Mehmet Nuri Akıncı

Qualitative Microwave Imaging With Scattering Parameters Measurements

Microwave imaging (MWI) systems extensively employ vector network analyzers for microwave measurements due to their high availability and accuracy. This is in contrast to theoretical models, which are naturally formulated in terms of scattered electric field vectors. Accordingly, experimental verification of MWI methods requires an intermediate step where measured scattering parameters are converted to scattered electric fields. In parallel to recent research, which formulates the Born iterative method in terms of scattering parameters, we develop formulations of two closely related qualitative inverse scattering methods-the linear sampling method and the factorization method-directly in terms of scattering parameters to avoid the intermediate conversion step. To this aim, we introduce vector S-parameters and we extend the vector Greens function for S-parameters to the dyadic case. There are certain advantages of these formulations over their electric field counterparts. First of all, the resulting formulations inherently incorporate the antenna radiation characteristics. Moreover, they reduce the measurement time since they do not require any pre- or post-measurement process. We experimentally verified the presented novel formulations against multi-frequency measurements performed inside an anechoic chamber. Obtained results show that the proposed methodologies can accurately reconstruct the shape of the targets by directly exploiting multifrequency measurements in the imaging process.

Microwave subsurface imaging of buried objects under a rough air–soil interface

We consider subsurface imaging of buried objects under a rough air–soil interface and present a microwave imaging method that is capable of determining the geometrical properties of multiple objects without requiring any a-priori information on the objects. The theoretical background of the method relies on factorization of scattering operators and the locations of buried objects are qualitatively determined from limited aperture near-field measurements performed with a short antenna array moving over the investigated region. The numerical results demonstrate that the method can handle very rough interfaces, provided that they are exactly known, and accurately determine the locations of buried obstacles even while the measurements are still in progress, which in turn opens up the possibility of real-time operation.

Experimental Assessment of Linear Sampling and Factorization Methods for Microwave Imaging of Concealed Targets

Shape reconstruction methods are particularly well suited for imaging of concealed targets. Yet, these methods are rarely employed in real nondestructive testing applications, since they generally require the electrical parameters of outer object as a priori knowledge. In this regard, we propose an approach to relieve two well known shape reconstruction algorithms, which are the linear sampling and the factorization methods, from the requirement of the a priori knowledge on electrical parameters of the surrounding medium. The idea behind this paper is that if a measurement of the reference medium (a medium which can approximate the material, except the inclusion) can be supplied to these methods, reconstructions with very high qualities can be obtained even when there is no information about the electrical parameters of the surrounding medium. Taking the advantage of this idea, we consider that it is possible to use shape reconstruction methods in buried object detection. To this end, we perform several experiments inside an anechoic chamber to verify the approach against real measurements. Accuracy and stability of the obtained results show that both the linear sampling and the factorization methods can be quite useful for various buried obstacle imaging problems.

Experimental Microwave Imaging With a Novel Corrugated Vivaldi Antenna

In this communication, a novel corrugated Vivaldi antenna (CVA) is developed for microwave imaging (MWI) applications. In particular, different from the previous works, the lengths of the corrugations are independently optimized to reach the final design. It is shown that by letting more parameters to be optimized in the design process, we can obtain a more effective CVA, which has more suitable characteristics for MWI applications (i.e., higher gain, broader bandwidth) compared with the previous designs. Apart from that, the imaging performance of the proposed design is compared with a generic VA having the same size of the proposed antenna. As imaging algorithm, a recently introduced qualitative MWI technique, the scattering parameter-based linear sampling method (S-LSM), is employed. The similarity between exact shapes of the targets and the obtained qualitative results are compared with the help of the well-known Jaccard index. Experimental results show that the proposed CVA performs better than a generic VA in such real-world MWI problems.

Experimental comparison of qualitative inverse scattering methods

Qualitative inverse scattering theory offers a group of highly theoretical methods that aims to extract physical properties of inaccessible targets. Although there are various methods depending on quite different principles which can be ultimately classified as qualitative inverse scattering methods, such methods share some common characteristics. In general, these methods are only capable of determining the shape of imaged objects and do not provide any information about electrical properties. Compared to nonlinear optimization methods, they have a simple and stable nature which offers many advantages, such as easy implementation and requiring less computational resources. In this work, we compare the performances of two well known qualitative inverse scattering algorithms which are linear sampling (LSM) and factorization methods (FM). For this purpose, we setup experimental configurations inside an anechoic chamber and investigate the performances of these methods by means of scattered field measurements. Our results indicate that both methods have quite similar reconstructions.

Near-Field Orthogonality Sampling Method for Microwave Imaging: Theory and Experimental Verification

In this paper, a new qualitative inverse scattering method for microwave imaging is proposed. The presented method is inspired by the previously introduced orthogonality sampling method (OSM) and direct sampling method (DSM), which aim to recover the reduced scattered fields. Both the OSM and the DSM are classified as backpropagation-based methods, and they are linked with the point source method and the linear sampling method. Although 3-D formulations of the OSM and the DSM exist for electromagnetic inverse scattering problems, the extension of these methods to near-field measurements is an open problem. The main contribution of this paper is introducing two novel linear operators to connect the reduced scattered fields and the tangential component of the scattered electric field measured on a circle for 2-D transverse electric (2-D-TE) and transverse magnetic (2-D-TM) inverse problems with the near-field measurements. To derive the kernel of these linear transformations, an integral equation is defined for each of the 2-D-TM and 2-D-TE problems. These equations are analytically solved, and the solutions are shown to be computable without any regularization. In addition to these theoretical contributions, the accuracy of the proposed approaches is shown with both numerical and experimental data. The constraints of the method are the measurement circle has to encover the scatterers and the targets have to be bounded in size and weak in contrast. The obtained results show that the developed approaches can be very useful in real-world applications, such as nondestructive testing and biomedical imaging.

A Simple Approach For Estimating the Effective Electric Parameters of Two-Dimensional Targets

In this paper, we introduce a simple, noniterative algorithm to estimate the effective dielectric properties of unknown targets from the measurements of their backscattered fields. The proposed approach relies on the virtual experiments concept, as it exploits a combination of the incident fields to be able to focus the exciting field on a certain region. Then, it associates the effective parameters to the permittivity and conductivity values that minimize the mean square error between the virtual scattered field (obtained by recombining the measured data) and the field scattered by a homogeneous dielectric cylinder centered on the target, having approximately the same area. The center of this effective scatterer and its radius can be estimated with a qualitative imaging algorithm or can be given as a priori information. Notably, by properly designing the virtual incident fields, the proposed method can easily handle the case of multiple targets. The effectiveness of the method is assessed by both numerical and experimental examples.

Modelling of user behaviour in cellular networks

Modeling of user behaviour becomes almost a necessity on data networks nowadays. Besides using their resources more efficiently, many data communication systems will perform more effective via estimation of statistical distribution of packet counts transferred (uploaded or downloaded) by users at once. Hence, the purpose of this study is to search suitable statistical models for distribution of packet counts that is transferred by user at once, on a arbitrary network. For this aim, an Android application is used to track Internet usage of real users. A detailed statistical analysis is performed using this data and the results are checked by applying different performance tests. Consequently, it is observed that the most suitable statistical distribution to model user behaviour is lognormal family.