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A dual-layered wideband antenna with coplanar waveguide (CPW)-base and circular parasitic element technique was proposed. In comparison to past research problems, which largely produced omnidirectional and hard antennas, it should be flexible, unidirectional, wideband, low weight, and compact. The wearable antenna consists of three stages, whereby Antenna A is designed by a basic rectangular antenna with CPW. Design B is the next stage of antenna design development with the patch size modified. Antenna C is the next development stage with extra circular parasitic element and felt substrate. The bandwidth of 4.11 GHz (79.8 %) of the proposed antenna, which ranges from 2.89 GHz to 7.0 GHz, combines a number of wideband resonant frequencies, including those at 3.07 GHz, 3.90 GHz, 4.35 GHz, 5.15 GHz, and 6.32 GHz. There is also a 40 MHz-wide narrowband that functions between 1.15 GHz and 1.19 GHz and with resonance at 1.17 GHz. This proposed antenna is designed to develop a multifunction application future work system, particularly for breast cancer detection.

Electromagnetic Imaging (EMI) is a modality that uses electromagnetic waves to interrogate an object and reconstruct the internal electrical properties. Data is collected in an imaging chamber in which antennas transmit and measure the fields surrounding the object. Cables and a switching network are necessary to connect the antennas to a vector network analyzer (VNA) to collect data, however, they also introduce mismatch by attenuating and phase shifting the signal between the antennas and VNA. A second source of error is the simplifying assumptions EMI algorithms make to efficiently model the electromagnetic fields, leading to discrepancies between the physical system and simulated fields. This thesis focuses on the calibration process used to convert the raw measurements to the scattered field data used as the input of the EMI algorithm. The first contribution of this thesis addresses the signal mismatch between the VNA and antenna ports. Considering the application of grain bin EMI, in which EMI is performed in commercial grain bins to prevent grain spoilage, the long cables needed to surround the bin structure can lead to highly corrupted signals. Herein, we consider the case when the EMI system cannot be physically accessed, and only partial scattering parameters are available from the VNA. A de-embedding method is presented that estimates the unknown cable and VNA scattering parameters so that the measurements at the antenna ports can be recovered. The method is experimentally tested on an industrial sized grain bin, with the recovered data agreeing within the measurement error of the VNA. The second contribution of this thesis is a novel calibration procedure that models the antennas and scattered fields in the imaging chamber as 2-port networks. The parameters of the antenna model are calculated by measuring calibration targets for which the theoretical fields are calculated. After the antenna model is characterized, a simple de-embedding procedure can be a

The need for non-ionizing techniques for medical imaging applications has led to the use of microwave signals. Several systems have been introduced in recent years based on increasing the number of antennas and frequency bandwidth to obtain high resolution and good accuracy in locating objects. A novel microwave imaging system that reduces the number of required antennas for precise target location appropriate for medical applications is presented. The proposed system consists of four UWB extended gap ridge horn (EGRH) antennas covering the frequency band from 0.5 GHz to 1.5 GHz mounted on a cylindrical phantom that mimics the brain in an orthogonal set of two EGRH probes. This configuration has the ability to control both the longitudinal and transversal dimensions of the reconstructed target’s image, rather than controlling the spatial resolution, by increasing the frequency band that can be easily affected by medium losses. The system is tested numerically and experimentally by the detection of a cylindrical target within a human brain model., This work was financially supported by CICYT PID2019-107885GB-C31, and support grants for university departments and research units (FI-SDUR)(2021 FISDU 00195). This work was also supported by the National Center for Scientific and Technological Research (CNRST) under grant number PPR2/2015/36., Peer Reviewed, Postprint (published version)

Morphological microwave imaging has shown interesting results on reconstructing biological objects inside the human body, and these parameters represent their actual biological condition, but not their biological activity. In this paper, we propose a novel microwave technique to locate the low-frequency (f≃1 kHz) -modulated signals produced by a microtag mimicking an action potential and proved it in a cylindrical phantom of the brain region. A set of two combined UWB microwave applicators, operating in the 0.5 to 2.5 GHz frequency band and producing a nsec interrogation pulse, is able to focus its radiated field into a small region of the brain containing the microtag with a modulated photodiode. The illuminating UWB microwave field was first modulated by the low-frequency (f≃1 kHz) electrical signal produced by the photodiode, inducing modulated microwave currents into the microtag that reradiating back towards the focusing applicators. At the receiving end, the low-frequency (f≃1 kHz) -modulated signal was first extracted from the full set of the backscattered signals, then focused into the region of interest and spatially represented in the corresponding region of the brain, resulting in a spatial resolution of the images in the order of 10 mm., This work was financially supported by the CICYT PID2019-107885GB-C31 and PDC2022-133091-I00 grants of the Agencia Estatal de Investigacion (Spain) and the PDR-2014-2022/56-30157-021-2A grant from Generalitat de Catalunya (Spain), as well as support grants for university departments and research units (FI-SDUR) (2021 FISDU 00195). This work was also supported by the National Center for Scientific and Technological Research (CNRST) under Grant Number PPR2/2015/36., Peer Reviewed, Postprint (published version)

Incidence angle diversity of space-borne radiometer and radar systems operating at low microwave frequencies needs to be taken into consideration to accurately estimate soil moisture (SM) across spatial scales. In this study, the single channel algorithm (SCA) is first applied to Soil Moisture and Ocean Salinity (SMOS) brightness temperatures at vertical polarization ( TBV ) to estimate SM at coarse resolution (25 km) and develop a land cover-specific and incidence angle (32.5°, 42.5°, and 52.5°)-adaptive calibration of single scattering albedo ( ¿ ) and soil roughness ( hs ) parameters. These effective parameters are used together with fine-scale multiangular Sentinel-1 backscatter in a single-pass active–passive downscaling approach to estimate TBV at fine scale (1 km) for each SMOS incidence angle. These TBVs are finally inverted to obtain the corresponding high-resolution SM maps. Results over the Iberian Peninsula for year 2018 show an increasing trend of ¿ and a decreasing trend of hs with SMOS incidence angle, with almost no variability of ¿ across land cover types. The active–passive covariation parameter is shown to increase with SMOS incidence angle and decrease with Sentinel-1 incidence angle. Coarse and fine TBV maps from the three SMOS incidence angles show similar distributions (mean differences below 0.38 K). Resulting high-resolution SM maps have maximum differences in mean and standard deviation of 0.016 and 0.015 m 3 /m 3 , respectively, and compare well with in situ measurements. Our results indicate that model-based microwave approaches to estimate SM can be adequately adapted to account for the incidence angle diversity of planned missions, such as Copernicus Microwave Imaging Radiometer (CIMR), Radar Observing System for Europe in L-band (ROSE-L), and Sentinel-1 next generation., This work was supported in part by Ministeriode Ciencia e Innovación (MCIN)/Agencia Estatalde Investigación (AEI)/10.13039/501100011033 under Project PID2020-114623RB-C32; in part by the Spanish Ministry of Science, Innovation and Universities, through the coordinated project L-Band [MCIU/AEI/Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea (UE)]: Sobre la continuidad de las misiones satelitales de banda L. Nuevos paradigmas en productos y aplicaciones, under Grant ESP2017-89463-C3-2-R (UPC part) and Grant ESP2017- 89463-C3-1-R (ICM part); and in part by the Unidad de Excelencia María de Maeztu under Grant MDM-2016-0600. The work of María Piles was supported by project LEAVES under Grant RTI2018-096765-A-100 funded by MCIN/AEI/10.13039/501100011033 and by the European Regional Development Fund (ERDF, EU), Peer Reviewed, Postprint (author's final draft)

Early detection and resection of colon polyp is the best way to reduce colorectal cancer (CRC) mortality. The current method for early detection is colonoscopy, which has a limited field of view, and its efficacy is highly dependant on the endoscopist's experience and colon preparation. This work presents a device for combining microwave imaging with optical colonoscopy. The challenges of this new microwave imaging system are presented, such as the unknown distance to the colon mucosa, which leads to undesired scattered fields and, the antenna size limitations. Four dynamic calibration techniques are proposed to remove the effects of the undefined distance from the imaging region to colon mucosa. These calibration methods are based on averaging the colonoscopy trajectory frames and subtracting the calibration set from the current frame. The phantom preliminary results show that these calibration methods completely delete the undesired scatter., A.G. acknowledges the financial support from DIN2019- 010857, M.G., and W.D acknowledge the financial support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 960251 and from the European Institute of Innovation and Technology (EIT). J.R. acknowledges the financial support from Agencia Estatal Investigacion PID2019-107885GB-C31/AEI/10.13039/., Peer Reviewed, Postprint (author's final draft)

Nondestructive testing of composite materials is important in aerospace applications, and mm-wave imaging has been increasingly used for this purpose. Imaging is traditionally performed using Fourier methods, with inverse methods being an alternative. This communication presents a mm-wave imaging method with an inverse approach intended for nondestructive testing of singly curved composite panels with sparsely distributed flaws. It builds on previous work which was limited to imaging on planar panels. The move from planar to singly curved panels increases the applicability of the method for aerospace applications. The imaging method is reference-free due to a numerical source separation algorithm and exploits sparsity in reconstruction of scatterers. It is demonstrated using near-field measurements at 60 GHz of an industrially manufactured composite panel with deliberate flaws. Compared to a more traditional Fourier imaging method, our method generates images with higher resolution and higher dynamic range. Flaw detection is also easier using our method as it generates images with less background clutter.

This work proposes a wideband and unidirectional antenna consisting of dual layer of coplanar waveguide based on the circular parasitic element technique. The design procedure is implemented in three stages: Design A, which operates at 3.94 GHz with a bandwidth of 3.83 GHz and a fractional bandwidth (FBW) of 97.2%; Design B, which operates at 3.98 GHz with a bandwidth of 0.66 GHz (FBW of 56.53%); and Design C as the final antenna. The final Design C is designed to resonate at several frequencies between 2.89 and 7.0 GHz for microwave imaging applications with a bandwidth of 4.11 GHz (79.8%) centered at 5.15 GHz. This antenna is fabricated fully using two textile materials: felt as the substrate and ShieldIt as the conductor. It features a unidirectional radiation with a gain of 5.5 dBi, and reduced low back radiation from 2.06 to−7.81 dB. The front-to-back ratio (FBR) for Design A, Design B and Design C are 4.82, 2.94 and 11.36 dB, respectively. This antenna is wideband with unidirectional radiation, lightweight, and flexible.

One of the techniques to enhance the performance of microwave imaging (MWI) systems is to increase the amount of independent measured data that is collected when interrogating the object-of-interest (OI). A novel method is introduced which employs field perturbing elements (FPEs) to achieve this goal. The research reported herein utilizes a cylindrical metallic enclosure having an octagonal cross-section, i.e. with at-faceted walls on which a set of electrically controlled field perturbing elements (FPEs) that project into the chamber. The FPEs are implemented as printed circuit boards that include diodes that can be forward or reversed biased. Transmit and receive antennas are placed on the walls of the chamber and for each transmitter the interrogating eld can be changed by turning one or more of the recon figurable plates ON or OFF. This allows one to reduce the number of transmit antennas that are used. Our current system consists of an octogonally shaped chamber with four transmitter/receiver antennas. The size of the metallic chamber is on the order of a few wavelengths and with the entirety of the enclosure being made up of a conductive metallic material, it constitutes a quasi-resonant chamber (we utilize an open top adding some loss to the chamber). The fi eld perturbing elements include a pattern of segmented PCB traces with multiple diodes connecting the trace segments. To reduce the computational resources required to model these reconfi gurable plates, the design criteria is to choose a pattern of the segmented PCB traces that minimally perturb the fi eld within the chamber when the diodes are \OFF" (i.e. in reverse-biased mode) by choosing the frequencies that match closely with the numerical model. This allows us to remove the plates from the numerical model when in the \OFF" mode with small effects on the accuracy. In the \ON" mode, the plates are modelled as PEC surfaces. To evaluate the performance of the proposed approach, a number of imaging expe

This thesis reports on the development and testing of 2-D and 3-D ultrasound (US) breast imaging systems, as well as a novel integrated microwave-ultrasound breast imaging system that uses US-derived prior information to enhance microwave imaging (MWI). The dual-mode system is designed to overcome the challenges present in current breast cancer screening and diagnostic techniques, namely, the use of ionizing radiation, the dependence on a skilled clinician to perform the scan and painful compression of the breast during imaging. The USI systems presented herein utilize a stationary array of transceivers that surround the breast being imaged. Tissue-mimicking phantoms designed to have sound-speeds similar to real breast tissue were developed, and details of their design are reported. Reconstruction results for several 2-D and 3-D phantoms are shown, demonstrating the ability of our USI system to produce quantitative images of the speed of sound inside an object of interest. The integrated dual-mode system makes use of the new 3-D USI system along with an existing air-based MWI system. Features of the dual-mode design include the ability to obtain scattered field measurements for both imaging modalities with little to no movement of the breast, as well as not requiring the breast to be compressed, nor the use of an immersion medium. A workflow for dual-mode imaging has been developed, including the investigation of several techniques for producing and incorporating US-derived prior information into the MW finite-element method contrast source inversion algorithm. Data were obtained using each imaging modality as well as the integrated system for two simple dual-mode breast phantoms, and the resulting quantitative reconstructions shown. The impact of different types of prior information on the MW reconstructions is discussed. An improved ability for tumour-detection using a simple thresholding technique is demonstrated for the dual-mode system, as compared to either sy

In this paper, we propose a fractional regularized distorted Born iterative method (DBIM) to solve non-linear ill-posed problems of microwave imaging. Fractional regularization is a modification to Tikhonov regularization, where singular values are weighed with fractional power. As a result, the well-known effect of oversmoothing present in Tikhonov regularization is reduced, thereby the output image quality is improved. The results of this method are compared with standard DBIM using Tikhonov regularization. Various numerical examples of simulated and experimental datasets containing homogeneous as well as heterogeneous scatterers are considered to validate the effectiveness of the proposed approach. It is found that the proposed method improves the accuracy of estimated images over conventional DBIM.

In this paper, we propose a fractional regularized distorted Born iterative method (DBIM) to solve non-linear ill-posed problems of microwave imaging. Fractional regularization is a modification to Tikhonov regularization, where singular values are weighed with fractional power. As a result, the well-known effect of oversmoothing present in Tikhonov regularization is reduced, thereby the output image quality is improved. The results of this method are compared with standard DBIM using Tikhonov regularization. Various numerical examples of simulated and experimental datasets containing homogeneous as well as heterogeneous scatterers are considered to validate the effectiveness of the proposed approach. It is found that the proposed method improves the accuracy of estimated images over conventional DBIM.

Due to the coarse spatial resolution of currently available microwave (mostly passive) soil moisture (SM) products, it is difficult to apply these SM data in watersheds or at local scales. To this end, a number of downscaling approaches have been developed to improve the spatial resolution of microwave SM products. Specifically, the optical-/thermal-based downscaling methods are most widely used in recent decades. However, such methods normally rely on instantaneous optical/thermal land surface parameters, which are commonly inapplicable under cloudy conditions. The purpose of this study is to develop a new downscaling method based on the temporal variation in geostationary satellite-derived land surface temperature and net surface shortwave radiation. The proposed method has a certain potential to improve data availability under cloudy conditions, because geostationary satellites are capable of providing land surface parameters at high temporal resolution. The proposed method was tested over the REMEDHUS network in Spain. The scaling strategy of cumulative distribution function matching was used to remove systematic differences in spatial mismatch between satellite pixels and in situ SM measurements. Results indicate that the downscaled SM agrees well with in situ measurements and has comparable accuracy with the original microwave SM product. The overall root mean square errors with the in situ measurements for the original microwave SM and the downscaled SM are 0.054 and 0.057 m³/m³, respectively. This method not only has a successful attempt to downscale microwave SM data using temporal information but also has the potential to avoid the failure of traditional instantaneous observations-based downscaling procedure due to clouds.

[EN] This paper describes the use of microwave technology to identify anti-counterfeiting markers on banknotes. The proposed method is based on a robust near-field scanning microwave microscope specially developed to measure permittivity maps of heterogeneous paper specimens at the micrometer scale. The equipment has a built-in vector network analyzer to measure the reflection response of a near-field coaxial probe, which makes it a standalone and portable device. A new approach employing the information of a displacement laser and the cavity perturbation technique was used to determine the relationship between the dielectric properties of the specimens and the resonance response of the probe, avoiding the use of distance-following techniques. The accuracy of the dielectric measurements was evaluated through a comparative study with other well-established cavity methods, revealing uncertainties lower than 5%, very similar to the accuracy reported by other more sophisticated setups. The device was employed to determine the dielectric map of a watermark on a 20 EUR banknote. In addition, the penetration capabilities of microwave energy allowed for the detection of the watermark when concealed behind dielectric or metallic layers. This work demonstrates the benefits of this microwave technique as a novel method for identifying anti-counterfeiting features, which opens new perspectives with which to develop optically opaque markers only traceable through this microwave technique.

[EN] This paper describes the use of microwave technology to identify anti-counterfeiting markers on banknotes. The proposed method is based on a robust near-field scanning microwave microscope specially developed to measure permittivity maps of heterogeneous paper specimens at the micrometer scale. The equipment has a built-in vector network analyzer to measure the reflection response of a near-field coaxial probe, which makes it a standalone and portable device. A new approach employing the information of a displacement laser and the cavity perturbation technique was used to determine the relationship between the dielectric properties of the specimens and the resonance response of the probe, avoiding the use of distance-following techniques. The accuracy of the dielectric measurements was evaluated through a comparative study with other well-established cavity methods, revealing uncertainties lower than 5%, very similar to the accuracy reported by other more sophisticated setups. The device was employed to determine the dielectric map of a watermark on a 20 EUR banknote. In addition, the penetration capabilities of microwave energy allowed for the detection of the watermark when concealed behind dielectric or metallic layers. This work demonstrates the benefits of this microwave technique as a novel method for identifying anti-counterfeiting features, which opens new perspectives with which to develop optically opaque markers only traceable through this microwave technique.

In the theoretical part of this work, a calibration strategy for both phase and amplitude calibration of rotating equispaced circular array based on redundant space calibration was introduced. It avoids the challenging implementation of conventional noise-injection networks, especially for a large-scale array, by using the strong self-consistency accomplished by array rotation. This study presents comprehensive simulation results of the proposed calibration strategy, where calibration residuals and image reconstruction errors are evaluated. The phase calibration shows outstanding performance, while the amplitude calibration is found to be biased due to the logarithms used to linearize the system of calibration equations, and the resulting image reconstruction bias is scene-dependent. A bias correction method is proposed accordingly, which requires an a priori regional brightness temperature within the observation scene. The performance of both phase and amplitude calibration take advantage of increasing the number of elements, which promises the system scalability for high spatial resolution applications.

This thesis investigates utilizing deep learning techniques to enhance Microwave Imaging (MWI). MWI has been used for a broad range of applications, from medical imaging and security to industrial engineering, subsurface prospection and stored-grain monitoring. Like other applications, medical imaging and stored-grain monitoring, which are of interest in this thesis, have recently received a lot of attention. While traditional MWI approaches have made great progress in recent years, there are still many fundamental challenges. Lower resolution compared to other imaging modalities, as well as the many reconstruction artifacts are the main challenges for MWI. In the first part of this thesis, in order to remove reconstruction artifacts and enhance the tomographic reconstructions of the complex-valued permittivity obtained using traditional MWI techniques in the breast imaging application, a 2D Convolutional Neural Network (CNN) based on the U-Net architecture is proposed. The proposed CNN takes in images obtained using the Contrast-Source Inversion (CSI) technique and attempts to produce the true image of the permittivity. The results demonstrate that the trained CNN not only removes common artifacts in CSI reconstructions, but also improves tumor detection performance. Considering these promising results on 2D images and with the hope of being able to deal with 3D real-world microwave imaging problems, we expand the U-Net architecture to enhance the 3D reconstructed breast images as the second part of this thesis. A 3D CNN was developed and trained to improve the tomographic reconstructions. Significantly, the results show that while the network is trained only with 3D images obtained synthetically, it works well with 3D images obtained from both synthetic and experimental data. Finally, a novel CNN architecture is developed to replace the inversion technique itself. The proposed architecture is a multi-branch deep convolutional neural network designed to solve elect

This paper presents a survey into the currently thriving research on using machine learning for COVID-19 induced pneumonia detection through the use of radiographic scans, presents a brief review of the methodologies and assesses the classification results, and finally presents an alternative in the form of ultrawideband (UWB) imaging. Few works on UWB imaging is investigated and used as a source of inspiration for developing an UWB imaging system for detection of accumulation of  fluid in lungs. The goal is to extract information about dielectric property variation from backscattered UWB signals to detect pneumonia caused by COVID-19. An edge fed Vivaldi antenna along with a multilayer planar model for lung is simulated in CST microwave studio and subjected to UWB excitation. The backscattered signals in the form of S-parameters are analyzed with various Delay-and-Sum (DAS) algorithms and images are constructed for lung tissues of different permittivity and conductivity, where higher values are supported to allude to the  infected lungs.  &nbsp

In this paper, a new methodology based on the exponential filtering of singular values is adopted to solve the linear ill-posed problem of microwave imaging. This technique filters out the insignificant singular values and works as an efficient low pass filter to eliminate high-frequency noise from the estimated solution. Standard Tikhonov regularization has also proven to be a special case of this method. To show the effectiveness of this approach, various numerical examples of synthetic data and experimental data of Fresnel's Institute are considered for the study. The reconstruction performance of this algorithm is quantified using the mean square error (MSE) and Pearson's correlation coefficient (PCC). Further, the effect of noise on these metrics is presented. The results are compared with the standard Tikhonov regularization method, and it is observed that the proposed reconstruction algorithm provides accurate results compared to the standard Tikhonov regularization method.

In this paper, a new methodology based on the exponential filtering of singular values is adopted to solve the linear ill-posed problem of microwave imaging. This technique filters out the insignificant singular values and works as an efficient low pass filter to eliminate high-frequency noise from the estimated solution. Standard Tikhonov regularization has also proven to be a special case of this method. To show the effectiveness of this approach, various numerical examples of synthetic data and experimental data of Fresnel's Institute are considered for the study. The reconstruction performance of this algorithm is quantified using the mean square error (MSE) and Pearson's correlation coefficient (PCC). Further, the effect of noise on these metrics is presented. The results are compared with the standard Tikhonov regularization method, and it is observed that the proposed reconstruction algorithm provides accurate results compared to the standard Tikhonov regularization method.

A system to integrate microwave imaging with optical colonoscopy is presented. The overarching goal is to improve the prevention and early diagnosis of one of the main health and economic burdens of an increasingly aging population, i.e., colorectal cancer. For a colonoscopy, the gold standard for colorectal cancer diagnosis, 22% of polyps are not detected, and the risk of cancer after a negative colonoscopy can be up to 7.9%. To remedy this, a microwave imaging system able to generate an alarm when a polyp is detected is designed, manufactured and validated with a colon phantom composed of tissue-mimicking oil-gelatin materials reproducing the anatomy and dielectric properties of a human colon with a polyp. The acquisition was performed by a miniaturized ring-shaped switched array of 16 antennas attachable at the tip of a conventional colonoscope. This has been conceived to satisfy endoscopy size restrictions, patient safety and intercompatibility with current clinical practice. A Modified Monofocusing imaging method preceded by a previous frame average subtraction as a calibration technique shows a perfect detection of a 10-mm polyp (100% sensitivity and specificity) in the eight analyzed trajectories. The phantom results demonstrate the feasibility of the system in future preclinical trials., The work of Alejandra Garrido was supported by DIN2019-010857. The work of Roberto Sont, Ignasi Belda, and Marta Guardiola was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 960251 and in part by the European Institute of Innovation and Technology (EIT). The work of Jordi Romeu was supported by PID2019-107885GB-C31/AEI/10.13039/501100011033., Peer Reviewed, Postprint (published version)

The dissertation solves the coupled models of electromagnetic (EM) wave and heat transfer by using finite element method (FEM) in the field of communication, medical, and heating. Microwave radiation lies in the non-ionizing radiation part of the EM wave spectrum. In communication, there have been concern that the exposure of mobile phone radiation could cause an adverse effect on human health. Moreover, the interaction of microwave radiation with metal objects could cause an interference leading to a higher exposure to human. Hence, the effect of microwave radiation in the human head in proximity of metal objects are studied. Results showed a significant increase in the power absorption in the head tissues due to the presence of the metal objects. Coming to the medical usage of the microwave radiation, radar-based microwave imaging of breast cancer detection is studied. A microstrip patch antenna is designed and used in the microwave imaging system. The antenna scans the breast tissues, and with the help of an imaging algorithm, a 2D image of the breast tissue is generated showing the presence of the tumor in it. Power absorption in the breast tissue for different age group of women and types of tumor has also been studied. The usage of microwave radiation is further investigated in the field of microwave heating of coal. A coal sample is heated in a microwave oven while the position of the waveguide port is varied. It has been found that the microwave heating of coal highly depends on the position of the waveguide port.

The dissertation solves the coupled models of electromagnetic (EM) wave and heat transfer by using finite element method (FEM) in the field of communication, medical, and heating. Microwave radiation lies in the non-ionizing radiation part of the EM wave spectrum. In communication, there have been concern that the exposure of mobile phone radiation could cause an adverse effect on human health. Moreover, the interaction of microwave radiation with metal objects could cause an interference leading to a higher exposure to human. Hence, the effect of microwave radiation in the human head in proximity of metal objects are studied. Results showed a significant increase in the power absorption in the head tissues due to the presence of the metal objects. Coming to the medical usage of the microwave radiation, radar-based microwave imaging of breast cancer detection is studied. A microstrip patch antenna is designed and used in the microwave imaging system. The antenna scans the breast tissues, and with the help of an imaging algorithm, a 2D image of the breast tissue is generated showing the presence of the tumor in it. Power absorption in the breast tissue for different age group of women and types of tumor has also been studied. The usage of microwave radiation is further investigated in the field of microwave heating of coal. A coal sample is heated in a microwave oven while the position of the waveguide port is varied. It has been found that the microwave heating of coal highly depends on the position of the waveguide port.

The dissertation solves the coupled models of electromagnetic (EM) wave and heat transfer by using finite element method (FEM) in the field of communication, medical, and heating. Microwave radiation lies in the non-ionizing radiation part of the EM wave spectrum. In communication, there have been concern that the exposure of mobile phone radiation could cause an adverse effect on human health. Moreover, the interaction of microwave radiation with metal objects could cause an interference leading to a higher exposure to human. Hence, the effect of microwave radiation in the human head in proximity of metal objects are studied. Results showed a significant increase in the power absorption in the head tissues due to the presence of the metal objects. Coming to the medical usage of the microwave radiation, radar-based microwave imaging of breast cancer detection is studied. A microstrip patch antenna is designed and used in the microwave imaging system. The antenna scans the breast tissues, and with the help of an imaging algorithm, a 2D image of the breast tissue is generated showing the presence of the tumor in it. Power absorption in the breast tissue for different age group of women and types of tumor has also been studied. The usage of microwave radiation is further investigated in the field of microwave heating of coal. A coal sample is heated in a microwave oven while the position of the waveguide port is varied. It has been found that the microwave heating of coal highly depends on the position of the waveguide port.

We consider imaging the reflectivity of scatterers from intensity-only data recorded by a single moving transducer that both emits and receives signals, forming a synthetic aperture. By exploiting frequency illumination diversity, we obtain multiple intensity measurements at each location, from which we determine field cross-correlations using an appropriate phase controlled illumination strategy and the inner product polarization identity. The field cross-correlations obtained this way do not, however, provide all the missing phase information because they are determined up to a phase that depends on the receiver's location. The main result of this paper is an algorithm with which we recover the field cross-correlations up to a single phase that is common to all the data measured over the synthetic aperture, so all the data are synchronized. Thus, we can image coherently with data over all frequencies and measurement locations as if full phase information was recorded.

3-D imaging with irregular planar multiple-input-multiple-output (MIMO) arrays is discussed. Due to signal acquisition on irregular spatial sampling grids by using these antenna arrays, the fast Fourier transform (FFT)-based imaging algorithms cannot readily be used for image formation. To avoid the application of computationally intensive coherent summation algorithms such as filtered backprojection or Kirchhoff migration, we propose a nonuniform FFT (NUFFT)-based MIMO Range Migration Algorithm (i.e., NUFFT-based MIMO-RMA) for efficient microwave imaging. The algorithm exploits NUFFT to reconstruct the wavenumber-domain spectra related to each Fourier frequency. It is generic and applicable to 3-D imaging with irregular planar MIMO arrays. The effects of irregular spatial sampling and signal bandwidth on the imaging performance and computational efficiency of the proposed algorithm are analyzed. Finally, some numerical simulations and experimental results are presented to demonstrate the performance of the proposed imaging algorithm., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

In this paper, we describe the recent development of new algorithms applied to short-range radar imaging. Facing the limitations of classical backpropagation algorithms, the use of techniques based on Fast Fourier Transforms has led to substantial image computation accelerations, especially for Multiple-Input Multiple-Output systems. The necessary spatial interpolation and zero-padding steps are still particularly limiting in this context, so it is proposed to replace it by a more efficient matrix technique, showing improvements in memory consumption, image computation speed and reconstruction quality., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

The dissertation solves the coupled models of electromagnetic (EM) wave and heat transfer by using finite element method (FEM) in the field of communication, medical, and heating. Microwave radiation lies in the non-ionizing radiation part of the EM wave spectrum. In communication, there have been concern that the exposure of mobile phone radiation could cause an adverse effect on human health. Moreover, the interaction of microwave radiation with metal objects could cause an interference leading to a higher exposure to human. Hence, the effect of microwave radiation in the human head in proximity of metal objects are studied. Results showed a significant increase in the power absorption in the head tissues due to the presence of the metal objects. Coming to the medical usage of the microwave radiation, radar-based microwave imaging of breast cancer detection is studied. A microstrip patch antenna is designed and used in the microwave imaging system. The antenna scans the breast tissues, and with the help of an imaging algorithm, a 2D image of the breast tissue is generated showing the presence of the tumor in it. Power absorption in the breast tissue for different age group of women and types of tumor has also been studied. The usage of microwave radiation is further investigated in the field of microwave heating of coal. A coal sample is heated in a microwave oven while the position of the waveguide port is varied. It has been found that the microwave heating of coal highly depends on the position of the waveguide port.

In this paper, we describe the recent development of new algorithms applied to short-range radar imaging. Facing the limitations of classical backpropagation algorithms, the use of techniques based on Fast Fourier Transforms has led to substantial image computation accelerations, especially for Multiple-Input Multiple-Output systems. The necessary spatial interpolation and zero-padding steps are still particularly limiting in this context, so it is proposed to replace it by a more efficient matrix technique, showing improvements in memory consumption, image computation speed and reconstruction quality., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

Breast microwave sensing (BMS) is an emerging modality that has the potential to be used as a breast cancer screening technique but challenges remain before the modality is suitable for clinical use. Improvements to image-based and machine learning tumor-detection methods are required. This thesis presents novel improvements in image reconstruction and machine learning methods. This work presents the development of the largest open-access experimental dataset in the published BMS literature to-date, the University of Manitoba Breast Microwave Imaging Dataset (UM-BMID). The impact of the inverse chirp z-transform (ICZT) on radar-based image reconstruction was compared to that of the standard inverse discrete Fourier transform using a subset of this dataset. The ICZT was found to reduce image artifacts, improve image contrast, and increase tumor-detection in reconstructions. A novel reconstruction method, the iterative delay-and-sum (itDAS) beamformer, was compared to two literature standard approaches. The novel method improved image contrast by as much as 249% on average and allows for the implementation of correction factors to improve the radar signal model used in the literature standard algorithms. Three correction factors were examined and modeling the output pulse of the BMS system significantly increased the contrast of itDAS reconstructions. The diagnostic capability of machine learning methods in BMS was investigated using UM-BMID. The area under the curve of the receiver operating characteristic curve of a convolutional neural network was estimated to be between (76 ± 3)% and (91 ± 3)%, where the upper estimate is obtained when the testing set is constrained to consist of phantoms with breast volumes that are within the breast volume bounds of the training set and when the tumor is located at the same vertical position as the antennas. This thesis has set the stage for future large-scale analyses in BMS through the development of the first and largest open

Although microwave imaging (MWI) remains a promising future diagnostic tool in breast cancer detection and monitoring, its progress towards clinical application would benefit from improvement to its relatively low spatial and contrast resolution in delineating healthy and abnormal tissues. Research into multiple quality improvement methods for MWI reconstructions has thus been undertaken, through alterations of an existing finite-element contrast source inversion (FEM-CSI) algorithm that uses a time-harmonic, discontinuous Galerkin formulation of Maxwell's equations (DGM-CSI). Firstly, DGM-CSI has been employed to produce 2D images of the dielectric properties of synthetic breast models at multiple frequencies using a modified frequency-hopping technique that successively introduces alterations to the intermediate reconstructions of the complex-valued permittivity obtained at each of the individual frequencies. Using a tissue-dependent mapping technique, improvement in overall image quality is observed when the imaginary part of a reconstruction is modified to reflect the identical tissue geometry and probable tissue types obtained in its real part, and passed back to the algorithm as the initial guess between successive frequencies. Secondly, related increases in efficiency are noted when this same DGM-CSI algorithm is altered to employ a “frequency cycling” reconstruction technique combined with novel automated stopping criteria. Images obtained from the highest frequency data in a given frequency-hopping sequence are cycled back to the lowest frequency data as new initial guesses to restart multi-frequency inversions. The stopping criteria reduce the total number of algorithmic iterations by determining a suitable time to shift imaging frequencies and globally terminate reconstructions, based on a statistical analysis of a window of past iterations of data error using the two-sample Kolmogorov-Smirnov (K-S) test. Finally, contrast enhancement using “ferrofluid” c

3-D imaging with irregular planar multiple-input-multiple-output (MIMO) arrays is discussed. Due to signal acquisition on irregular spatial sampling grids by using these antenna arrays, the fast Fourier transform (FFT)-based imaging algorithms cannot readily be used for image formation. To avoid the application of computationally intensive coherent summation algorithms such as filtered backprojection or Kirchhoff migration, we propose a nonuniform FFT (NUFFT)-based MIMO Range Migration Algorithm (i.e., NUFFT-based MIMO-RMA) for efficient microwave imaging. The algorithm exploits NUFFT to reconstruct the wavenumber-domain spectra related to each Fourier frequency. It is generic and applicable to 3-D imaging with irregular planar MIMO arrays. The effects of irregular spatial sampling and signal bandwidth on the imaging performance and computational efficiency of the proposed algorithm are analyzed. Finally, some numerical simulations and experimental results are presented to demonstrate the performance of the proposed imaging algorithm., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

This paper presents the feasibility of using a microwave imaging system for monitoring bone mineralization progress overtime after craniotomy surgery. Any variation in the composition of the bone flap can be monitored as a variation in the intensity of the image. A simulation is conducted on a head structure derived from a numerical head phantom based on anatomically realistic MRI-derived FDTD models using commercial CST 2019 software. For simulation, a defect is provided in the skull layer surrounded by a 9-elements antenna. Applying Space-Frequency Time Reversal (TR) method, the image of defect is constructed for different permittivity of the defect ranging from 16 to 36. Results show that the image intensity at the defect location will decrease as the permittivity of the defect decreases.

type:Journal Article, Microwave imaging is the technique to identify hidden objects from structures using electromagnetic waves that can be applied in medical diagnosis. The change of dielectric property can be detected using microwave antenna sensor, which can lead to localization of abnormality in the human body. This paper presents a stacked type modified Planar Inverted F Antenna (PIFA) as microwave imaging sensor. Design and performance analysis of the sensor antenna along with computational and experimental analysis to identify concealed object has been investigated in this study. The dimension of the modified PIFA radiating patch is 40 × 20 × 10 mm3. The reflector walls used, are 45 mm in length and 0.2-mm-thick inexpensive copper sheet is considered for the simulation and fabrication which addresses the problems of high expenses in conventional patch antenna. The proposed antenna sensor operates at 1.55–1.68 GHz where the maximum realized gain is 4.5 dB with consistent unidirectional radiation characteristics. The proposed sensor antenna is used to identify tumor in a computational human tissue phantom based on reflection and transmission coefficient. Finally, an experiment has been performed to verify the antenna’s potentiality of detecting abnormality in realistic breast phantom.

type:Journal Article, Globally, breast cancer is reported as a primary cause of death in women. More than 1.8 million new breast cancer cases are diagnosed every year. Because of the current limitations on clinical imaging, researchers are motivated to investigate complementary tools and alternatives to available techniques for detecting breast cancer in earlier stages. This article presents a review of concepts and electromagnetic techniques for microwave breast imaging. More specifically, this work reviews ultra-wideband (UWB) antenna sensors and their current applications in medical imaging, leading to breast imaging. We review the use of UWB sensor based microwave energy in various imaging applications for breast tumor related diseases, tumor detection, and breast tumor detection. In microwave imaging, the back-scattered signals radiating by sensors from a human body are analyzed for changes in the electrical properties of tissues. Tumorous cells exhibit higher dielectric constants because of their high water content. The goal of this article is to provide microwave researchers with in-depth information on electromagnetic techniques for microwave imaging sensors and describe recent developments in these techniques.

In this study, an inverse scattering approach is investigated for the detection and imaging of an abnormal structure (a bleeding or a stroke) inside the human brain. The method is mainly based on the solution of an integral equation whose kernel is the Green’s function of the inhomogeneous medium (corresponding to a human head model) which is obtained by a numerical approach based on Method of Moments (MoM). In this context, an inverse scattering problem related to the difference of healthy and unhealthy brain models is formulated and a difference function is obtained which indicates the region where the anomaly is located by solving this inverse problem. In order to reduce the reflection effects caused by the electromagnetic differences between the free space and the brain, a matching medium is used as the background space.

The growing need for high-performance imaging tools for terrorist threat detection and medical diagnosis has led to the development of new active architectures in the microwave and millimeter range. Notably, multiple-input multiple-output systems can meet the resolution constraints imposed by these applications by creating large, synthetic radiating apertures with a limited number of antennas used independently in transmitting and receiving signals. However, the implementation of such systems is coupled with strong constraints in the software layer, requiring the development of reconstruction techniques capable of interrogating the observed scene by optimizing both the resolution of images reconstructed in two or three dimensions and the associated computation times. In this paper, we first review the formalisms and constraints associated with each application by taking stock of efficient processing techniques based on spectral decompositions, and then, we present a new technique called the transverse spectrum deconvolution range migration algorithm allowing us to carry out reconstructions that are both faster and more accurate than with conventional Fourier domain processing techniques. This paper is particularly relevant to the development of new computational imaging tools that require, even more pronouncedly than in the case of conventional architectures, fast image computing techniques despite a very large number of radiating elements interrogating the scene to be imaged., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

In this paper, an UWB Tapered Slot Vivaldi Antenna (TSA) is presented. The proposed TSA is optimized in order to increase the bandwidth and ensure a good impedance matching at low and bandwidth frequencies while respecting the low profile. The overall size of simulated antenna is 45×40×0.8 mm 3 . This antenna is designed in order to be used in bio medical application and some other radar based microwave imaging., This work was supported by the Moroccan Ministry of Higher Education (MESRSFC) and the CNRST under grant number PPR2/2015/36., Peer Reviewed, Postprint (published version)

Представљена је квалитативна метода нумеричке електромагнетике за микроталасно формирање слике, која се ослања на решавање инверзног проблема расејања. У уводном делу дат је преглед литературе и укратко су дефинисане предности предложеног алгоритма у односу на већ постојеће методе. Након увода, дефинисани су основни постулати инверзних проблема и упоређени са добро познатом формулацијом директних електромагнетских проблема. Након тога, објашњене су потешкоће које настају при решавању инверзних проблема, односно показано је да су они у општем случају нелинеарни и некоректно постављени. Такође, детаљно је описана техника развоја по мултиполима као фундаментална алатка у аналитичкој електромагнетици, на којој се заснива приказана метода..., An electromagnetic qualitative microwave imaging method, which relies on solving an inverse scattering problem, is presented. In the introductory part of this dissertation, the state-of-the-art is briefly summarized. Also, main advantages of the proposed method, compared to other known methods, are outlined. After the introduction, we define the basic idea of an inverse problem, compared to the well-known direct electromagnetic problem formulation. Then, we explain the main difficulties arising during an attempt to solve such an inverse problem, i.e., it is shown that these problems are generally non-linear and ill-posed. Also, the multipole expansion technique, as a fundamental tool in analytical electromagnetics, is described in detail...

This paper presents the reconstructed curved images after craniotomy. The performance of the resistively tapered antenna is evaluated in terms of short-range sensing aspects. A series of amplitude scans along the curved array structure is proposed and measured. Three different conditions at the defect area are emulated and these images are reconstructed as a curved cranial shape.

The motivation of this work is the detection of cerebrovascular accidents by microwave tomographic imaging. This requires the solution of an inverse problem relying on a minimization algorithm (for example, gradient-based), where successive iterations consist in repeated solutions of a direct problem. The reconstruction algorithm is extremely computationally intensive and makes use of efficient parallel algorithms and high-performance computing. The feasibility of this type of imaging is conditioned on one hand by an accurate reconstruction of the material properties of the propagation medium and on the other hand by a considerable reduction in simulation time. Fulfilling these two requirements will enable a very rapid and accurate diagnosis. From the mathematical and numerical point of view, this means solving Maxwell's equations in time-harmonic regime by appropriate domain decomposition methods, which are naturally adapted to parallel architectures.

This thesis presents the development and implementation of the time-harmonic discontinuous Galerkin method (DGM) as a robust forward solver for the contrast source inversion (CSI) and Gauss-Newton inversion (GNI) imaging algorithms for electromagnetic imaging. Modern microwave imaging systems require versatile imaging algorithms that support electric and/or magnetic field data, and recent advances in material sciences have shown promise in the use of magnetic contrast agents which require the ability to recover permeability, both of which can be accomplished by using a DGM forward solver. DGM features also include high-order field and constitutive expansions and support for high-order representations of inhomogeneous backgrounds, which have been shown to improve imaging results. Presented herein are implementation details of a fully parallel C++ code for the DGM forward solver and DGM-CSI and DGM-GNI inversion algorithms, as well as synthetic and experimental results highlighting the capabilities of these algorithms, with a focus on breast cancer imaging.

The growing need for high-performance imaging tools for terrorist threat detection and medical diagnosis has led to the development of new active architectures in the microwave and millimeter range. Notably, multiple-input multiple-output systems can meet the resolution constraints imposed by these applications by creating large, synthetic radiating apertures with a limited number of antennas used independently in transmitting and receiving signals. However, the implementation of such systems is coupled with strong constraints in the software layer, requiring the development of reconstruction techniques capable of interrogating the observed scene by optimizing both the resolution of images reconstructed in two or three dimensions and the associated computation times. In this paper, we first review the formalisms and constraints associated with each application by taking stock of efficient processing techniques based on spectral decompositions, and then, we present a new technique called the transverse spectrum deconvolution range migration algorithm allowing us to carry out reconstructions that are both faster and more accurate than with conventional Fourier domain processing techniques. This paper is particularly relevant to the development of new computational imaging tools that require, even more pronouncedly than in the case of conventional architectures, fast image computing techniques despite a very large number of radiating elements interrogating the scene to be imaged., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Microwave Sensing, Signals & Systems

In this study, an inverse scattering approach is investigated for the detection and imaging of an abnormal structure (a bleeding or a stroke) inside the human brain. The method is mainly based on the solution of an integral equation whose kernel is the Green’s function of the inhomogeneous medium (corresponding to a human head model) which is obtained by a numerical approach based on Method of Moments (MoM). In this context, an inverse scattering problem related to the difference of healthy and unhealthy brain models is formulated and a difference function is obtained which indicates the region where the anomaly is located by solving this inverse problem. In order to reduce the reflection effects caused by the electromagnetic differences between the free space and the brain, a matching medium is used as the background space.