Reconstruction methods for acoustic particle detection in the deep sea using clusters of hydrophones

TL;DR

This paper presents methods for acoustic source reconstruction in the deep sea using hydrophone clusters, focusing on noise reduction, signal filtering, and position estimation with simulated data.

Contribution

It introduces a cluster-based approach with beamforming algorithms for accurate acoustic source localization in deep-sea environments.

Findings

Bandpass filters and cross correlations improve signal-to-noise ratio.

Cluster-based beamforming effectively reconstructs source direction.

Simulated data demonstrates the feasibility of the proposed methods.

Abstract

This article focuses on techniques for acoustic noise reduction, signal filters and source reconstruction. For noise reduction, bandpass filters and cross correlations are found to be efficient and fast ways to improve the signal to noise ratio and identify a possible neutrino-induced acoustic signal. The reconstruction of the position of an acoustic point source in the sea is performed by using small-volume clusters of hydrophones (about 1 cubic meter) for direction reconstruction by a beamforming algorithm. The directional information from a number of such clusters allows for position reconstruction. The algorithms for data filtering, direction and position reconstruction are explained and demonstrated using simulated data.