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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 4, 2021.
Abstract: The Autonomous Underwater Vehicles (AUVs) in-dustry is still awaiting its Henry Ford to bring to the market solutions that are well adapted to the challenge of underwater exploration. This will certainly be done by the advent of small connected drones equipped with small sensors and embedded devices, allowing AUVs to operate in a coordinated swarm, at a unit price so affordable that we can consider deploying hundreds, or even thousands simultaneously, to be able to observe the ocean with an instrument of a size finally adapted to its immensity. The scope of this work is to build a high performance and low-cost embedded device easy to mount onboard small AUVs and implementing energy-based spectrum sensing algorithms in order to detect targets underwater using acoustic waves. The principle of design, hardware architecture and real-time implementation of the acoustic signal processing chain are described in this paper. Simulations and sea experiments have been conducted successfully and qualified the performance of the realized system to detect acoustic pings underwater depending on the signal-to-noise ratio (SNR). Moreover, this paper proposes methods to improve the measured detection range and accuracy.
Redouane Es-sadaoui, Jamal Khallaayoune and Tamara Brizard, “Design and Performance Measurement of Energy-based Acoustic Signal Detection with Autonomous Underwater Vehicles” International Journal of Advanced Computer Science and Applications(IJACSA), 12(4), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120490
@article{Es-sadaoui2021,
title = {Design and Performance Measurement of Energy-based Acoustic Signal Detection with Autonomous Underwater Vehicles},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120490},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120490},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {4},
author = {Redouane Es-sadaoui and Jamal Khallaayoune and Tamara Brizard}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.