A method of sound source recognition based on tow weak selection compressed sensing

The current compression sensing sound source recognition algorithm is mainly based on prior knowledge of exact sparsity. This paper proposes the two stagewise weak orthogonal matching pursuit (TSWOMP) compressed sensing reconstruction algorithm for sound source recognition, which selects atoms and detects the reliability of the selected atoms, and deletes the wrong atoms to obtain the final set of atoms. The results of TSWOMP, stagewise weak orthogonal matching pursuit (SWOMP) and conventional beamforming under different frequencies and different SNR are compared through numerical simulation methods. The results show that TSWOMP can effectively reduce the width of the main lobe, suppressing the influence of the side lobes, and improve the resolution. The recognition accuracy of TSWOMP is significantly higher than that of SWOMP. In addition, it can effectively reduce the algorithm's dependence on sparsity.