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为了获得高精度、高更新率的抗噪声性能,对星敏感器星像提取环节进行了研究。首先,分析星图中星像灰度的分布特点,建立了判断某个像素是否与峰值像素归属同一星像的标准。然后,介绍了像元阵列分块方法和背景预测法。最后,结合星像的特点提出了以峰值点为种子点的区域生长准则。仿真实验结果表明,在不加噪声的情况下,提取出的星像与参考星图完全一致,用质心法得到的亚像素定位精度为0.028 2。在添加均值为20、标准差高达2.5的强高斯灰度噪声的情况下,提取率仍能达到86.11%,质心精度则下降到0.219 6pixel。均匀性很差,信噪比低于4.9dB的实拍星图实验结果也证明该方法有很强的星像提取能力和准确性,能够满足强噪声弱星像质心提取的强抗干扰能力的要求。
In order to obtain high-precision, high update rate of anti-noise performance, star sensor star image extraction links were studied. Firstly, the distribution of star grayscale in the star image is analyzed, and a criterion for determining whether a certain pixel belongs to the same star image as the peak pixel is established. Then, the pixel array block method and background prediction method are introduced. Finally, according to the characteristics of the star image, the regional growth criterion with the peak point as the seed point is proposed. Simulation results show that the extracted star images are completely consistent with the reference star without noise, and the sub-pixel positioning accuracy obtained by the centroid method is 0.028 2. With the addition of Gaussian Gaussian noise with a mean of 20 and standard deviation up to 2.5, the extraction rate can still reach 86.11% and the centroid accuracy decreases to 0.219 6 pixels. Uniformity is very poor, the signal to noise ratio is less than 4.9dB real star chart experimental results also prove that the method has a strong star image extraction ability and accuracy, strong noise can weak star like centroid extraction strong anti-interference ability Claim.