Kara, Ali

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Kara, Ali

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Kara, A
Kara, A.
Kara,A.
Ali, Kara
Kara, Ali
K., Ali
A.,Kara
A., Kara
K.,Ali

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Profesör Doktor

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ali.kara@atilim.edu.tr

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Scholarly Output

165

Articles

73

Citation Count

657

Supervised Theses

33 Scholarly Output Search Results

Now showing 1 - 10 of 164

Citation Count: 31
Variational Mode Decomposition-Based Threat Classification for Fiber Optic Distributed Acoustic Sensing
(Ieee-inst Electrical Electronics Engineers inc, 2020) Dalveren, Yaser; Kara, Ali; Aghnaiya, Alghannai; Kara, Ali; Department of Electrical & Electronics Engineering
In this study, a novel method is proposed to detect and classify the threats for fiber optic distributed acoustic sensing (DAS) systems. In the study, phase-sensitive optical time-domain reflectometry (phase-OTDR) is realized for the sensing system. The proposed method is consisted of three main stages. In the first stage, Wavelet denoising method is applied for noise reduction in the measured signal, and difference in time domain approach is used to perform high-pass filtering. Autocorrelation is then used for comparing the signal with itself over time in each bin to remove uncorrelated signals. Next, the power of the correlated signals at each bin is calculated and sorted where maximum valued bins are considered as the event signal. In the second stage, Variational Mode Decomposition (VMD) technique is used to decompose the detected event signals into a series of band-limited modes from which the event signals are reconstructed. From the reconstructed event signals, higher order statistical (HOS) features including variance, skewness, and kurtosis are extracted. In the last stage, the threats are discriminated by implementing Linear Support Vector Machine (LSVM)-based classification approach to the extracted features. In order to evaluate the effects of proposed method on the classification performance, different types of activities such as digging with hammer, pickaxe, and shovel collected from various points of a buried fiber optic cable have been used under different Signal-to-Noise Ratio (SNR) levels (& x2212;4 to & x2212;18 dB). It has observed that the classification accuracy at high/moderate (& x2212;4 to & x2212;8 dB) and low (& x2212;8 to & x2212;18 dB) SNR levels are 79.5 & x0025; and 75.2 & x0025;, respectively. To the best of authors & x2019; knowledge, this research study is the first report to use VMD technique for threat classification in phase-OTDR-based DAS systems.
Citation Count: 0
A study for development of propagation model based on ray tracing for coverage prediction in terrestrial broadcasting systems;
(2009) Kara, Ali; Özmen,A.; Özmen, Ayten; Department of Electrical & Electronics Engineering; Department of Basic English (Prep School)
In this work, improvements on propagation prediction models based on ray tracing in coverage estimation for digital broadcasting systems are presented. For this purpose, firstly, propagation models based on Geometrical Theory of Diffraction (GTD) are discussed, and then an improved model is proposed for prediction of propagation path loss or electric field strength at the receiver. The proposed model incorporates first order expansion of classical GTD in field computation and convex hull for ray tracing. Simulation results are presented for comparison of various models in terms of computation time and accuracy. ©2009 IEEE.
Citation Count: 22
Variational Mode Decomposition-Based Radio Frequency Fingerprinting of Bluetooth Devices
(Ieee-inst Electrical Electronics Engineers inc, 2019) Kara, Ali; Ali, Aysha M.; Kara, Ali; Department of Electrical & Electronics Engineering
Radio frequency fingerprinting (RFF) is based on identification of unique features of RF transient signals emitted by radio devices. RF transient signals of radio devices are short in duration, non-stationary and nonlinear time series. This paper evaluates the performance of RF fingerprinting method based on variational mode decomposition (VMD). For this purpose, VMD is used to decompose Bluetooth (BT) transient signals into a series of band-limited modes, and then, the transient signal is reconstructed from the modes. Higher order statistical (HOS) features are extracted from the complex form of reconstructed transients. Then, Linear Support Vector Machine (LVM) classifier is used to identify BT devices. The method has been tested experimentally with BT devices of different brands, models and series. The classification performance shows that VMD based RF fingerprinting method achieves better performance (at least 8% higher) than time-frequency-energy (TFED) distribution based methods such as Hilbert-Huang Transform. This is demonstrated with the same dataset but with smaller number of features (nine features) and slightly lower (2-3 dB) SNR levels.
Citation Count: 1
Characterization of satellite transponder impairments based on simulations with test data
(Institute of Electrical and Electronics Engineers Inc., 2015) Kara, Ali; Gulgonul,S.; Kara,A.; Department of Electrical & Electronics Engineering
A satellite transponder simulator based on actual test data of TURKSAT 3A satellite has been developed to analyze degradation in multicarrier scenarios. Communication impairment sources through a transponder are explained in conjunction with a methodology defined to characterize total degradation resulting from them. Several transponder utilization scenarios are studied with respect to total degradation and optimum operation conditions are demonstrated. © 2015 IEEE.
A WEB BASED TRAINING MODULE FOR TEACHING DIGITAL COMMUNICATIONS
(2015) Kara, Ali; Erdem, Cihangir; Department of Electrical & Electronics Engineering; Çağıltay, Nergiz; Aydın, Elif
An interactive module which simulates a digital transmission link from one end to the other has been designed. Using the module, a user may enter a short audio/message signal using microphone of a PC, and then follows processes on the signal at each stage of the digital transmission link. The user can also analyze the signal at every stage of the link, and compare the performance of various modulation schemes used in the link, and finally may see how the audio signal is corrupted by noise in the transmission link. In this way, from source point to destination point of the signal, the user may study various stages such as analog to digital conversion, analysis of effects of Gaussian noise on the message signal.
Endüstriyel ortamlarda bina içi radyo yayılımı çalışmaları
(2016) Kara, Ali; Kara, Ali; Department of Electrical & Electronics Engineering
Bu tez çalışması Sincan 1. Organize Sanayi Bölgesi ve OSTIM sanayi bölgesinde bulunan endüstriyel ortamlarda yapılan yol kaybı ve geçici sönümleme ölçümlerinin sonuçlarını içermektedir. Dokuz farklı fabrika kanalında yapılan bu deneyler, 315 MHz, 434 MHz, 868 MHz, 915 MHz ve 2400 MHz bantlarında gerçekleştirilmiştir. Yol kaybı ölçümleri yapılırken farklı anten yüksekliklerinin etkisi de dikkate alınmıştır. Ayrıca, açık ve kapalı görüş linkleri üzerinde yapılan geçici sönümleme ölçümleri de bu çalışmada verilmiştir. Yapılan bu çalışmanın amacı farklı fabrika ortamlarının sinyal yayılım davranışları üzerindeki etkilerini incelemektir. Bu çalışma özellikle fabrika içlerinde kullanılan kablosuz sistemlerin etkili kullanımına yardımcı olacaktır.
Citation Count: 26
A Database for the Radio Frequency Fingerprinting of Bluetooth Devices
(Mdpi, 2020) Uzundurukan, Emre; Dalveren, Yaser; Kara, Ali; Department of Electrical & Electronics Engineering; Airframe and Powerplant Maintenance
Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices.
Citation Count: 0
A remote laboratory for training in radio communications
(Ieee, 2007) Kara, Ali; Çağıltay, Nergiz; Oektem, Rusen; Cagiltay, Nergiz; Department of Electrical & Electronics Engineering; Software Engineering
This paper presents, first, a short survey of remote laboratory initiatives in electrical and computer engineering, and then discusses design and development phases of remote laboratory environment on radio communications, the ERRL (European Remote Radio Laboratory). As being the first. attempt in establishing of such a large scale remote laboratory on radio communications, ERRL enables access to high technology RF equipments and setups through the Internet. The software structure, target groups and experimental set ups of ERRL are shortly discussed. First attempts on implementation of pilot experiments are discussed.
Advancing Mmwave Altimetry for Unmanned Aerial Systems: a Signal Processing Framework for Optimized Waveform Design
(Mdpi, 2024) Dalveren, Yaser; Kara, Ali; Kara, Ali; Derawi, Mohammad; Department of Electrical & Electronics Engineering
This research advances millimeter-wave (mmWave) altimetry for unmanned aerial systems (UASs) by optimizing performance metrics within the constraints of inexpensive automotive radars. Leveraging the software-defined architecture, this study encompasses the intricacies of frequency modulated continuous waveform (FMCW) design for three distinct stages of UAS flight: cruise, landing approach, and touchdown within a signal processing framework. Angle of arrival (AoA) estimation, traditionally employed in terrain mapping applications, is largely unexplored for UAS radar altimeters (RAs). Time-division multiplexing multiple input-multiple output (TDM-MIMO) is an efficient method for enhancing angular resolution without compromising the size, weight, and power (SWaP) characteristics. Accordingly, this work argues the potential of AoA estimation using TDM-MIMO to augment situational awareness in challenging landing scenarios. To this end, two corner cases comprising landing a small-sized drone on a platform in the middle of a water body are included. Likewise, for the touchdown stage, an improvised rendition of zoom fast Fourier transform (ZFFT) is investigated to achieve millimeter (mm)-level range accuracy. Aptly, it is proposed that a mm-level accurate RA may be exploited as a software redundancy for the critical weight-on-wheels (WoW) system in fixed-wing commercial UASs. Each stage is simulated as a radar scenario using the specifications of automotive radar operating in the 77-81 GHz band to optimize waveform design, setting the stage for field verification. This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. This study appraises popular CFAR variants to achieve optimized ground detection performance. The authors advocate for dedicated minimum operational performance standards (MOPS) for UAS RAs. Lastly, this body of work identifies potential challenges, proposes solutions, and outlines future research directions.
Citation Count: 4
On the Performance of Energy Criterion Method in Wi-Fi Transient Signal Detection
(Mdpi, 2022) Dalveren, Yaser; Kara, Ali; Catak, Ferhat Ozgur; Kara, Ali; Department of Electrical & Electronics Engineering
In the development of radiofrequency fingerprinting (RFF), one of the major challenges is to extract subtle and robust features from transmitted signals of wireless devices to be used in accurate identification of possible threats to the wireless network. To overcome this challenge, the use of the transient region of the transmitted signals could be one of the best options. For an efficient transient-based RFF, it is also necessary to accurately and precisely estimate the transient region of the signal. Here, the most important difficulty can be attributed to the detection of the transient starting point. Thus, several methods have been developed to detect transient start in the literature. Among them, the energy criterion method based on the instantaneous amplitude characteristics (EC-a) was shown to be superior in a recent study. The study reported the performance of the EC- a method for a set of Wi-Fi signals captured from a particular Wi-Fi device brand. However, since the transient pattern varies according to the type of wireless device, the device diversity needs to be increased to achieve more reliable results. Therefore, this study is aimed at assessing the efficiency of the EC-a method across a large set ofWi-Fi signals captured from variousWi-Fi devices for the first time. To this end, Wi-Fi signals are first captured from smartphones of five brands, for a wide range of signalto-noise ratio (SNR) values defined as low (3 to 5 dB), medium (5 to 15 dB), and high (15 to 30 dB). Then, the performance of the EC-a method and well-known methods was comparatively assessed, and the efficiency of the EC-a method was verified in terms of detection accuracy.

Kara, Ali

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Scholarly Output

165

Articles

73

Citation Count

657

Supervised Theses

33

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