# Acoustic and geoacoustic inverse problems in randomly perturbed shallow-water environments

## TL;DR

This paper develops a method to estimate the statistical properties of the water column and sea bottom in shallow-water environments using acoustic data, by modeling wave propagation as Markovian dynamics and solving a nonlinear inverse problem.

## Contribution

It introduces a novel approach to estimate environmental parameters from acoustic data by formulating the problem as a Markovian and nonlinear inverse problem, validated with real data.

## Key findings

- Successful estimation of water column fluctuations
- Effective characterization of sea bottom properties
- Validated method with experimental data

## Abstract

The main goal of this paper is to estimate the regional acoustic and geoacoustic shallow-water environment from data collected by a vertical hydrophone array and transmitted by distant time-harmonic point sources. We aim at estimating the statistical properties of the random fluctuations of the index of refraction in the water column and the characteristics of the sea bottom. We first explain from first principles how acoustic wave propagation can be expressed as Markovian dynamics for the complex mode amplitudes of the sound pressure, which makes it possible to express the cross moments of the sound pressure in terms of the parameters to be estimated. We then show how the estimation problem can be formulated as a nonlinear inverse problem using this formulation, that can be solved by minimization of a misfit function. We apply this method to experimental data collected by the ALMA system (Acoustic Laboratory for Marine Applications).