2017
DOI: 10.1007/s11277-017-4710-5
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Parameter Blind Estimation of Frequency-Hopping Signal Based on Time–Frequency Diagram Modification

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Cited by 15 publications
(6 citation statements)
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“…Many methods become useless when there is not much prior information, in which case blind identification becomes especially significant. In these cases, another direction based on image processing is raised, such as extracting the parameters of Frequency-Hopping (FH) signals based on the spectrogram obtained by Short-Time Fourier Transform (STFT), in time-frequency domain (Fu et al, 2017). After the feature extraction stage, researchers deploy various methods for SS signals clustering, such as K-means, x-means algorithms and DPMM-based, Bayesian non-parametric classification.…”
Section: Related Workmentioning
confidence: 99%
“…Many methods become useless when there is not much prior information, in which case blind identification becomes especially significant. In these cases, another direction based on image processing is raised, such as extracting the parameters of Frequency-Hopping (FH) signals based on the spectrogram obtained by Short-Time Fourier Transform (STFT), in time-frequency domain (Fu et al, 2017). After the feature extraction stage, researchers deploy various methods for SS signals clustering, such as K-means, x-means algorithms and DPMM-based, Bayesian non-parametric classification.…”
Section: Related Workmentioning
confidence: 99%
“…Among the various TFA methods, the widely used ones include the short-time Fourier transform (STFT) [24], [25], [26], [27], [28], [29], the Wigner-Ville distribution (WVD) [30], [31], [32], [33], and its modified solution, known as the smooth pseudo Wigner-Ville distribution (SPWVD) [3], [34], [35], [36], [37]. However, although the WVD has the highest resolution, its sizeable cross-term interference requires numerous computationally intensive matrix operations.…”
Section: Introductionmentioning
confidence: 99%
“…Among many FH spectrum representation and parameter estimation techniques, joint time-frequency (TF) analysis [14][15][16][17], sparse linear regression [18] and compressive sensing (CS) [19] are the most representative methods. Methods suitable for traditional time-frequency analysis are short-time Fourier transform (STFT) [20,21] and Wigner-Ville distribution (WVD) [22].…”
Section: Introductionmentioning
confidence: 99%