LAUSR

Abstract For the two-dimensional forward-look sonar imaging, the conventional beamformer (CBF) and the matched filter (MF) are often used due to the simplicity and robustness. However, the angular and range resolutions are limited and the sidelobes (SLs) are high. In this paper, we propose a deconvolution method to improve the resolutions and reduce the SLs. The proposed method uses a two-step Richardson-Lucy (R-L) algorithm to deconvolve the raw sonar image produced by CBF and MF, which is actually a post-beamformer processing method. In the first step the R-L algorithm is applied to the angular dimension, where the CBF beampattern is used as the point spread function (PSF); in the second step the R-L algorithm is applied to the range dimension where the auto-correlation function (ACF) of the transmitted linear frequency modulation (LFM) pulse is taken as the PSF. Furthermore, the non-ideal conditions including the low signal-to-noise ratio, the array manifold vector error and the echo distortion error are considered. Via numerical simulations and real data analysis, we show that the proposed method can improve the angular and range resolutions and reduce SLs significantly, while maintains a good robustness against these non-ideal conditions.