为了解决混凝土结构挠度测量中参考点精确定位的问题，推导了高斯光斑的拟合算法，证明了参数克拉美−罗下界的存在，并利用莱文贝格−马夸特方法优化了相应参数。实验结果表明，基于非线性参数优化的高斯拟合光斑定位算法在信噪比为40 dB时，其中心提取的均方根误差衰减为0。随着对比度的降低，3种测试方法的提取精度会变差。在对比度降至原图像的25%之前，基于非线性参数优化的高斯拟合光斑定位算法的鲁棒性优于其他算法，但当对比度继续下降时，这一优势将消失。因此，在对比度良好的情况下，该算法不仅可以保证精度而且可以较好地提高鲁棒性。

This paper mainly solves the problem of accurate positioning of reference points in deflection measurement of concrete structures. The fitting algorithm of Gaussian spot is derived. The existence of the parameter Krame-Rowe lower bound is proved, and the corresponding parameters are optimized by the Levenberg-Marquardt method. The experimental results show that the root mean square error attenuated by the center extracted by the Gaussian fitting spot localization algorithm based on nonlinear parameter optimization is 0 when the signal-to-noise ratio is 40 dB. As the contrast decreases, the extraction accuracy of the three methods deteriorates. The Gaussian fitted spot localization algorithm based on nonlinear parameter optimization is superior to other algorithms before the contrast drops to 25% of the original image, but this advantage disappears when the contrast continues to decrease. It shows that in the case of good contrast, it can not only ensure accuracy but also improve robustness.