Sedef Kent

Dielectric Permittivity Estimation of Cylindrical Objects Using Genetic Algorithm

A new method based on a genetic algorithm for the estimation of the dielectric permittivity distribution of a cross section of an inhomogeneous cylindrical object illuminated by a low power microwave radiation field is presented. This method has been tested for some objects using simulated scattered fields. A good convergence to the expected values was obtained.

Radar target classification based on support vector machines and High Resolution Range Profiles

In this study, the support vector machine (SVM) was used as a classifier to identify aerospace objects. Radar target identification based on high resolution range profiles (HRRPs) received much attention because of its reduced complexity than those using two-dimensional (2-D) ISAR images. Therefore range profiles were used as feature vectors to represent radar data. Data sets which are for training and testing were generated by using a program called radar target backscattering simulation (RTBS) for three different target types. The performance of the SVM was compared with other classification algorithms including statistical classification techniques such as maximum likelihood (ML) and fisher linear likelihood (FLL).

Performance analysis of compressive ISAR imaging for complex targets

In this paper, performance efficiency analysis of compressive inverse synthetic aperture radar (ISAR) imaging for a complex, electrically large target is presented. In this context, physical optics (PO) is used as a high-frequency scattered field prediction technique and compressive sensing (CS) theory is applied to ISAR imaging by exploiting the sparse point scatterer structure of the target. Results prove that CS provides high resolution and accuracy in ISAR imaging even under the Nyquist sampling rate and linearly decreases computational time.

Spectrum sensing using empirical mode decomposition and relative entropy

Recently, as many new wireless services emerge, number of the users needing to access the limited frequency spectrum is increased. This brings the need for improvements on efficient spectrum utilization. Cognitive Radio (CR) is proposed as a solution to this problem. Spectrum sensing is an essential component of CR to increase spectrum usage efficiency. One of the most important problems encountered in spectrum sensing is the noise uncertainty of the channel. In this study, an Empirical Mode Decomposition (EMD) based spectrum sensing algorithm using relative entropy is proposed. This approach is shown to be robust to noise uncertainty and provide promising probability of detection results by using computer simulations.

ANALYSIS OF MICROWAVE CAVITY LOADED WITH LOSSY DIELECTRIC SLAB BY MEANS OF MODE MATCHING METHOD AND OPTIMIZATION OF LOAD LOCATION

An analysis is presented by means of a mode matching method for two microwave cavities of difierent sizes which are fed by a TE10 waveguide and loaded with lossy dielectric slab type material. The accuracy of the results obtained is presented together with a comparison of the results which are obtained by the HFSS numerical method. Optimization of the load location was performed in order to maximize the electrical fleld on the material. The principle of this optimization is based on flnding the existence of the positions in which the re∞ection coe-cient S11 is the lowest. When the feeding guide for the two difierent microwave cavities was at the centre of the resonator, the change in the re∞ection coe-cient distribution was detected according to the difierent positions of the material in the oven, and then the lowest positions were found. The changes in the electric fleld in the detected positions were recorded.

Border feature detection and adaptation algorithm for consensual decision making

The performance of classification algorithms is heavily related to the quality of the training samples in supervised learning. Conventional statistical classifiers assume that data have a specific distribution. Such assumptions may not be valid for real world data. Additionally, enough training samples are required for every class to make a proper estimation of parameters to represent distribution functions. In general, there is a limited number of training samples in remote sensing. Therefore, classification algorithms should be robust with various types of training sample sets to achieve sufficient generalization performance. In this study, a new classification algorithm called border feature detection and adaptation (BFDA) is used to partition the feature space by taking into account some geometric considerations to support maximum margins between different class borders via some reference vectors called border features. The performance of the BFDA is related to the initialization of the border features during the border feature detection stage, and the input ordering of the training samples during the adaptation process. These dependencies cause relatively biased decisions. Therefore, consensual strategy with cross validation can be applied to improve the generalization performance. The resulting process is called consensual BFDA (C‐BFDA).

An edge detection method using 2-D autoregressive lattice prediction filters for remotely sensed images

Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Edge detecting an image significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Edge detection is useful for segmentation, registration, and identification of objects in remote sensing images. Two dimensional lattice filters have been shown to be useful in many applications such as multidimensional spectral estimation, image data compression, high-resolution radar imaging, and removal of correlated clutter to enhance the detection ability of small objects in images. In this work, lattice filters are used for detecting the edges in remote sensing images. Lattice filter can be used to predict the correlated parts in an image and the resulting error (the output of the filter) will be edges. Edge detection results have been compared with other conventional edge detection methods as well as wavelet based methods. Results show that the proposed method is a good candidate for edge detection problem in remotely sensed images

NUMERICAL MODELING OF MICROSTRIP RADIAL STUB

A simple numerical algorithm used to model microstrip radial stub is presented. The cascaded interconnections of uniform transmission lines with incremental length dl are considered for the calculation of input impedance of a radial stub. Calculated results are consistent with the theoretical and experimental results found in the literature.

Analysis of Multiple Wedges Electromagnetic Wave Absorbers

To improve the re∞ection performance of absorbers used in anechoic chambers, several difierent electromagnetic wave absorber geometries similar to conventional wedge absorber structures are proposed in this study. Design basics are examined by using the re∞ection and absorption of electromagnetic waves. The return loss characteristics of each absorber structure which is illuminated by a TE polarized plane wave have been obtained using well-known simulation software for several incidence angles. Comparisons of the simulation results of the conventional wedge and proposed absorbers are presented. The results show that new absorber shapes provide better absorption characteristics than a conventional wedge across almost all frequency ranges especially for normal and near normal incidence cases.

Optimized geometry pyramidal absorber for normal incidence case

To improve accuracy of the EMC measurements in anechoic chambers, a new absorber shape is presented in this study that results in a lower reflection coefficient than the commonly used pyramidal shape for the normal incidence case of the plane electromagnetic wave. This new profile shape is obtained based on a pyramidal absorber by using genetic algorithm. The return loss characteristics of the proposed absorber structure which is illuminated by a TE polarized plane wave have been obtained using well-known simulation software for normal incidence case. Comparisons of the simulation results of the conventional wedge and proposed absorber are presented. The results show that new absorber shape provides better absorption characteristics than a conventional wedge across almost all frequency ranges for normal incidence case.