Nguyen, YTH, McLernon, D orcid.org/0000-0002-5163-1975, Ghogho, M et al. (1 more author) (2019) Time-Frequency Distribution for Undersampled Non-stationary Signals using Chirp-based Kernel. In: 2018 5th NAFOSTED Conference on Information and Computer Science (NICS). NICS 2018: 5th NAFOSTED, 23 Nov - 24 Oct 2018, Ho Chi Minh city, Vietnam. IEEE , pp. 6-10. ISBN 978-1-5386-7983-8
Abstract
Missing samples and randomly sampled nonstationary signals give rise to artifacts that spread over both the time-frequency and the ambiguity domains. These two domains are related by a two-dimensional Fourier transform. As these artifacts resemble noise, the traditional reduced interference signal-independent kernels, which belong to Cohen’s class, cannot mitigate them efficiently. In this paper, a novel signal-independent kernel in the ambiguity domain is proposed. The proposed method is based on three important facts. Firstly, any windowed non-stationary signal can be approximated as a sum of chirps. Secondly, in the ambiguity domain, any chirp resides inside certain regions, which just occupy half of the ambiguity plane. Thirdly, the missing data artifacts always appear along the Doppler axis where the chirps auto-terms do not appear. Therefore, we propose using a chirp-based fixed kernel on windowed non-stationary signals in order to remove half of the noise-like artifacts in the ambiguity domain and compensate for the missing data effect located along the Doppler axis. It is shown that our method outperforms other reduced interference time-frequency distributions.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Reduced interference distribution; missing samples; non-stationary signal; time-frequency diforstribution; Cohen’s class; chirp-based kernel |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Oct 2018 10:12 |
Last Modified: | 28 Feb 2019 14:40 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/NICS.2018.8606839 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:136718 |