Improving the resolution of underwater acoustic image measurement by deconvolution

Abstract The conventional beamforming (CBF) map of underwater acoustic image measurement can be expressed as a convolution of the source distribution and the response of the beamformer to a point source, defined as the beam pattern or the point spread function (PSF). By deconvolving the CBF beamformer’s map, the distribution of the actual sources with a clean beam map can be obtained to improve the resolution. In this paper, the deconvolved conventional beamforming (dCv) is applied to underwater acoustic image measurement to improve the accuracy of sound source localization. Due to the point spread function of the array in near field is dependent on the focused point, which means that the PSF is shift variant, so it is necessary to use shift-variant deconvolution method. In this paper, an extended Richardson-Lucy (Ex-RL) algorithm is applied to the two-dimensional shift-variant deconvolution acoustic image measurement problem to improve resolution. The method is compared with the original-RL, classical deconvolution approach for the mapping of acoustic sources (DAMAS) and non-negative least squares (NNLS). The simulation and the experiment results verify the effectiveness of the algorithm.