Name
Abstract | ||
|---|---|---|
An adaptive time-frequency representation (TFR) with higher energy concentration usually requires higher complexity. Recently, a low-complexity adaptive short-time Fourier transform (ASTFT) based on the chirp rate has been proposed. To enhance the performance, this method is substantially modified in this paper: i) because the wavelet transform used for instantaneous frequency (IF) estimation is not signal-dependent, a low-complexity ASTFT based on a novel concentration measure is addressed; ii) in order to increase robustness to IF estimation error, the principal component analysis (PCA) replaces the difference operator for calculating the chirp rate; and iii) a more robust Gaussian kernel with time-frequency-varying window width is proposed. Simulation results show that our method has higher energy concentration than the other ASTFTs, especially for multicomponent signals and nonlinear FM signals. Also, for IF estimation, our method is superior to many other adaptive TFRs in low signal-to-noise ratio (SNR) environments. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TSP.2012.2197204 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
concentration measure,robustness,nonlinear fm signal,frequency estimation,wavelet transforms,fourier transforms,adaptive tfr,adaptive time-frequency analysis,energy concentration,chirp rate estimation,multicomponent signal,chirp rate,adaptive window width,time frequency varying window width,low signal-to-noise ratio environment,chirp modulation,robust gaussian kernel,difference operator,low complexity adaptive time-frequency representation,if estimation error,wavelet transform,instantaneous frequency estimation,time-frequency reassignment,principal component analysis,ridge detection,adaptive short time fourier transform,chirp,time frequency representation,signal to noise ratio,kernel,time frequency,instantaneous frequency,short time fourier transform,time frequency analysis,gaussian kernel,estimation | Control theory,Signal-to-noise ratio,Short-time Fourier transform,Fourier transform,Time–frequency analysis,Chirp,Instantaneous phase,Gaussian function,Mathematics,Wavelet transform | Journal |
Volume | Issue | ISSN |
abs/1705.08795 | 8 | IEEE Transactions on Signal Processing, Volume: 60, Issue: 8, Aug.
2012 |
Citations | PageRank | References |
13 | 0.57 | 22 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soo-Chang Pei | 1 | 449 | 46.82 |
| Shih-Gu Huang | 2 | 43 | 6.44 |