An Efficient Algorithm for Instantaneous Frequency Estimation of Nonstationary Multicomponent Signals in Low SNR

A method for components instantaneous frequency (IF) estimation of multicomponent signals in low signal-to-noise ratio (SNR) is proposed. The method combines a new proposed modification of a blind source separation (BSS) algorithm for components separation, with the improved adaptive IF estimation procedure based on the modified sliding pairwise intersection of confidence intervals (ICI) rule. The obtained results are compared to the multicomponent signal ICI-based IF estimation method for various window types and SNRs, showing the estimation accuracy improvement in terms of the mean squared error (MSE) by up to 23%. Furthermore, the highest improvement is achieved for low SNRs values, when many of the existing methods fail.

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Authors and Affiliations

1. Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000, Rijeka, Croatia

   Jonatan Lerga & Victor Sucic (EURASIP Member)

2. College of Engineering, Qatar University, P.O. Box 2713, Doha, Qatar

   Boualem Boashash

3. UQ Centre for Clinical Research, The University of Queensland, Brisbane, QLD, 4072, Australia

   Boualem Boashash

Corresponding author

Correspondence to Victor Sucic (EURASIP Member).

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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