Enhanced LPI Waveform Representation by Ambiguity-Domain Elliptical Gaussian Filtering

Taylan O. Gulum; A. Yasin Erdogan; Lutfiye Durak Ata; Tulay Yildirim; Phillip E. Pace

doi:10.1109/TAES.2017.2665078

Enhanced LPI Waveform Representation by Ambiguity-Domain Elliptical Gaussian Filtering

Taylan O. Gulum, A. Yasin Erdogan, Lutfiye Durak Ata, Tulay Yildirim, Phillip E. Pace

Informatics Institute

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

ESM systems need to use sophisticated signal processing, such as time-frequency representation techniques, for the interception of nonstationary LPI radar signals. In this study, an adaptive filtering technique using an ambiguity-domain elliptical Gaussian kernel is proposed to increase the readability of pseudo-Wigner-Ville distribution based representations for LPI waveform parameter extraction purposes. The complexity and information content of the outputs obtained by the proposed method are evaluated by objective criteria, such as ratio of norms, Rényi entropy, and Jubisa measure. The results quantify efficient filtering performance under severe SNR conditions with lower computational complexity.

Original language	English
Article number	7845676
Pages (from-to)	762-777
Number of pages	16
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	53
Issue number	2
DOIs	https://doi.org/10.1109/TAES.2017.2665078
Publication status	Published - Apr 2017

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Publisher Copyright:
© 2017 IEEE.

Keywords

Electronic support measures (ESM)
Jubisa measure
Radon-ambiguity transform (RAT)
Wigner-Ville distribution
elliptical Gaussian kernel
linear frequency modulation (LFM)
ratio of norms (RoN)
rényi entropy

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10.1109/TAES.2017.2665078

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title = "Enhanced LPI Waveform Representation by Ambiguity-Domain Elliptical Gaussian Filtering",

abstract = "ESM systems need to use sophisticated signal processing, such as time-frequency representation techniques, for the interception of nonstationary LPI radar signals. In this study, an adaptive filtering technique using an ambiguity-domain elliptical Gaussian kernel is proposed to increase the readability of pseudo-Wigner-Ville distribution based representations for LPI waveform parameter extraction purposes. The complexity and information content of the outputs obtained by the proposed method are evaluated by objective criteria, such as ratio of norms, R{\'e}nyi entropy, and Jubisa measure. The results quantify efficient filtering performance under severe SNR conditions with lower computational complexity.",

keywords = "Electronic support measures (ESM), Jubisa measure, Radon-ambiguity transform (RAT), Wigner-Ville distribution, elliptical Gaussian kernel, linear frequency modulation (LFM), ratio of norms (RoN), r{\'e}nyi entropy",

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AU - Erdogan, A. Yasin

AU - Durak Ata, Lutfiye

AU - Yildirim, Tulay

AU - Pace, Phillip E.

PY - 2017/4

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AB - ESM systems need to use sophisticated signal processing, such as time-frequency representation techniques, for the interception of nonstationary LPI radar signals. In this study, an adaptive filtering technique using an ambiguity-domain elliptical Gaussian kernel is proposed to increase the readability of pseudo-Wigner-Ville distribution based representations for LPI waveform parameter extraction purposes. The complexity and information content of the outputs obtained by the proposed method are evaluated by objective criteria, such as ratio of norms, Rényi entropy, and Jubisa measure. The results quantify efficient filtering performance under severe SNR conditions with lower computational complexity.

KW - Electronic support measures (ESM)

KW - Jubisa measure

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KW - Wigner-Ville distribution

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Enhanced LPI Waveform Representation by Ambiguity-Domain Elliptical Gaussian Filtering

Abstract

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Keywords

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