The invention relates to a singular value decomposition-random sample consensus (SVD-RANSAC) sub-pixel phase correlation matching method. The method includes the following steps that: at first, singular value decomposition is performed on a cross-power spectrum matrix of two images; and then, a random sample consensus algorithm is adopted to estimate the slope of phase angle vectors, and therefore, sub-pixel phase correlation matching of the two images can be realized. Compared with the prior art, and according to the method of the invention, the random sample consensus (RANSAC) algorithm is adopted to robustly estimate the slope of phase angle vector straight lines which are corresponding to main singular value vectors after the singular value decomposition, and only data that accord with a straight line model are selected to be estimated, and data which are subjected to deviation influence are discarded, and therefore, the singular value decomposition-random sample consensus (SVD-RANSAC) sub-pixel phase correlation matching method is advantageous in high-precision and high-stability results and effective inhabitation of a pixel locking phenomenon.