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Extraction methed of the motion blurred star image for the star sensor under high dynamic conditions

机译:高动态条件下恒星传感器运动模糊恒星图像的提取方法

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Star sensor is beyond dispute the most accuracy absolute attitude determination sensor and it is widely used in deep space exploring and earth observing. Star image spots captured in the image sensor of the star sensor will elongate when it is under high dynamic conditions especially the rotation motion resulting in the blurred star images. The motion blurred star images with low SNR lead to the increase of difficulty in the extraction of the star areas. Normal processing procedures as the estimation of background threshold, image binarization and connected components analysis are not profitable anymore. A extraction method of the motion blurred star image based on template-correlation matching of the star sensor under high dynamic conditions is proposed in this paper. Parameters of the motion degradation function is precisely measured with the strap down laser gyro unit. So the template is generated in real time according to different dynamic conditions through the degradation model of the motion blurred image. Correlation matching criterion like minimum correlation difference and maximum correlation product are alternatives. Simulation and experimental results show that this method readily identifies and extracts the star spot area and removes the noises outside its region simultaneously. It is effective in extracting faint blurred star images unless they are totally submerged by the noise.
机译:恒星传感器无疑是最准确的绝对姿态确定传感器,它广泛用于深空探测和地球观测中。在恒星传感器的图像传感器中捕获的恒星图像斑点在高动态条件下(尤其是旋转运动)会伸长,从而导致恒星图像模糊。低信噪比的运动模糊恒星图像导致提取恒星区域的难度增加。正常的处理程序(例如背景阈值的估计,图像二值化和连接的组件分析)不再有任何利润。提出了一种基于高动态条件下恒星传感器模板相关匹配的运动模糊恒星图像提取方法。运动下降功能的参数是使用捷联激光陀螺仪单元精确测量的。因此,通过运动模糊图像的退化模型,根据不同的动态条件实时生成模板。诸如最小相关差和最大相关乘积之类的相关匹配准则是替代方案。仿真和实验结果表明,该方法可以很容易地识别和提取星点区域,并同时消除其区域外的噪声。除非模糊的星图完全被噪音淹没,否则它可以有效地提取模糊的星图。

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