Optical remote sensing of sound in the ocean

James H. Churnside; Konstantin Naugolnykh; Richard D. Marchbanks

doi:10.1117/1.JRS.9.096038

16 June 2015 Optical remote sensing of sound in the ocean

James H. Churnside, Konstantin Naugolnykh, Richard D. Marchbanks

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 9, Issue 1, 096038 (June 2015). https://doi.org/10.1117/1.JRS.9.096038

Abstract

We propose a remote sensing technique to measure sound in the upper ocean. The objective is a system that can be flown on an aircraft. Conventional acoustic sensors are ineffective in this application, because almost none (∼0.1%) of the sound in the ocean is transmitted through the water/air interface. The technique is based on the acoustic modulation of naturally occurring bubbles near the sea surface. It is clear from the ideal gas law that the volume of a bubble will decrease if the pressure is increased, as long as the number of gas molecules and temperature remain constant. The pressure variations associated with the acoustic field will therefore induce proportional volume fluctuations of the insonified bubbles. The lidar return from a collection of bubbles is proportional to the total void fraction, independent of the bubble size distribution. This implies that the lidar return from a collection of insonified bubbles will be modulated at the acoustic frequencies, independent of the bubble size distribution. Moreover, that modulation is linearly related to the sound pressure. A laboratory experiment confirmed the basic principles, and estimates of signal-to-noise ratio suggest that the technique will work in the open ocean.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Citation Download Citation

James H. Churnside, Konstantin Naugolnykh, and Richard D. Marchbanks "Optical remote sensing of sound in the ocean," Journal of Applied Remote Sensing 9(1), 096038 (16 June 2015). https://doi.org/10.1117/1.JRS.9.096038

Published: 16 June 2015

ACCESS THE FULL ARTICLE

JOURNAL ARTICLE
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY