New wavelet-based features for the recognition of jittered and stagger PRI modulation types;

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2015

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Institute of Electrical and Electronics Engineers Inc.

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Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

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Abstract

In dense electronic warfare environments, numerous emitters can be active simultaneously and an interleaved stream of pulses in natural time of arrival order is received by the Electronic Support Measures (ESM) receiver. It is the task of the ESM system to de-interleave this mixed pulse sequence and thus to identify the surrounding threatening emitters. In this processing, pulse repetition interval (PRI) modulation recognition has a significant role due to the fact that it can reveal the hidden patterns inside pulse repetition intervals and thus help identify the emission source and its functional purpose. In this paper, we propose new wavelet-based features for the recognition of jittered and stagger PRI modulation types. The recognition of these types are heavily based on histogram features. Experimental results show that the proposed feature set have very high recognition rates and outperform histogram based methods. © 2015 IEEE.

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Keywords

Electronic Support Measures (ESM), Electronic Warfare (EW), Multiresolution wavelet analysis, Pulse repetition interval (PRI) modulation recognition

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1

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2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings -- 2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- Malatya -- 113052

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Start Page

2134

End Page

2137

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