Snapping shrimp noise reduction using convex optimization for underwater acoustic communication in warm shallow water

We propose an ambient noise reduction technique for underwater acoustic communication systems in warm shallow water, where the snapping shrimp impulsive noise is a common impairment. This noise is emitted at the cavitation bubble collapse caused by the claw shut, and can produce very high acoustic pressures which are responsible for the impulsiveness of the noise. The denoised signal is the solution of an unconstrained scalarized bi-criterion convex optimization problem. One of the criterions is based on the robust least-squares signal reconstruction approach, for which the sum of the Huber penalty function of the residuals is minimized. The other criterion uses a quadratic smoothing regularization term, acting on the first-difference of the denoised signal samples. It is shown that the proposed technique can significantly reduce the ambient noise and, thus, reduce the bit error rate of an underwater digital communication system.