Jammer Classification in GNSS Bands Via Machine Learning Algorithms

Jammer Classification in GNSS Bands Via Machine Learning Algorithms

This paper proposes to treat the jammer classification problem in the Global Navigation Satellite System bands as a black-and-white image classification problem, based on a time-frequency analysis and image mapping of a jammed signal. The paper also proposes to apply machine learning approaches in o...

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Bibliographic Details
Main Authors: Ruben Morales Ferre, Alberto de la Fuente, Elena Simona Lohan
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Sensors
Subjects:
jamming
global navigation satellite systems (gnss)
classification
image processing
deep learning
convolutional neural networks (cnn)
support vector machines (svn)
Online Access:https://www.mdpi.com/1424-8220/19/22/4841

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