Radio Frequency Interference Detection Using Nonnegative Matrix Factorization

This article proposes a new precorrelation interference detection technique based on the nonnegative matrix factorization (NMF) for global navigation satellite system (GNSS) signals. The proposed technique uses the NMF to extract the time and frequency properties of the received signal from its spec...

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Bibliographic Details
Published in:IEEE transactions on aerospace and electronic systems 2022-04, Vol.58 (2), p.868-878
Main Authors: da Silva, Felipe B., Cetin, Ediz, Martins, Wallace A.
Format: Article
Language:English
Subjects:
Chirp
Factorization
False alarms
Global navigation satellite system
Global navigation satellite systems (GNSSs)
Interference
interference detection
Jamming
jamming detection
Noise
nonnegative matrix factorization (NMF)
Radio frequency
Radio frequency interference
Similarity
Spectra
Spectral shape
Spectrogram
Time-frequency analysis
time–frequency (TF) analysis
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Summary:This article proposes a new precorrelation interference detection technique based on the nonnegative matrix factorization (NMF) for global navigation satellite system (GNSS) signals. The proposed technique uses the NMF to extract the time and frequency properties of the received signal from its spectrogram. The estimated spectral shape is then compared with the spectrogram’s time slices by means of a similarity function to detect the presence of radio frequency interference (RFI). In the presence of RFI, the NMF estimated spectral shape tends to be well-defined, resulting in high similarity levels. In contrast, in the absence of RFI, the received signal is solely comprised of noise and GNSS signals resulting in a noise like spectral shape estimate, leading to considerably reduced similarity levels. The proposal exploits these different similarity levels to detect the presence of interference. Simulation results indicate that the proposed technique yields increased detection capability with low false alarm rate even in low jammer-to-noise ratio environments for both narrow and wideband interference sources without requiring fine tuning of parameters for specific RFI types. In addition, the proposal has reduced computational complexity, when compared with an existing statistical-based detector.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2021.3111730