Signal Enhancement and Deconvolution Based Improved Underwater 3D Acoustic Imaging with Range Extension

During the reconstruction of underwater 3D acoustic images conventional beamforming introduces distortion in the form of broadening of objects in the image due to main lobe and spectral leakage due to side lobes of the beam-pattern. This distortion can be modeled as the convolution of the point spread function of the beamformer with the ideal image. To de-convolve this effect of beamforming, a decon-volution technique is used, namely Deconvolution Approach for Mapping Acoustic Sources (DAMAS). This enhances the angular resolution of the reconstructed underwater acoustic image over the raw image, but we have observed that it works only above a minimum input SNR of the received signal at the hydrophone sensors of the receiver array. We introduce a sensor level signal enhancement method to extend the effectiveness of the DAMAS method to lower SNRs, which is shown to be about 18dB lower for an illustrative case study. This alternately translates to an increase in the maximum imaging range upto which DAMAS based image enhancement technique remains effective. Sonar equation analysis is also reported which shows that the above input SNR enhancement maps to an increase of approximately 32% in the maximum imaging range.