Gençol, Kenan

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Profile URL
https://hdl.handle.net/20.500.14411/8132
Name Variants
K.,Gençol
K., Gencol
Gencol,K.
Gencol, Kenan
Kenan, Gencol
Gençol,K.
Kenan, Gençol
G.,Kenan
G., Kenan
K.,Gencol
Gençol, Kenan
Job Title
Araştırma Görevlisi
Email Address
Main Affiliation
Department of Electrical & Electronics Engineering
Status
Former Staff
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Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

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Scholarly Output

9

Articles

3

Views / Downloads

20/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

68

Scopus Citation Count

80

WoS h-index

2

Scopus h-index

3

Patents

0

Projects

0

WoS Citations per Publication

7.56

Scopus Citations per Publication

8.89

Open Access Source

2

Supervised Theses

0

Google Analytics Visitor Traffic

JournalCount
2013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 2013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 24 April 2013 through 26 April 2013 -- Haspolat -- 981091
2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings -- 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 -- 23 April 2014 through 25 April 2014 -- Trabzon -- 1060531
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 -- 1130521
21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUS1
22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY1
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2016 - 20173
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COAR Resource Type: text::journal::journal article

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Article
    A Wavelet-Based Feature Set for Recognizing Pulse Repetition Interval Modulation Patterns
    (2016) Gençol, Kenan; At, Nuray; Kara, Alı
    This paper presents a new feature set for the problem of recognizing pulse repetition interval (PRI) modulation patterns. The recognition is based upon the features extracted from the multiresolution decomposition of different types of PRI modulated sequences. Special emphasis is placed on the recognition of jittered and stagger type PRI sequences due to the fact that these types of PRI sequences appear predominantly in modern electronic warfare environments for some specific mission requirements and recognition of them is heavily based on histogram features. We test our method with a broad range of PRI modulation parameters. Simulation results show that the proposed feature set is highly robust and separates jittered, stagger, and other modulation patterns very well. Especially for the stagger type of PRI sequences, wavelet-based features outperform conventional histogram-based features. Advantages of the proposed feature set along with its robustness criteria are analyzed in detail.
  • Thumbnail Image
    Article
    Citation - WoS: 29
    Citation - Scopus: 35
    A Wavelet-Based Feature Set for Recognizing Pulse Repetition Interval Modulation Patterns
    (Tubitak Scientific & Technological Research Council Turkey, 2016) Gencol, Kenan; At, Nuray; Kara, Ali
    This paper presents a new feature set for the problem of recognizing pulse repetition interval (PRI) modulation patterns. The recognition is based upon the features extracted from the multiresolution decomposition of different types of PRI modulated sequences. Special emphasis is placed on the recognition of jittered and stagger type PRI sequences due to the fact that these types of PRI sequences appear predominantly in modern electronic warfare environments for some specific mission requirements and recognition of them is heavily based on histogram features. We test our method with a broad range of PRI modulation parameters. Simulation results show that the proposed feature set is highly robust and separates jittered, stagger, and other modulation patterns very well. Especially for the stagger type of PRI sequences, wavelet-based features outperform conventional histogram-based features. Advantages of the proposed feature set along with its robustness criteria are analyzed in detail.
  • Thumbnail Image
    Article
    Citation - WoS: 36
    Citation - Scopus: 38
    Improvements on Deinterleaving of Radar Pulses in Dynamically Varying Signal Environments
    (Academic Press inc Elsevier Science, 2017) Gencol, Kenan; Kara, Ali; At, Nuray
    An electronic support system receiver which is a passive receiver picks up an interleaved stream of pulses and extracts their pulse parameters. These parameters are sent to a deinterleaving subsystem which sorts them and forms pulse cells that each are assumed to belong to a specific emitter. In this paper, we develop a method for this task of deinterleaving of radar pulse sequences. For this aim, a novel pulse amplitude tracking algorithm is proposed for dynamically varying signal environments wherein radar parameters can change abruptly. This method particularly works for air-to-air engagements where pulse amplitude distortion due to channel effects can be considered negligible. Simulation results show that the proposed algorithm incorporated with a clustering algorithm improves deinterleaving of radar emitters that have agile pulse parameters such as airborne radars. (C) 2017 Elsevier Inc. All rights reserved.