Signal Processing - From signal processing theory to implementation
A new approach for estimation of instantaneous mean frequency of a time-varying signal
EURASIP Journal on Applied Signal Processing
Speckle suppression in SAR images using the 2-D GARCH model
IEEE Transactions on Image Processing
Robust L-estimation based forms of signal transforms and time-frequency representations
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive windowed cross Wigner-Ville distribution as an optimum phase estimator for PSK signals
Digital Signal Processing
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Studying the properties of the Wigner-Ville distribution (wvd) and its smoothed versions such as smoothed pseudo-WVD (spwvd), we demonstrate that they have significantly non-Gaussian statistics. Also, we investigate the presence of two-dimensional heteroscedasticity in them for different signals based on employing Lagrange multiplier (LM) procedure. Therefore, we employ a heteroscedastic model called two-dimensional generalized autoregressive conditional heteroscedastic (2-D garch) for statistical modeling of these distributions. This modeling captures the characteristics of WVD and SPWVD, such as heavy tailed marginal distribution, and the dependencies among them. Since the performance of WVD and its smoothed versions degrade in the presence of additive noise, we design a novel Bayesian estimator for estimating the clean distributions based on garch modeling. Also, estimating the instantaneous frequency (if) curves of signals in presence of noise based on WVD and its smoothed versions is an interesting topic in the radar domain. So, we apply the denoised distributions for estimating the if. Experimental results demonstrate the efficiency of proposed method in denoising wvd and SPWVD and also performance improvement for if estimation in utilizing the denoised distributions.