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Optical underwater distance estimation

Mathias Pelka, Martin Mackenberg, Christian Funda, Horst Hellbruck

Abstract

Data communication with high data rate and precise underwater positioning with an accuracy of several centimeters is an unsolved problem. Precise positioning is important for autonomous vehicles. State-of-the-art acoustic communication and distance estimation faces difficulties underwater, e.g. multipath fading or variation of propagation speed. In this work, we propose optical distance estimation, which is the basis for positioning in future work. We combine the Beer-Lambert law and the inverse-square-law to model the underwater channel of the medium. We investigate different wavelengths and employ curve fitting based on the Levenberg-Marquardt algorithm to determine the unknown coefficients of the model, e.g. absorption. Our evaluation shows promising results and distance estimation of up to 25 m in pool water is possible. In stream water we determined a mean error for the optical distance estimation of up to 0.02 m with a wavelength of 470 nm.

Original languageEnglish
Title of host publicationOCEANS 2017 - Aberdeen
Number of pages6
Volume2017-October
PublisherIEEE
Publication date25.10.2017
Pages1-6
ISBN (Print)978-1-5090-5279-0, 978-1-5386-2111-0
ISBN (Electronic)978-1-5090-5278-3
DOIs
Publication statusPublished - 25.10.2017
EventOCEANS 2017 - Aberdeen, United Kingdom
Duration: 19.06.201722.06.2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  4. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

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