Abstract: In order to solve the problem that the segment weak orthogonal matching pursuit algorithm was difficult to obtain high-precision reconstructed signals during the measurement process,firstly,the traditional SWOMP algorithm with Gaussian matrix as the measurement matrix was analyzed,and the key to the problem lay in the column coherence of the Gaussian matrix,which excessive assembly affects the matching process of the residual signal,resulting in partial signal loss and reduced reconstruction accuracy.Then,based on the analysis,a piecewise weak orthogonal matching tracking algorithm(PH-SWOMP)based on partial Hadamard matrix was proposed.Part of the Hadamard matrix was constructed according to the principle of even row extraction,which can significantly reduce the cross-correlation of the measurement matrix.Finally,the performance of the PH-SWOMP algorithm was verified through the image simulation experiment with the traditional SWOMP algorithm.Among them,the traditional SWOMP algorithm selected the Gaussian matrix,the Toeplitz matrix and other two matrices as the measurement matrix.The simulation results show that under the same conditions,compared with the traditional SWOMP algorithm,the PH-SWOMP algorithm has a maximum signal-to-noise ratio increase of 53.95%,the corresponding reconstruction time is reduced by 15.41%,and has a smaller recovery residual and higher signal reconstruction power.