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Harmonik radar, doğrusal olmayan karakteristikler barındıran ve genellikle insan yapımı cisimleri tespit etmek için kullanılan, son yıllarda üzerine çok sayıda araştırma yapılmış, elektromanyetik yayılım yapan bir algılayıcıdır. Bu tezde ilk olarak geleneksel radar sistemlerinden farklı bir tespit mekanizmasına sahip olan harmonik radar sistemi kullanılarak yeni bir devre sınıflandırma yöntemi geliştirilmiştir. Elektronik devrelerin harmonik frekanslardaki geri yayılım özellikleri harmonik radar benzetimi ile kaydedilmiş ve devrelere ait harmonik güç eğrileri elde edilmiştir. Önerilen yöntem ile test edilen elektronik devrelerin (TEED) özellik alanı oluşturulup analiz edilmiş ve gerçekçi bir benzetim modeliyle doğrulanmıştır. TEED'lerin harmonik tepkisi, birden fazla çıkış düğümünün üst üste bindirilmesiyle elde edilmiştir. Toplanan veriler ile çarpıklık, basıklık ve varyans gibi devrelere özel istatistiksel özellikler hesaplanmış ve K-En Yakın Komşular (kNN) algoritması kullanılarak sınıflandırma işlemi gerçekleştirilmiştir. Tezin ikinci kısmında, çoklu faz, doğrusal frekans modülasyonlu (LFM) dalga formları ile darbe sıkıştırma ve darbe entegrasyonu gibi çeşitli algoritmalar kullanan bir harmonik radar benzetim aracı geliştirilmiştir. Bu benzetim aracı ile harmonik radar sistemlerinin avantajları ve dezavantajları görünür hale getirilerek, radar tasarımında kullanılan parametrelerin etkileri gözlenmiştir. Tezin son kısmında, harmonik radar uygulamalarında kullanılabilecek radyo frekansı (RF) etiket devreleri için karakterizasyon sistemleri geliştirilmiştir. Bu düzenekler ile elektronik devrelerin çeşitli radar dalga formlarına etkileri incelenmiştir. Radar dalga formlarındaki bozulmaların radar tespit performansına etkileri incelenerek, bu etkileri azaltacak yöntemler önerilmiştir. Elde edilen veriler ile farklı RF etiketlerin farklı dalga formları ile daha uyumlu çalıştığı gösterilmiştir., Harmonic radar is an electromagnetic propagating sensor on which a lot of research has been conducted in recent years, is usually used to detect man-made objects that has nonlinear characteristics. In this thesis, first a new circuit classification method is developed using the harmonic radar system, which has a different detection mechanism than traditional radar systems. The back propagation properties of electronic circuits at harmonic frequencies have been recorded with harmonic radar simulations and harmonic power curves of the circuits has been obtained. Feature space of the electronic circuits under test (ECUT) has been created and analysed with the proposed method then verified with a realistic simulation model. The harmonic response of the ECUTs has been achieved by superimposing multiple output nodes. With the collected data, statistical properties specific to circuits such as skewness, kurtosis and variance were calculated and classification was performed using the K-Nearest Neighbors (kNN) algorithm. In the second part of the thesis, a harmonic radar simulation tool that uses phase coded and linear frequency modulated (LFM) waveforms has been developed. It can also apply various radar algorithms such as pulse compression and pulse integration. With this simulation tool, the advantages and disadvantages of harmonic radar systems have been made visible, and the effects of the parameters used in radar design have been made observable. In the last part of the thesis, a characterization system has been developed for RF (Radio Frequency) electronic tag circuits that can be used during harmonic radar operation. Using this system, the effects of some electronic circuits on various radar waveforms have been studied. By examining the effects of distortions in radar waveforms on radar detection performance, methods to reduce these performance defects have been proposed. With the results obtained, it has been shown that different RF tags work more compatible with di

Günümüzde elektronik cihazların büyük çoğunluğu, diyot, transistör, yarıiletkenler vb. doğrusal olmayan devre elemanları içerir. Doğrusal olmayan bu devreler, iletilen temel frekansın harmoniklerinde geri-ışımaya neden olurlar. Bu sayede bu devrelerin Radyo Frekansı (RF) yayını ile tespiti ve sınıflandırılmasında harmonik radar kullanılmaktadır. Literatürde yapılan çalışmaların çok büyük bir çoğunluğu, elektronik cihazların tespiti, menzil tayini ve takibine dayanırken, sınırlı sayıda çalışma, cihazların harmonik radar ile ayrıştırılması ve sınıflandırılmasına odaklanmıştır. Bu tezde, doğrusal olmayan yapıdaki elektronik devrelerden geri-ışıyan sinyaller analiz edilerek, bu devrelerin tespiti ve sınıflandırılmasına yönelik özgün metotlar geliştirilmiştir. Bu tez kapsamında, ilk olarak, Frekans Süpürmeli Harmonik Radar (FSHR) yaklaşımı ile elektronik devreleri sınıflandıran özgün bir yöntem sunulmaktadır. Literatürde bulunan çalışmalardan farklı olarak elektronik devrelere sabit güce sahip frekans süpürmeli bir sinyal gönderilmektedir. FSHR yaklaşımı sayesinde farklı tipteki elektronik devreler, farklı harmonik yanıtlar sergilerken, aynı türdeki devreler, benzer harmonik davranışlar göstermektedir. Elektronik devrelerin sınıflandırılmasında harmonik tepkilerden elde edilen istatiksel ve Fourier öznitelikler kullanılmaktadır. Sınıflandırma performansı hem harmonik hem de öznitelik uzaylarında ifade edilmektedir. Harmonik uzay, ilk üç harmonikten oluşan üç boyutlu uzay olarak tanımlanmaktadır. Üç boyutlu öznitelik uzay ise istatiksel ve Fourier parametrelerinden oluşmaktadır. Ek olarak, gürültü varlığındaki harmonik tepkiler kullanılarak Monte Carlo benzetimleri ile FSHR yaklaşımının sınıflandırma performansı değerlendirilmektedir. İlk çalışmanın devamı olarak ikinci çalışmada, elektronik devrelerin sınıflandırılmasında yeni öznitelik kümeleri kullanılmaktadır. Elektronik devrelere, sabit güçte frekans süpürmeli sinyaller iletilerek devrelerin doğrusal olmayan cevaplar, Nowadays, the vast majority of electronic devices contain non-linear circuit elements such as diodes, transistors, semiconductors, etc. These nonlinear circuits cause re-radiation at the harmonics of the transmitted frequency. Thus, harmonic radar is used in the detection and classification of these circuits by Radio Frequency (RF) broadcasting. While the majority of the studies in the literature are based on detection, ranging, and tracking of electronic devices, a limited number of studies have focused on distinguishing and classification of electronic devices with harmonic radar. In this thesis, re-radiated signals from nonlinear electronic circuits were analyzed and unique methods were developed for the detection and classification of these circuits. In this thesis, firstly, a novel method for classifying electronic circuits with a Frequency-Sweep Harmonic Radar (FSHR) approach is presented. Unlike studies in the literature, a frequency-swept signal with a constant power is transmitted to the electronic circuits. Different types of electronic circuits exhibit different harmonic responses, while the same type of circuits show similar harmonic behavior via FSHR approach. Statistical and Fourier features obtained from harmonic responses are utilized to classify electronic circuits. Classification performance is expressed in both harmonic and feature spaces. The harmonic space is defined as a three-dimensional space consisting of the first three harmonics. On the other hand, a three-dimensional feature space consists of statistical and Fourier parameters. Furthermore, the classification performance of the FSHR approach is evaluated with Monte Carlo simulations using harmonic responses in the presence of noise. In the second study, as a continuation of the first study, new feature sets are used to classify electronic circuits. The nonlinear responses of the circuits are recorded by transmitting constant power frequency-swept signals to the electronic circuits. Unlike

Günümüzde elektronik harp sistemlerinin önemi dramatik olarak artmaktadır. Elektronik Harp sistemlerinin unsurlarından olan elektronik destek sistemleri, elektromanyetik spektrumu pasif olarak kullanmaktadır. Yayılan sinyalleri analiz eden bu sistemler, düşman ve dost unsurların, yönlerini, konumlarını, kimliklerini, birlikler arası haberleşme içeriğini tespit edebilmektedir. Bu sayede, elektronik destek sistemleri istihbarat verilerinin çıkarılmasında büyük rol oynamaktadır. Teknolojinin gelişmesiyle birlikte, radar veya haberleşme sinyallerini analiz eden sistemler kabiliyetlerini genişletmektedir. Elektronik harp ve radar uygulamaları, keşif kabiliyetini artırmanın yanı sıra sinyal polarizasyon bilgilerini kullanarak hedef yön ve konum bulma performansını arttırmaya çalışmaktadır. Bu faktörler, sinyalin polarizasyon bilgisinin bahsedilen mevcut sistemlere dahil edilmesine yol açmıştır. Alıcının veya vericinin bulunduğu platformun konumuna veya yönüne bağlı olarak alıcı-verici arası polarizasyon uyumsuzluğu meydana gelebilmektedir. Hedef sinyallerin yüksek güçte alınabilmesi, başarılı bir yön bulma performansı veya elektronik harp sistemlerine karşı etkili bir karşı önlem alınabilmesi için alıcı ve vericideki polarizasyon uyumsuzluğunun önlenmesi gerekmektedir. Bu yüzden elektronik destek sistemlerinde, yayılan sinyalin polarizasyonunun tespiti, kimliklendirme, yön ve konum bulma sistemlerinde kritik bir rol oynamaktadır. Bu çalışmada, gelen sinyalin polarizasyonunu derin öğrenme yoluyla kestiren bir yaklaşım önerilmiştir. Önerilen yaklaşımda, öncelikle klasik geliş açısı ve polarizasyon kestirimi gerçekleştiren algoritmalar gibi kovaryans matrisi hesaplanmaktadır. Hesaplanan kovaryans matrisinin gerçek, sanal ve faz değerlerinden algoritmanın giriş görüntüleri elde edilmiştir. Evrişimsel sinir ağları sayesinde giriş görüntülerinden öznitelikler çıkarılıp, tam bağlı katmanlar sayesinde polarizasyon kestirimi yapılmaktadır. Çalışmada doğrusal polarizasyon belli çöz, Nowadays, the importance of electronic warfare systems is increasing. Electronic support systems, which are one of the elements of Electronic Warfare systems, passively use the electromagnetic spectrum. These systems, which analyze the emitted signals, are able to detect the directions, positions, identities, and content of communication between the enemy and friendly elements. In this way, electronic support systems play a major role in extracting intelligence data. With the development of technology, systems that analyze radar or communication signals are expanding their capabilities. Electronic warfare and radar applications try to increase target direction and position finding performance by using signal polarization information as well as increasing reconnaissance capability. These factors have led to the incorporation of polarization information of the signal into existing systems. Depending on the location or direction of the platform where the receiver or transmitter is located, polarization mismatch between the transmitter and receiver may occur. In order for target signals to be received at high power, for successful direction finding performance, or for an effective countermeasure against electronic warfare systems, polarization mismatch in the receiver and transmitter must be prevented. Therefore, detection of the polarization of the emitted signal in electronic support systems plays a critical role in identification, direction and position finding systems. In this study, an approach that estimate the polarization of the incoming signal through deep learning is proposed. In the proposed approach, first of all, the covariance matrix is calculated, such as algorithms that perform classical angle of arrival and polarization estimation. The input images of the algorithm were obtained from the real, imaginer and phase values of the calculated covariance matrix. Thanks to convolutional neural networks, features are extracted from the input images and polarizat

A new approach to exploit nonlinear reradiation of electronic circuits under test (ECUT) for classification of electronic devices using harmonic radar is proposed in this article. Unlike prior approaches, we develop a linear model to relate the measurements to the unknown parameters representing the nonlinear characteristics of the ECUT. Each nonlinear circuit under test has a distinguishable response to a power-varying single-tone or two-tone incident wave. As a result, each ECUT possesses a unique unknown deterministic vector of parameters derived from the proposed linear model. We use maximum likelihood estimator in the presence of complex white Gaussian noise based on the newly constructed linear model. The statistical features of the normalized estimated vectors of parameters are employed as distinguishing factors in classification of different nonlinear electronic devices using K-nearest neighbors classification method. Simulation results show that the proposed method of linear model with power-swept signals and estimated vectors of parameters successfully classifies nonlinear devices.

13th International Conference on Electrical and Electronics Engineering, ELECO 2021 -- 25 November 2021 through 27 November 2021 -- 176537, A realistic simulation model to obtain harmonic power curves of nonlinear circuits using harmonic radar is proposed in this study. Advanced Design System (ADS) and High Frequency Structural Simulator (HFSS) are used as simulation tools. HFSS is used for modelling free space radiation and ADS is used for circuit modelling. Three different circuits are modelled in ADS which are diode clamper, diode limiter and full wave rectifier. In HFSS part of the simulation, wideband Vivaldi antennas are modelled as radar transmit and receive antennas. To couple radiated power on electronic circuits, a single opportunity dipole antenna tuned to radar transmit frequency is used. Similarly to reradiate the harmonics generated by electronic circuits back to the radar, a log periodic dipole antenna is modelled as an opportunity transmit antenna. Sweeping electromagnetic power level from 0 to 40 dBm on the transmit antenna, nonlinear variation of reflected harmonic powers due to nonlinear components are observed. © 2021 Chamber of Turkish Electrical Engineers.

A new approach to exploit nonlinear reradiation of electronic circuits under test (ECUT) for classification of electronic devices using harmonic radar is proposed in this article. Unlike prior approaches, we develop a linear model to relate the measurements to the unknown parameters representing the nonlinear characteristics of the ECUT. Each nonlinear circuit under test has a distinguishable response to a power-varying single-tone or two-tone incident wave. As a result, each ECUT possesses a unique unknown deterministic vector of parameters derived from the proposed linear model. We use maximum likelihood estimator in the presence of complex white Gaussian noise based on the newly constructed linear model. The statistical features of the normalized estimated vectors of parameters are employed as distinguishing factors in classification of different nonlinear electronic devices using K-nearest neighbors classification method. Simulation results show that the proposed method of linear model with power-swept signals and estimated vectors of parameters successfully classifies nonlinear devices.

In this paper, a two-step model is proposed, to design an optimal radar waveform to improve the detection of point like targets over a glistening surface. In this respect, a non adaptive waveform is first transmitted and a constrained Generalized Likelihood Ratio Test (GLRT) detector is used at the receiver, which exploits multipath returns in the range cell under test, by modelling the target echo as a superposition of the direct plus the multipath returns. Besides, the clutter returns are assumed to be compound-Gaussian. The Fixed Point Estimate (FPE) algorithm is used in order to estimate the clutter in the range cell under test through the secondary data collected from the out-of-bin cells. The clutter estimates are used to design an adaptive waveform for the next transmission, in order to suppress the clutter coming from adjacent cells. The proposed GLRT is also used at the end of the second transmission for the final decision. The performance analysis results show that the proposed algorithm increases the Signal-to-Clutter Ratio (SCR) of the received signal.

YÖK Tez No: 459553, Basically, a radar system is a system that transmits radio frequency and electromagnetic waves to desired regions and receives electromagnetic waves reflected from targets and performs functions such as detection, tracking and imaging about the region. The Radar Cross Sectional area (RCS) is a measure of the scattered power in given direction when a target is illuminated by a sending electromagnetic wave. Radar Cross Sectional area is an imaginary field that indicates how much power is radiate according to the transmitter power density. In this study, Radar Cross Sectional area value of the basic and complex geometries were calculated with the aid of the Physical Optics method in Ansys HFSS programme. First, basic targets such as cubes, triangles, squares and circular plates, then more complex targets such as almonds, conical spheres, etc. were modeled and frequency and angle dependent change of the Radar Cross Sectional area values have been examined in numerical environment. A simple ammunition model which is modeled by using cylinder and cone was added to the model of the winged almond created by combining the examined simple and complex models. In order to see the effect of this ammunition on the Radar Cross Sectional area depending on the polarization, frequency and angle, simulation studies have been done in numerical environment. Finally, MQ-1B unmanned aerial vehicle and AGM-114 ammunition were modeled in three dimensions and the effect of the low and high frequencies in addition to parameters such as number of ammunition, direction of the incoming wave to target, polarization on the Radar Cross Sectional area was examined., Temel olarak bir radar sistemi, radyo frekansı ve elektromanyetik dalgaları istenilen bölgeye gönderen ve hedeflerden yansıyan elektromanyetik dalgaları alarak bölge hakkında tespit, takip, görüntüleme gibi fonksiyonları gerçekleştiren sistemlerdir. RKA, gönderilen bir elektromanyetik dalga tarafından bir hedef aydınlatıldığında verilen yönde geri saçılan gücün bir ölçütüdür. Radar Kesit Alanı sadece verici güç yoğunluğuna göre ne kadar gücün saçıldığını belirten hayali bir alan ifade etmektedir. Bu çalışmada, basit ve karmaşık yapıların Radar Kesit Alanı, Fiziksel Optik yöntemi yardımıyla Ansys HFSS programı kullanılarak hesaplanmıştır. İlk olarak, küp, üçgen, kare ve dairesel levha gibi basit hedefler daha sonra ise badem, konik küre gibi daha karmaşık hedefler Ansys HFSS'de modellenerek, Radar Kesit Alanlarının frekansa ve açıya bağlı değişimi sayısal ortamda incelenmiştir. İncelenen basit ve karmaşık modeller bir araya gelmesiyle oluşturulan kanatlı badem modeline, silindir ve koni kullanarak basit bir mühimmat modeli ana modele eklenmiştir. Eklenen muhimmatın, polarizasyon, frekans ve açıya bağlı olarak RKA'ya olan etkisini görmek için sayısal ortamda benzetim çalışmaları yapılmıştır. Son olarak MQ-1B insansız hava aracı ve AGM-114 mühimmatı üç boyutlu modellenmiş ve mühimmat sayısının, hedefe gelendalganın yönü, polarizasyon gibi parametrelere ek olarak düşük ve yüksek frekansların Radar Kesit Alanına olan etkisi incelenmiştir.

The problem of detecting point like targets over a glistening surface is investigated in this manuscript, and the design of an optimal waveform through a two-step process for a multipath exploitation radar is proposed. In the first step, a non-adaptive waveform is transmitted and a constrained Generalized Likelihood Ratio Test (GLRT) detector is deduced at reception which exploits multipath returns in the range cell under test by modelling the target echo as a superposition of the direct plus the multipath returns. Under the hypothesis of heterogeneous environments, thus by assuming a compound-Gaussian distribution for the clutter return, this latter is estimated in the range cell under test through the secondary data, which are collected from the out-of-bin cells. The Fixed Point Estimate (FPE) algorithm is applied in the clutter estimation, then used to design the adaptive waveform for transmission in the second step of the algorithm, in order to suppress the clutter coming from the adjacent cells. The proposed GLRT is also used at the end of the second transmission for the final decision. Extensive performance evaluation of the proposed detector and adaptive waveform for various multipath scenarios is presented. The performance analysis prove that the proposed method improves the Signal-to-Clutter Ratio (SCR) of the received signal, and the detection performance with multipath exploitation.

The problem of detecting point like targets over a glistening surface is investigated in this manuscript, and the design of an optimal waveform through a two-step process for a multipath exploitation radar is proposed. In the first step, a non-adaptive waveform is transmitted and a constrained Generalized Likelihood Ratio Test (GLRT) detector is deduced at reception which exploits multipath returns in the range cell under test by modelling the target echo as a superposition of the direct plus the multipath returns. Under the hypothesis of heterogeneous environments, thus by assuming a compound-Gaussian distribution for the clutter return, this latter is estimated in the range cell under test through the secondary data, which are collected from the out-of-bin cells. The Fixed Point Estimate (FPE) algorithm is applied in the clutter estimation, then used to design the adaptive waveform for transmission in the second step of the algorithm, in order to suppress the clutter coming from the adjacent cells. The proposed GLRT is also used at the end of the second transmission for the final decision. Extensive performance evaluation of the proposed detector and adaptive waveform for various multipath scenarios is presented. The performance analysis prove that the proposed method improves the Signal-to-Clutter Ratio (SCR) of the received signal, and the detection performance with multipath exploitation.

In this paper, a two-step model is proposed, to design an optimal radar waveform to improve the detection of point like targets over a glistening surface. In this respect, a non adaptive waveform is first transmitted and a constrained Generalized Likelihood Ratio Test (GLRT) detector is used at the receiver, which exploits multipath returns in the range cell under test, by modelling the target echo as a superposition of the direct plus the multipath returns. Besides, the clutter returns are assumed to be compound-Gaussian. The Fixed Point Estimate (FPE) algorithm is used in order to estimate the clutter in the range cell under test through the secondary data collected from the out-of-bin cells. The clutter estimates are used to design an adaptive waveform for the next transmission, in order to suppress the clutter coming from adjacent cells. The proposed GLRT is also used at the end of the second transmission for the final decision. The performance analysis results show that the proposed algorithm increases the Signal-to-Clutter Ratio (SCR) of the received signal.

Adaptive detection of point like targets have been studied in detail during last decades. Most of these studies assume that the target steering vector is perfectly known. This assumption may be acceptable when the signal reflected from a target has only line of sight component. However, interactions between the signal backscattered from the target and the environment causes the signal to have multipath components. In this case, the conventional adaptive detectors which assume that the target steering vector is perfectly known may not be able to detect the target properly. In addition to the studies about target signal modelling, various studies have been carried out so far about modeling the noise signal. In this respect, homogeneous model is widely used in adaptive target detection algorithms where Gaussian distribution is used as the probability density function of noise. However, the theoretical studies and the measurements with high-resolution radars show that the probability density function of the noise deviates from the Gaussian distribution. In this thesis, adaptive detection of point-like targets is considered in the presence of multipath effect under the assumption of partially homogeneous and heterogeneous environments. Therefore, in the design of an adaptive detector to operate in partially homogeneous environments, an unknown scaling factor is used to represent the mismatch between the noise covariance matrices of test and training signals. In this scenario, it is assumed that each member of the secondary data set have the same spectral properties. On the other hand, in the design of an adaptive detector to operate in heterogeneous environments, the estimation of the covariance matrix in the cell under test carried out assuming that every individual member of the secondary data set have different noise scaling factors. Besides, the target echo is modelled as the superposition of direct and multipath components where multipath echoes are thought of as sc, Nokta benzeri hedeflerin uyarlamalı sezimiyle ilgili şimdiye kadar çeşitli çalışmalar yapılmıştır. Bu çalışmaların çoğunda hedeften yansıyan sinyalin radara geliş doğrultusunun bilindiği varsayılmaktadır. Bu varsayım, sinyalin yalnızca görüş hattı bileşenine sahip olduğu durumlarda doğru kabul edilebilir. Ancak, hedeften geri saçılan sinyal ortamla etkileşime girerek çoklu-yol bileşenlerine de sahip olmaktadır. Hedef sinyali çoklu-yol bileşenleri içerdiğinde, sinyalin geliş doğrultusunun bilindiği varsayılarak geliştirilen geleneksel uyarlamalı hedef sezimi algoritmaları ile hedef tespiti düzgün bir şekilde yapılamamaktadır. Hedef sinyalinin modellenmesi üzerine yapılan çalışmaların yanı sıra, gürültü sinyalinin modellenmesi üzerine de şimdiye kadar çeşitli çalışmalar yapılmıştır. Uyarlamalı hedef sezimi algoritmalarında gürültünün olasılık yoğunluk fonksiyonu olarak Gauss dağılımının kullanıldığı homojen ortam modeli yaygın olarak kullanılmaktadır; fakat yapılan teorik çalışmalar ve yüksek çözünürlüklü radarlar kullanıldığında elde edilen ölçümler gürültünün olasılık yoğunluk fonksiyonunun Gauss dağılımından saptığını ortaya koymaktadır. Bu tez çalışmasında, nokta benzeri hedeflerin uyarlamalı sezimi çoklu-yol etkisi altında kısmi-homojen ve heterojen ortam modelleri kullanılarak gerçekleştirilmektedir. Kısmi-homojen ortamlarda çalışacak uyarlamalı dedektörün tasarımında, test hücresine ait gürültü sinyalinin kovaryans matrisi ile ikincil veri kullanılarak kestirimi yapılan kovaryans matris arasındaki uyuşmazlığı temsil eden bilinmeyen bir gürültü ölçeklendirme faktörü kullanılmaktadır. Bu senaryoda, ikincil veri hücrelerinin her birinin aynı spektral özelliklere sahip olduğu varsayılmaktadır. Heterojen ortamlarda çalışacak uyarlamalı dedektörün tasarımında ise, test altındaki hücrenin kovaryans matrisinin kestirimi ikincil veri setine ait her elemanın gürültü ölçeklendirme faktörünün birbirinden farklı olduğu varsayılarak gerçekleştirilmektedir. Bununla birlikte

Nonlinear circuit components such as diodes, transistors, etc. receive a transmitted signal at a fundamental frequency and re-radiate the harmonics and possibly intermodulation products of that frequency. Many studies have been done to utilize nonlinearities of electronic circuits to detect, range, and track targets of interest in the presence of clutter using harmonic radar, yet only a few number of researches focus on classification of various electronic circuits. A new technique to use nonlinear characteristics of electronic devices for classification of those devices using Harmonic Radar is proposed in this thesis. Unlike prior work in the literature, the powers of the transmitted incident waves are swept within a determined range in this study to capture the nonlinearities of the Electronic Circuits Under Test (ECUT). National Instruments (NI) AWR Design Environment is used to design the ECUT of this study. The first three harmonics of the received powers are analyzed in harmonic space. This novel method, derives the harmonic responses of the ECUT using Power Series Model. As a major contribution of this research, a linear model is proposed to relate the measurements to the unknown deterministic vectors of parameters characterizing the nonlinearities of the ECUT. Each electronic circuit under test has a distinguishable harmonic response to a single-tone or two-tone incident wave with varying power. Therefore, a unique vector of parameters can be derived from the presented linear model for each circuit. A Maximum Likelihood Estimator (MLE) is used in this novel approach to estimate the unique vectors of parameters in the presence of Complex White Gaussian Noise (CWGN) based on the newly developed linear model. K-Nearest Neighbors (kNN) classification method is employed to classify different nonlinear electronic devices such as diode clamper, diode limiter, and full-wave rectifier using the statistical features of the normalized estimated vectors of parameters as

A linear model using harmonic radar to distinguish electronic devices is proposed in this article. Nonlinear characteristics of the electronic devices are captured by using power varying signals as incident waves. Three harmonics of the received powers are analyzed in harmonic space. As a major contribution of this study, power series model is employed to calculate the input-output relationship of the electronic devices. As a first in this area, we construct a linear model that relates the measurements to the vectors of parameters characterizing the nonlinear behaviors of the Electronic Circuits Under Test (ECUT). Each nonlinear circuit has a distinct response to a single-tone time-varying signal with varying power. Subsequently, a unique unknown deterministic vector of parameters can be estimated from this linear model for each device. We estimate the unique vectors of parameters using a Maximum Likelihood Estimator (MLE) in the presence of Complex White Gaussian Noise (CWGN). We show that the statistical features of the normalized estimated vectors of parameters can be used to distinguish various nonlinear electronic devices.

A novel approach for classification of electronic devices using a harmonic radar is proposed in this article. We transmit single-tone time-varying signals with varying power to the electronic circuits under test (ECUTs). The novelty of the proposed approach stems from representing the harmonic response of the ECUT in the harmonic and statistical feature spaces. Besides, as a new approach, we sweep the transmitting power to capture the nonlinear behavior relevant to nonlinear I - V characteristics of the ECUT. Furthermore, we utilize both the time and frequency content of the received harmonic response. Statistical and Fourier domain features of the received power levels at harmonic frequencies are determined and used for classification. k-nearest neighbors is chosen as the classification method. We demonstrate the effectiveness of our method in the presence of noise through Monte Carlo simulations with different signal-to-noise ratio values. Extensive simulation studies show that our new approach of power-swept signals and new features we have developed are very effective at classifying nonlinear devices. © 1965-2011 IEEE.

A novel approach for classification of electronic devices using a harmonic radar is proposed in this article. We transmit single-tone time-varying signals with varying power to the electronic circuits under test (ECUTs). The novelty of the proposed approach stems from representing the harmonic response of the ECUT in the harmonic and statistical feature spaces. Besides, as a new approach, we sweep the transmitting power to capture the nonlinear behavior relevant to nonlinear I - V characteristics of the ECUT. Furthermore, we utilize both the time and frequency content of the received harmonic response. Statistical and Fourier domain features of the received power levels at harmonic frequencies are determined and used for classification. k-nearest neighbors is chosen as the classification method. We demonstrate the effectiveness of our method in the presence of noise through Monte Carlo simulations with different signal-to-noise ratio values. Extensive simulation studies show that our new approach of power-swept signals and new features we have developed are very effective at classifying nonlinear devices. © 1965-2011 IEEE.

The adaptive detection of point-like targets in the presence of multipath is considered in this article. Target return signal is modeled as the sum of direct path return and reflected path return signals under the assumption of a zero-mean complex circular Gaussian noise with an unknown covariance matrix. A new approach to exploit multipath returns in target detection with an adaptive regime is studied. The novelty of this approach is that the multipath returns are exploited with a priori knowledge of the reflecting environment, so that we have the knowledge of the reflected steering vector for a known actual direct path steering vector. As a case study, we analyze a radar-target scenario over a flat conducting surface.

Designing adaptive detector has gathered remarkable attention for modern radar systems in order to acquire more reliable target detection. Most of the work so far on adaptive detection have modeled multipath returns as clutter. In this work, we study the effects of multipath exploitation on adaptive target detection for point like targets. To that end, we compare performance of various adaptive detectors in terms of probability of detection in different multipath return senarios. We observe that adaptive detectors which exploit multipath returns have better detection performance when there is a significant resolvable multipath returns.

In this paper, a novel technique to distinguish between multiple types of electronic circuits using nonlinear radar is presented. The transmitter transmits a single tone signal to the targets, and harmonic responses are utilized to detect and distinguish non-linear electronic devices. Contrary to previous studies, the power of the transmitted signal is swept within a determined range. Then, first five harmonics of the received signal are analyzed. We utilize the information related to the frequency content using Fourier Transforms of the received harmonics are analyzed. We show that the energy levels of the Fourier Transforms can be used to classify various nonlinear electronic devices.

The idea of spectrum sharing between radar and wireless communication systems arise because of the need for extra bandwidth for wireless communication systems. Due to strong and ever growing economic, political, social, and technological driving factors, realization of this vision is inevitable in near future. Therefore, novel solutions for the efficient and fair sharing of the spectrum is needed. In this paper, we present a concise review of the state of the art on radar and communication system coexistence and bandwidth sharing.

In this paper, the design, analysis and numerical results of back scattering field of winged almond model with ammunition and without ammunition are presented. Simulations with using Physical Optics (PO) method in Ansys HFSS software for monostatic Radar Cross Section (RCS) were made in 1 GHz and 9 GHz. By using PO method to obtain the total scattered field received part of the radar, the body of the target is seperated into number of facets, then all these facets scattered field components are super imposed. When the electrical size of the target is twice as large as the wavelength, the order diffraction field is not considered. The fractured area from the first order will be sufficient to calculate the RCS of the target. Effects of ammunition quantity of modeled winged almon model with ammunition on RCS are compared in different frequencies.

Rating driving performance is a challenging topic. It attracts professionals from a variety of domains such as automotive industry and insurance companies. A great majority of the previous studies combines multiple measurement modalities such as Controller Are Network (CAN Bus) data, physiological measurements, camera reconrdings and localization estimates from Global Positioning System (GPS). One school of thought attempted to discriminate agressive/non-agressive, attentive/inattentive or drowsy/wakeful drivers through a statistical learning. Other researchers applied a rule-based approach. However, this approaches are inapplicable since labelled data for supervised learning schemes is scarce and rules that are representative for all road conditions are not feasible. Moreover, the abundance of sensor modalities in a personal vehicle is rather costly. In order to handle these problems, in this work, we propose a fully unsupervised driving style scoring mechanism operating on a minimalistic dataset. The proposed model operates similar to conventional anomaly detecton schemes. In this setting, a driving experience is scored in proportion to its congruency to the driving norms which are obtained as the most common driving patters in the training data. As a novelity of our work, these norms are defined considering road type and traffic flow patterns. This is applied via a probabilistic approach where joint probability densities of the variables controlling road type, traffic flow type and driving style are required. Since estimating this probability is mathematically intractable, we follow an alternative approach relaxing the probability estimation through discretization. In this context, each of these variables are clustered by unsupervised learning techniques and the joint probabilities are approximated by the number elements shared between inter-variable clusters. This probability information is stored in a special architecture which we call Co-Clustering Matrix. (CC, Araç sürüş performansının ölçülmesi, özellikle otomotiv ve sigorta sektörlerinde çalışan araştırmacıların ilgisini çeken, oldukça zorlu bir konudur. Bu alandaki geçmiş çalışmaların bir kolu Denetleyici Alanı Veri Yolu Ağı (CAN Bus) ve Küresel Konum Belirleme Sistemi (GPS) çıktıları, fizyolojik veriler, kamera kayıtları ve pek çok diğer veri tipini öznitelik olarak kullanarak, etiketli veri setleri üzerinde agresif/agresif olmayan, dikkatli/dikkatsiz, uykulu/uykusuz gibi davranışsal ayrımları istatistiksel olarak öğrenmeyi amaçlamışlardır. Bir diğer akımda ise, araştırmacılar sürüş davranışlarını kural-bazlı olarak değerlendirmeyi tercih etmişlerdir. Ancak, bu yaklaşımlar etiketli verinin çoğu zaman mevcut olmaması, bütün yol şartlarını temsil edebilecek kuralların öğrenilememesi ve standart bir aracın gerekli bütün sensör modalitelerine sahip olmamasından dolayı kullanışlı değillerdir. Çalışmamızda, bu problemlerin hepsinin üstesinden gelen, minimalistik bir veri üzerinde skorlama yapma kapasitesine sahip, gözetimsiz bir olasılıksal model tasarlanmıştır. Sunulan model, sürücüleri geleneksel anomali tespiti yaklaşımlarıyla değerlendirir. Buna göre, bir sürüş tecrübesinin geçmişte görülen örnekler üzerinden hesaplanan normlara ne kadar uyumlu olduğu, onun ne kadar yüksek skorlanacağını tanımlar. Bu normlar, diğer çalışmalardan farklı olarak, yolun tipine ve trafik akışına bağlı olarak bulunur. Takip edilen olasılıksal yaklaşım, bu sürekli değişkenlerin bileşik olasılık dağılımlarının bilinmesini gerektirmektedir; ancak bu matematiksel olarak oldukça zorlu bir problemdir. Bu işlemi kolaylaştırmak için, değişkenlerden her birini gözetimsiz öğrenme yöntemleri ile ayrıklaştırma yoluna gidilmiştir. Bu sayede, değişkenleri ayrık az sayıda küme ile temsil etmek ve bu kümeler arasındaki paylaşılan eleman sayılarını kullanarak bileşik olasılık dağılımlarını kestirmek mümkün olmuştur. Bileşik dağılım bilgisi, Birlikte Kümelenme Matrisi (BKM) adlı bir yapıda tutulmuştur ve bu ma

The authors consider the problem of multipath exploitation on adaptive radar detection of point-like targets in a multipath environment where a priori information is available. A new approach to exploit multipath returns with knowledge-aided adaptive target-detection regime is proposed. The authors model the received signal as the sum of direct-path and reflected-path return under the assumption of a zero-mean complex circular Gaussian noise with an unknown covariance matrix. The advantage of the proposed method is exploiting multipath returns with a priori knowledge of the reflecting environment, so that it has the knowledge of the reflected steering vector for a known actual direct-path steering vector. A Generalised Likelihood Ratio Test (GLRT) for the corresponding hypothesis testing problem is derived. It is shown that the devised detector also secures the Constant False Alarm Rate (CFAR) property regarding the unknown parameters of the noise. Performance comparison of the proposed detector with the existing well-known adaptive detectors is provided. It is presented that better-detection performance can be achieved by exploiting multipath with knowledge-aided adaptive radar. It is also observed that the devised detector has a small performance degradation in case of weak multipath return. © The Institution of Engineering and Technology 2019

A new approach to distinguishing electronic circuits using nonlinear/harmonic radar is presented in this paper. The radar transmits a single tone signal to the electronic circuits, consisting of nonlinear components, and exploits received harmonic response for separation. Unlike previous studies, the transmitted signal power is swept within a determined range so that the received powers at each harmonic are analyzed to capture the nonlinear characteristics. To predict the behavior of the nonlinear circuits such as diode clamper, diode limiter and full wave rectifier, certain statistical features of the received powers are analyzed. We show that the received power at the harmonics are distinctive for each circuit using Euclidean distances of features in feature space.

In this paper, we deal with the problem of detecting point-like targets in the presence of multipath under the assumption of a partially homogeneous Gaussian disturbance with unknown covariance matrix. Therefore, we introduce an unknown scaling factor which represents the mismatch between the noise covariance matrices of test and training signals. Besides, we model the target echo as a combination of direct and multipath components where multipath echoes are thought of as scattered signals from a glistening surface which is referred to as diffuse multipath environment. Hence, the total multipath return is also represented as a Gaussian distributed random vector with an unknown covariance matrix. At the design stage, we construct a constrained Generalized Likelihood Ratio Test (GLRT) by assuming that the total primary data covariance structure, in the target present case, resembles to the covariance matrix obtained from secondary data up to a degree (related to noise scaling factor and multipath contribution). Finally, at the analysis stage, we compared the developed algorithm with the existing solutions available in the open literature. The results highlight that the new detector copes well with severe multipath conditions and has considerable scale-invariance. © 2019 IEEE.

Radar is a system that performs functions such as detection, tracking and imaging about the target and region by sending electromagnetic waves to the interested target or region and receiving reflecting electromagnetic waves from the target. Radar consists of many elements and one of these elements is the detector. Detector decides on the target detection once it receives the reflected electromagnetic waves from the target. Depending on the effects of unwanted external signals and the noise in the environment, detectors may misoperation and have huge performans loss. Therefore, designing an adaptive detector that can operate under harsh conditions is of great importance in modern electronic warfare systems. In this thesis, unlike existing adaptive detectors in the literature, a new approach to exploit multipath returns for adaptive target detection is proposed and a new detector that exploits multipath returns, estimates the unknown noise parameters of the environment and adjust itself accordingly is designed. The performance of the obtained detector is compared with various existing adaptive detectors in terms of probability of detection. It is shown that better detection performance is achieved when there is a significant resolvable multipath returns., Radar, elektromanyetik dalgayı ilgilenen hedefe veya bölgeye gönderen ve hedeflerden yansıyan elektromanyetik dalgaları alarak hedef ve bölge hakkında tespit, takip, görüntüleme gibi fonksiyonları gerçekleştiren bir sistemdir. Radar bir çok elemandan oluşur ve içerisinde bulunan bu elemanlardan biri de algılayıcıdır. Algılayıcı, hedeften yansıyan elektromanyetik dalgaları aldıktan sonra hedef tespiti hakkında karar verir. Ortamda bulunan gürültü biçimine ve istenmeyen dış kaynaklı sinyallerin etkisine göre algılayıcılar hatalı çalışabilir ve ciddi performans kaybı yaşayabilir. Bu yüzden zor şartlarda çalışabilecek uyarlamalı algılayıcı tasarlamak günümüzde elektronik harp sistemlerinde ciddi önem taşımaktadır. Bu tez çalışmasında, literatürdeki mevcut uyarlamalı algılayıcılardan farklı olarak ortamdaki çok-yol sinyallerini sömürmek için yeni bir yöntem sunulmuş ve çok-yol yansımalarını sömüren, ortamın bilinmeyen gürültü değişkenlerini kestiren ve kendisini buna göre uyarlayan yeni bir algılayıcı tasarlanmıştır. Elde edilen algılayıcının performansı, var olan çeşitli uyarlamalı algılayıcılar ile tespit olasılığı cinsinden karşılaştırılmıştır. Belirgin ve ayırt edilebilir çok-yol yansımalarının olduğu ortamlarda daha iyi tespit performansı sağladığı gösterilmiştir.

Rating driving performance is a challenging topic. It attracts professionals from a variety of domains such as automotive industry and insurance companies. In this work, we propose a fully unsupervised driver scoring framework using a minimalistic dataset which is composed of Global Positioning System (GPS) and Controller Area Network (CAN Bus) data. Based on the natural expectation that good driving patterns should depend on the road type and traffic flow intensity, our framework attempts to assign a probabilistic score in proportion to the occurrence probability of a certain driving style given the road geometry and traffic conditions. Quantization of these random variables through clustering methods and learning of a co occurrence matrix between clusters of distinct variables provide a computationally relaxed way of otherwise intractable joint probability estimations. Utilizing this approach, we report explicitly different scoring results for aggressive and nonaggressive labelled driving experiences. Besides, we provide a rigorous analysis of clustering schemes applied on trajectory, traffic flow and driving style data.

In this paper, the analysis and numerical results of back scattering field of armed and unarmed Unmanned Air Vehicle (UAV) are presented. Simulations using Physical Optics (PO) method in Ansys HFSS software for monostatic Radar Cross Section (RCS) were made in 1 GHz, and 9 GHz. Since the electrical size of the target is twice as large as the wavelength, the order diffraction field is not considered. The fractured area from the first order will be sufficient to calculate the RCS of the target. Effects of ammunition quantity of modeled UAV with ammunition on RCS are compared in different frequencies.

The idea of spectrum sharing between radar and wireless communication systems arise because of the need for extra bandwidth for wireless communication systems. Due to strong and ever growing economic, political, social, and technological driving factors, realization of this vision is inevitable in near future. Therefore, novel solutions for the efficient and fair sharing of the spectrum is needed. In this paper, we present a concise review of the state of the art on radar and communication system coexistence and bandwidth sharing.

In this paper, a novel technique to distinguish between multiple types of electronic circuits using nonlinear radar is presented. The transmitter transmits a single tone signal to the targets, and harmonic responses are utilized to detect and distinguish non-linear electronic devices. Contrary to previous studies, the power of the transmitted signal is swept within a determined range. Then, first five harmonics of the received signal are analyzed. We utilize the information related to the frequency content using Fourier Transforms of the received harmonics are analyzed. We show that the energy levels of the Fourier Transforms can be used to classify various nonlinear electronic devices.

In this paper, the design, analysis and numerical results of back scattering field of winged almond model with ammunition and without ammunition are presented. Simulations with using Physical Optics (PO) method in Ansys HFSS software for monostatic Radar Cross Section (RCS) were made in 1 GHz and 9 GHz. By using PO method to obtain the total scattered field received part of the radar, the body of the target is seperated into number of facets, then all these facets scattered field components are super imposed. When the electrical size of the target is twice as large as the wavelength, the order diffraction field is not considered. The fractured area from the first order will be sufficient to calculate the RCS of the target. Effects of ammunition quantity of modeled winged almon model with ammunition on RCS are compared in different frequencies.

A new approach to distinguishing electronic circuits using nonlinear/harmonic radar is presented in this paper. The radar transmits a single tone signal to the electronic circuits, consisting of nonlinear components, and exploits received harmonic response for separation. Unlike previous studies, the transmitted signal power is swept within a determined range so that the received powers at each harmonic are analyzed to capture the nonlinear characteristics. To predict the behavior of the nonlinear circuits such as diode clamper, diode limiter and full wave rectifier, certain statistical features of the received powers are analyzed. We show that the received power at the harmonics are distinctive for each circuit using Euclidean distances of features in feature space.

In this paper, we deal with the problem of detecting point-like targets in the presence of multipath under the assumption of a partially homogeneous Gaussian disturbance with unknown covariance matrix. Therefore, we introduce an unknown scaling factor which represents the mismatch between the noise covariance matrices of test and training signals. Besides, we model the target echo as a combination of direct and multipath components where multipath echoes are thought of as scattered signals from a glistening surface which is referred to as diffuse multipath environment. Hence, the total multipath return is also represented as a Gaussian distributed random vector with an unknown covariance matrix. At the design stage, we construct a constrained Generalized Likelihood Ratio Test (GLRT) by assuming that the total primary data covariance structure, in the target present case, resembles to the covariance matrix obtained from secondary data up to a degree (related to noise scaling factor and multipath contribution). Finally, at the analysis stage, we compared the developed algorithm with the existing solutions available in the open literature. The results highlight that the new detector copes well with severe multipath conditions and has considerable scale-invariance. © 2019 IEEE.

In this paper, the analysis and numerical results of back scattering field of armed and unarmed Unmanned Air Vehicle (UAV) are presented. Simulations using Physical Optics (PO) method in Ansys HFSS software for monostatic Radar Cross Section (RCS) were made in 1 GHz, and 9 GHz. Since the electrical size of the target is twice as large as the wavelength, the order diffraction field is not considered. The fractured area from the first order will be sufficient to calculate the RCS of the target. Effects of ammunition quantity of modeled UAV with ammunition on RCS are compared in different frequencies.