RFI analysis and mitigation in airborne GNSS-R campaign

January 1, 2018·
Jorge Querol
,
R. Onrubia
,
D. Pascual
,
J. Castellvi-Esturi
,
H. Park
,
A. Camps
· 1 min read
DOI
Abstract
Radio-Frequency Interference (RFI) is one of the most concerning topics in Global Navigation Satellite Systems (GNSS) and GNSS - Reflectometry (GNSS-R) because any undesired signal present at the antenna can corrupt the received signal and the eventual geophysical measurements. The purpose of this paper is two-fold. First, an RFI analysis is performed to the raw data obtained from an airborne dual-band GNSS reflectometer. Finally, the Front-End GNSS Interference eXcisor (FENIX) mitigation algorithm is applied to the raw data, and then the Signal-to-Noise Ratio (SNR) improvement at the Delay-Doppler Map (DDM) is obtained. From the analysis of one of the datasets, two RFI signals were detected and characterized. Moreover, FENIX output signal was revealed to be much cleaner than before. The mean SNR improvement with coherent DDMs of 1 ms is 0.72 dB, whereas the SNR improvement increases to 1.49 dB when considering 50 incoherent averages. This improvement represents a reduction in the geophysical parameter estimation uncertainty.
Type
Publication
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium
publication

Abstract & Overview

Radio-Frequency Interference (RFI) is one of the most concerning topics in Global Navigation Satellite Systems (GNSS) and GNSS - Reflectometry (GNSS-R) because any undesired signal present at the antenna can corrupt the received signal and the eventual geophysical measurements. The purpose of this paper is two-fold. First, an RFI analysis is performed to the raw data obtained from an airborne dual-band GNSS reflectometer. Finally, the Front-End GNSS Interference eXcisor (FENIX) mitigation algorithm is applied to the raw data, and then the Signal-to-Noise Ratio (SNR) improvement at the Delay-Doppler Map (DDM) is obtained. From the analysis of one of the datasets, two RFI signals were detected and characterized. Moreover, FENIX output signal was revealed to be much cleaner than before. The mean SNR improvement with coherent DDMs of 1 ms is 0.72 dB, whereas the SNR improvement increases to 1.49 dB when considering 50 incoherent averages. This improvement represents a reduction in the geophysical parameter estimation uncertainty.

Publication Metadata

  • Authors: Jorge Querol, R. Onrubia, D. Pascual, J. Castellvi-Esturi, H. Park, A. Camps
  • Venue: IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (2018)
  • Research Areas: JCAS & Earth Observation, RFI Mitigation & GNSS Security, GNSS & Positioning, AI & Neuromorphic SatCom
  • DOI: 10.1109/igarss.2018.8518827
JCAS & Earth Observation RFI Mitigation & GNSS Security GNSS & Positioning AI & Neuromorphic SatCom