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- W4306386481 abstract "In this paper, a transfer learning-based global navigation satellite system (GNSS) jamming classification scheme using overlapped images of the smoothed pseudo-Wigner-Ville distribution (SPWVD) and power spectral density (PSD) is proposed. Five types of jamming are considered: amplitude modulation jamming (continuous wave interference), linear chirp jamming, frequency modulation jamming, narrow-band noise jamming, and distance measurement equipment jamming (pulse jamming). The performance of the proposed scheme is shown to be the F1 score and the confusion matrix for pre-mentioned 5 jamming types with no jamming case. A representative conventional transfer learning-based GNSS jamming classification scheme uses a concatenated image comprising a spectrogram, in-phase and quadrature constellation, PSD, and histogram. However, in conventional schemes, the spectrogram" @default.
- W4306386481 created "2022-10-17" @default.
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- W4306386481 date "2022-10-31" @default.
- W4306386481 modified "2023-09-26" @default.
- W4306386481 title "Transfer Learning-based GNSS Jamming Classification Scheme Using Overlapped SPWVD-PSD Images" @default.
- W4306386481 doi "https://doi.org/10.5302/j.icros.2022.22.0135" @default.
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