Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution

Daniel L. Stevens; Stephanie A. Schuckers

Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution

Daniel L. Stevens * § Ph.D., B.S. in Electrical Engineering, M.S. in Physics

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Stephanie A. Schuckers

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§ Clarkson University Potsdam

Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution

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Abstract

Low probability of intercept radar signals, which are often challenging to detect and characterize, have as their objective ‘to see and not be seen’. Digital intercept receivers are currently moving from Fourier-based techniques to classical time-frequency techniques for the analysis of low probability of intercept radar signals. This paper presents the novel approach of characterizing low probability of intercept frequency hopping radar signals through utilization and direct comparison of the Wigner Ville Distribuion versus the Choi Williams Distribution. Two different frequency hopping low probability of intercept radar signals were analyzed (4-component and 8-component). The following metrics were used for evaluation: percent error of: carrier frequency, modulation bandwidth, modulation period, and time-frequency localization. Also used were: percent detection, lowest signaltonoise ratio for signal detection, and plot (processing) time.

References

14 Cites in Article

Reference Format

D Adamy (2004). EW 102: A Second Course in Electronic Warfare.
L Anjaneyulu,N Sarma,N Murthy (2009). Identification of LPI radar signals by higher order spectra and neural network techniques.
L Anjaneyulu,N Murthy,N Sarma (2009). A Novel Method for Recognition of Modulation Code of LPI Radar Signals.
F Auger,P Flandrin,P Goncalves,O Lemoine (1996). Time-Frequency Toolbox Users Manual.
Boualem Boashash (2003). Preface to the First Edition.
H-I Choi,W Williams (1989). Improved time-frequency representation of multicomponent signals using exponential kernels.
T Gulum (2007). Autonomous Non-Linear Classifications of LPI Radar Signal Modulations.
T Gulum,P Pace,R Cristi (2008). Extraction of Polyphase Radar Modulation Parameters Using a Wigner-Ville Distribution-Radon Transform.
S Han,H Hong,D Seo,J Choi (2000). Target Position Extraction Based on Instantaneous Frequency Estimation in a Fixed-Reticle Seeker.
F Hlawatsch,G Boudreaux-Bartels (1992). Linear and Quadratic Time-Frequency Signal Representations.
X Li,G Bi (2008). A New Reassigned Time-Frequency Representation.
Y Li,X Xiao (2003). Recursive Filtering Radon-Ambiguity Transform Algorithm for Detecting Multi-LFM Signals.
P Milne,P Pace (2002). Wigner distribution detection and analysis of FMCW and P-4 polyphase LPI waveforms.
A Ozdemir (2003). Time-Frequency Component Analyzer.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Daniel L. Stevens, Stephanie A. Schuckers. 2018. "Low Probability of Intercept Frequency Hopping Signal Characterization Comparison Using the Wigner Ville Distribution and the Choi Williams Distribution". Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 18 (GJRE Volume 18 Issue F2).

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GJRE Volume 18 Issue F2

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-F Classification FOR Code: 280204

Submission ReceivedDecember 6, 2017
Peer Review Double Blind
Handling Editor
Accepted January 5, 2018
Published January 15, 2018

Version of record

v1.2

Issue date

April 24, 2018

Language

English

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Article Matrices

Total Score: 102

Country: Unknown

Subject: Global Journal of Research in Engineering

Authors: Daniel L. Stevens, Stephanie A. Schuckers (PhD/Dr. count: 0)

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