Article (Scientific journals)
AUTOMATIC RFI DETECTION, LOCATION, AND CLASSIFICATION SYSTEM IN GNSS BANDS
Perez-Portero, Adrian; QUEROL, Jorge; Camps, Adriano
2025In IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, p. 1-13
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Keywords :
Classification; Detection; GNSS; Location; RFI; Classification system; Defence applications; Detection location; Detection system; Global Navigation Satellite Systems; Interference detection; Interference Location System; Positioning navigation and timings; Radio frequency interference; Computers in Earth Sciences; Atmospheric Science
Abstract :
[en] Global Navigation Satellite Systems (GNSS) are critical infrastructure components in modern Positioning, Navigation, and Timing (PNT) services, playing a vital role in both civilian and defense applications. These systems operate in specific frequency bands that are also utilized by other Earth Observation technologies, such as GNSS-Radio Occultations and GNSS-Reflectometry. Other passive microwave remote sensing techniques such as microwave radiometers, work with very faint signals in nearby frequency bands within the L-Band. However, the increasing prevalence of Radio-Frequency Interferences (RFI) poses a significant threat, potentially compromising the integrity and reliability of PNT services, and corrupting geophysical observations. Effective RFI mitigation relies on accurate detection and classification of interference sources, a task that becomes increasingly challenging due to the complexity and diversity of RFI signals. This work presents an automated classification system for RFI detection and characterization in GNSS bands. The methodology employs advanced digital signal processing techniques and statistical algorithms to improve RFI detection and classification. RFI events are then stored in a long-term database to provide insights into the local spectrum, and to aid in mitigation and law enforcement efforts. This study provides a description of the classification system, including its architecture, implementation, and performance analysis. The results highlight the potential of this system to enhance the resilience of GNSS PNT services against RFI.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Perez-Portero, Adrian;  Universitat Politècnica de Catalunya– BarcelonaTech, CommSensLab– UPC, Spain ; Institute of Space Studies of Catalonia (IEEC), CTE-UPC, Spain
QUEROL, Jorge  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom ; Universitat Politècnica de Catalunya– BarcelonaTech, CommSensLab– UPC, Spain
Camps, Adriano;  Universitat Politècnica de Catalunya– BarcelonaTech, CommSensLab– UPC, Spain ; Institute of Space Studies of Catalonia (IEEC), CTE-UPC, Spain ; UAE University, CoE, Al-Ain, United Arab Emirates
External co-authors :
yes
Language :
English
Title :
AUTOMATIC RFI DETECTION, LOCATION, AND CLASSIFICATION SYSTEM IN GNSS BANDS
Publication date :
2025
Journal title :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
ISSN :
1939-1404
eISSN :
2151-1535
Publisher :
Institute of Electrical and Electronics Engineers Inc.
Pages :
1-13
Peer reviewed :
Peer Reviewed verified by ORBi
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