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• W3200384356 abstract "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." @default.
• W3200384356 created "2021-09-27" @default.
• W3200384356 creator A5002488131 @default.
• W3200384356 creator A5052025135 @default.
• W3200384356 creator A5056452912 @default.
• W3200384356 date "2022-04-01" @default.
• W3200384356 modified "2023-10-16" @default.
• W3200384356 title "Radio Frequency Interference Detection Using Nonnegative Matrix Factorization" @default.
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• W3200384356 doi "https://doi.org/10.1109/taes.2021.3111730" @default.
• W3200384356 hasPublicationYear "2022" @default.
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