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Multi‐component instantaneous frequency estimation using locally adaptive directional time frequency distributions
Author(s) -
Khan Nabeel Ali,
Boashash Boualem
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2583
Subject(s) - instantaneous phase , smoothing , signal (programming language) , component (thermodynamics) , energy (signal processing) , algorithm , frequency domain , time–frequency analysis , least mean squares filter , computer science , signal processing , mean squared error , kernel (algebra) , mathematics , adaptive filter , statistics , telecommunications , computer vision , radar , combinatorics , thermodynamics , programming language , physics
Summary This paper presents a locally adaptive time‐frequency ( t , f ) method for estimating the instantaneous frequency (IF) of multi‐component signals. A high‐resolution adaptive directional time‐frequency distribution (ADTFD) is defined by locally adapting the direction of its smoothing kernel at each ( t , f ) point based on the direction of the energy distribution in the ( t , f ) domain. The IF of signal components is then estimated from the ADTFD using an image processing algorithm. Using the mean square error between the original IF and estimated IF as a performance criterion, experimental results indicate that the ADTFD gives better IF estimation performance compared with other TFDs for a multi‐component signal. For example, for signal‐to‐noise ratio of 12dB, the IF estimate obtained using the ADTFD achieves a mean square error of −42dB for a weak signal component, which is an improvement of −12dB compared with other TFDs. Copyright © 2015 John Wiley & Sons, Ltd.