Publicación: Design and Development of an SVM-Powered Underwater Acoustic Modem
Cargando...
Fecha
2024-05-05
Editor/a
Director/a
Tutor/a
Coordinador/a
Prologuista
Revisor/a
Ilustrador/a
Derechos de acceso
Atribución-NoComercial-SinDerivadas 4.0 Internacional
Título de la revista
ISSN de la revista
Título del volumen
Editor
MDPI
Resumen
Underwater acoustic communication is fraught with challenges, including signal distortion, noise, and interferences unique to aquatic environments. This study aimed to advance the field by developing a novel underwater modem system that utilizes machine learning for signal classification, enhancing the reliability and clarity of underwater transmissions. This research introduced a system architecture incorporating a Lattice Semiconductors FPGA for signal modulation and a half-pipe waveguide to emulate the underwater environment. For signal classification, support vector machines (SVMs) were leveraged with the continuous wavelet transform (CWT) employed for feature extraction from acoustic signals. Comparative analysis with traditional signal processing techniques highlighted the efficacy of the CWT in this context. The experiments and tests carried out with the system demonstrated superior performance in classifying modulated signals under simulated underwater conditions, with the SVM providing a robust classification despite the presence of noise. The use of the CWT for feature extraction significantly enhanced the model’s accuracy, eliminating the need for further dimensionality reduction. Therefore, the integration of machine learning with advanced signal processing techniques presents a promising research line for overcoming the complexities of underwater acoustic communication. The findings underscore the potential of data mining methodologies to improve signal clarity and transmission reliability in aquatic environments.
Descripción
Categorías UNESCO
Palabras clave
underwater acoustic communication, signal processing, support vector machines, continuous wavelet transform, FPGA, feature extraction, modulation techniques, noise reduction
Citación
Guerrero-Chilabert, G.S.; Moreno-Salinas, D.; Sánchez-Moreno, J. Design and Development of an SVM-Powered Underwater Acoustic Modem. J. Mar. Sci. Eng. 2024, 12,(5) 773. https://doi.org/10.3390/jmse12050773
Centro
E.T.S. de Ingeniería Informática
Departamento
Informática y Automática