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In order to improve the accuracy of signal reconstruction and the application range of sparsity, a new method of measuring matrix optimization is proposed. First, Multiply measurement matrix and sparse transformation matrix to construct a Gram matrix, and calculate the minimum value of mutual coherence, that is the Welch bound; Secondly, Set a threshold based on Welch bound and reduce the elements of the non-diagonal of the Gram matrix; Third, Produce new projection matrix from inverse solution of new Gram matrix and sparse transformation matrix iteratively, so as to achieve the purpose of reduction the mutual coherence and optimizing the measurement matrix. Experiments in the last show: Measurement matrix based on the Welch optimization can rapidly reduce the maximum value of the compressed sensing correlation matrix and improve the performance of OMP algorithm, such as when error rate is 10-0.9, the original Gauss random matrix need 23 observations, but our optimized matrix only 16 observations. On the