satellite attitude. The experimental results show that the performance of dark channel denoising, which can solve many strip noise and background noise problems in stellar maps, is better than that of the existing stellar map denoising method. The centroid positioning results improves the star angular distance by 18.85 arc sec compared with the Gaussian filter and by 8.03 arc sec compared with the global threshold segmentation method, significantly improving the accuracy of stellar map centroid positioning and laying a foundation for improving the star tracker positioning accuracy. A jitter frequency of 0.67 Hz was detected on the ZiYuan3 satellite platform based on the centroid positioning results. It enriches the jitter detection methods and provides a theoretical and technical basis for the design of future high-resolution ground observation remote sensing satellite platforms and geometric accuracy compensation.

中文翻译：

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ZiYuan3卫星平台基于暗通道降噪的恒星图质心定位和抖动检测的可行性

恒星图的去噪和质心定位直接决定恒星跟踪器的后置精度，是恒星图处理中的关键技术。由于复杂的星空背景的影响，在恒星图中通常会存在大量噪声，这使得很难准确地定位恒星质心。提出了一种基于暗通道去噪和连续多帧恒星图质心定位结合质心轨迹约束的恒星图处理方法。首先，使用暗通道噪声模板进行降噪，并对降噪结果中的单点和多点噪声进行滤波。其次，在恒星图定位过程中，如果恒星的最大灰度值不是唯一的，则受先前恒星定位结果的约束，建立自适应窗口，并采用灰度质心加权方法对质心进行定位。然后，使用星角距离分析质心定位的精度。最后，基于连续多帧质心定位结果的卫星平台抖动频率被用于检测卫星姿态。实验结果表明，暗通道去噪性能优于现有的恒星图去噪方法，能够较好地解决恒星图中的条带噪声和背景噪声问题。质心定位结果与高斯滤波器相比，将星角距离提高了18.85弧秒，与全局阈值分割方法相比，提高了8.03弧秒，显着提高了恒星图质心定位的精度，为提高恒星跟踪仪的定位精度奠定了基础。根据质心定位结果，在ZiYuan3卫星平台上检测到0.67 Hz的抖动频率。它丰富了抖动检测方法，为未来的高分辨率地面观测遥感卫星平台的设计和几何精度补偿提供了理论和技术基础。