High Resolution Time-Frequency Analysis Base on Ricker Atom Matching Pursuit Decomposition

2013 ◽  
Vol 284-287 ◽  
pp. 3115-3119
Author(s):  
Wei Song ◽  
Jia Hui Zuo ◽  
Peng Cheng Hu
Keyword(s):  
Frequency Analysis ◽  
Matching Pursuit ◽  
Low Frequency ◽  
Seismic Signal ◽  
Dominant Frequency ◽  
Frequency Resolution ◽  
Frequency Variation ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
The Impact

The high accuracy time-frequency representation of non-stationary signals is one of the key researches in seismic signal analysis. Low-frequency part of the seismic data often has a higher frequency resolution, on the contrary it tends to have lower frequency resolution in the high frequency part. It’s difficult to fine characterize the time-frequency variation of non-stationary seismic signals by conventional time-frequency analysis methods due to the limitation of the window function. Therefore based on the Ricker wavelet, we put forward the matching pursuit seismic trace decomposition method. It decomposes the seismic records into a series of single component atoms with different centre time, dominant frequency and energy, by making use of the Wigner-Ville distribution, has the time-frequency resolution of seismic signal reach the limiting resolution of the uncertainty principle and skillfully avoid the impact of interference terms in conventional Wigner-Ville distribution.

Time-frequency analysis of vibrotactile driving responses by matching pursuit

1998 ◽  
Vol 81 (1-2) ◽  
pp. 121-129 ◽  
Author(s):  
J. Zygierewicz ◽  
E.F. Kelly ◽  
K.J. Blinowska ◽  
P.J. Durka ◽  
S.E. Folger
Keyword(s):  
Frequency Analysis ◽  
Matching Pursuit ◽  
Time Frequency Analysis ◽  
Time Frequency

scholarly journals Application of S-Transform in ISAR Imaging

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 676 ◽  
Author(s):  
Bo Zang ◽  
Mingzhe Zhu ◽  
Xianda Zhou ◽  
Lu Zhong
Keyword(s):  
Frequency Analysis ◽  
Low Frequency ◽  
Frequency Region ◽  
Echo Signal ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
S Transform ◽  
Isar Imaging ◽  
Body Components ◽  
Over Time

In inverse synthetic aperture radar (ISAR) imaging, time-frequency analysis is the basic method for processing echo signals, which are reflected by the results of time-frequency analysis as each component changes over time. In the time-frequency map, a target’s rigid body components will appear as a series of single-frequency signals in the low-frequency region, and the micro-Doppler components generated by the target’s moving parts will be distributed in the high-frequency region with obvious frequency modulation. Among various time-frequency analysis methods, S-transform is especially suitable for analyzing these radar echo signals with micro-Doppler (m-D) components because of its multiresolution characteristics. In this paper, S-transform and the corresponding synchrosqueezing method are used to analyze the ISAR echo signal and perform imaging. Synchrosqueezing is a post-processing method for the time-frequency analysis result, which could retain most merits of S-transform while significantly improving the readability of the S-transformation result. The results of various simulations and actual data will show that S-transform is highly matched with the echo signal for ISAR imaging: the better frequency-domain resolution at low frequencies can concentrate the energy of the rigid body components in the low-frequency region, and better time resolution at high frequencies can better describe the transformation of the m-D component over time. The combination with synchrosqueezing also significantly improves the effect of time-frequency analysis and final imaging, and alleviates the shortcomings of the original S-transform. These results will be able to play a role in subsequent work like feature extraction and parameter estimation.

Time-Frequency Analysis of Pressure Fluctuations on a Hydrofoil Undergoing a Transient Pitching Motion Using Hilbert-Huang and Teager-Huang Transforms

2007 ◽  
Author(s):  
S. Benramdane ◽  
J. C. Cexus ◽  
A. O. Boudraa ◽  
J.-A. Astolfi
Keyword(s):  
Frequency Analysis ◽  
Pressure Coefficient ◽  
Pressure Fluctuations ◽  
Low Frequency ◽  
Suction Side ◽  
Intrinsic Mode Functions ◽  
Pitching Motion ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
The Hilbert Transform

In this paper, time-frequency analysis of wall pressure signals of a hydrofoil’s suction side undergoing a forced transient pitching motion with incoming flow is conducted. A novel method recently introduced by Huang et al., the Empirical Mode Decomposition (EMD), is first used to decompose resulting non-stationary signals into frequency sub-band components called Intrinsic Mode Functions (IMFs). EMD-filtered pressure coefficient signals are then reconstructed from few selected IMFs from low frequency modes and time-frequency analysis performed on high frequency modes. For this latter purpose, two analysis methods are used. The first one consists in demodulating IMFs into their Instantaneous Amplitude (IA) and Instantaneous Frequency (IF) using the Hilbert transform and the second one is based on the Teager energy tracking operator (TEO). The transition occurrence is analyzed using IA and IF of extracted IMFs from chordwise pressure transducer’s signals. This transition occurrence is then described in time-frequency domain.

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