Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator

This is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for signal-type identification based on front-end hardw...

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Main Authors: Ruben Morales Ferre, Wenbo Wang, Alejandro Sanz Abia, Elena Simona Lohan
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Data
Subjects:
Online Access:https://www.mdpi.com/2306-5729/5/1/18
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spelling doaj-92952d170a184a4484c8b0cdaf8ff75e2020-11-25T02:32:13ZengMDPI AGData2306-57292020-02-01511810.3390/data5010018data5010018Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom GeneratorRuben Morales Ferre0Wenbo Wang1Alejandro Sanz Abia2Elena Simona Lohan3ITC Faculty, Department of Electrical Engineering, Tampere University, 33720 Tampere, FinlandITC Faculty, Department of Electrical Engineering, Tampere University, 33720 Tampere, FinlandITC Faculty, Department of Electrical Engineering, Tampere University, 33720 Tampere, FinlandITC Faculty, Department of Electrical Engineering, Tampere University, 33720 Tampere, FinlandThis is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for signal-type identification based on front-end hardware characteristics at transmitter or receiver side. Examples are given in this paper of achievable classification accuracy of six of the collected signal classes. The RFF is one of the state-of-the-art, promising methods to identify GNSS transmitters and receivers, and can find future applicability in anti-spoofing and anti-jamming solutions for example. The uses of the provided raw data are not limited to RFF studies, but can extend to uses such as testing GNSS acquisition and tracking, antenna array experiments, and so forth.https://www.mdpi.com/2306-5729/5/1/18global navigation satellite systems (gnss)radio frequency fingerprinting (rf fp)spectracomroof antennagalileoglobal positioning systems (gps)machine learning
collection DOAJ
language English
format Article
sources DOAJ
author Ruben Morales Ferre
Wenbo Wang
Alejandro Sanz Abia
Elena Simona Lohan
spellingShingle Ruben Morales Ferre
Wenbo Wang
Alejandro Sanz Abia
Elena Simona Lohan
Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
Data
global navigation satellite systems (gnss)
radio frequency fingerprinting (rf fp)
spectracom
roof antenna
galileo
global positioning systems (gps)
machine learning
author_facet Ruben Morales Ferre
Wenbo Wang
Alejandro Sanz Abia
Elena Simona Lohan
author_sort Ruben Morales Ferre
title Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
title_short Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
title_full Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
title_fullStr Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
title_full_unstemmed Identifying GNSS Signals Based on their Radio Frequency (RF) Features—A Dataset with GNSS Raw Signals Based on Roof Antennas and Spectracom Generator
title_sort identifying gnss signals based on their radio frequency (rf) features—a dataset with gnss raw signals based on roof antennas and spectracom generator
publisher MDPI AG
series Data
issn 2306-5729
publishDate 2020-02-01
description This is a data descriptor paper for a set of raw GNSS signals collected via roof antennas and Spectracom simulator for general-purpose uses. We give one example of possible data use in the context of Radio Frequency Fingerprinting (RFF) studies for signal-type identification based on front-end hardware characteristics at transmitter or receiver side. Examples are given in this paper of achievable classification accuracy of six of the collected signal classes. The RFF is one of the state-of-the-art, promising methods to identify GNSS transmitters and receivers, and can find future applicability in anti-spoofing and anti-jamming solutions for example. The uses of the provided raw data are not limited to RFF studies, but can extend to uses such as testing GNSS acquisition and tracking, antenna array experiments, and so forth.
topic global navigation satellite systems (gnss)
radio frequency fingerprinting (rf fp)
spectracom
roof antenna
galileo
global positioning systems (gps)
machine learning
url https://www.mdpi.com/2306-5729/5/1/18
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