With the dangerous and troublesome nature of hollow defects inside building structures, hollowness inspection has always been a challenge in the field of construction quality assessment. Several methods have been proposed for inspecting hollowness inside concrete structures. These methods have shown great advantages compared to manual inspection but still lack autonomy and have several limitations. In this paper, we propose a range-point migration-based non-contact hollowness inspection system with sensor fusion of ultra-wide-band radar and laser-based depth camera to extract both outer surface and inner hollowness information accurately and efficiently. The simulation result evaluates the performance of the system based on the original range-point migration algorithm, and our proposed one and the result of our system show great competitiveness. Several simulation experiments of structures that are very common in reality are carried out to draw more convincing conclusions about the system. At the same time, a set of laboratory-made concrete components were used as experimental objects for the robotic system. Although still accompanied by some problems, these experiments demonstrate the availability of an automated hollow-core detection system.

Through-wall imaging is capable of detecting various living and non-living things behind the wall. The characteristics of the wall under the investigation, amount of clutter and noise govern the quality and reliability of the image as well as the detection ability of the targets using through the wall imaging system. The characteristics of the wall are not known prior, in the literature only the intensity profile is investigated for the unknown wall characteristics using a single dielectric target and the effect of the wall characteristics on the contrast imaging and impact on time or frequency domain features are not investigated. The target with less dielectric is having less reflectivity; hence its detection in the presence of a high reflective target and a noisy environment becomes difficult. In this paper, to enhance the detection ability of the imaging system attenuation constant (α) of the wall is estimated with the proposed wall parameter estimation methods and used as a normalizing factor. To achieve effective beamforming different weighting strategies are developed and the obtained images are compared with the traditional beamforming. Furthermore, a novel approach to finding the effective rank in the low-rank estimation using a statistical model and multi-objective genetic algorithm is proposed for de-noising.

The distorted Born iterative method (DBIM) is a widely used quantitative reconstruction algorithm to solve the inverse scattering problems of microwave imaging. The major mathematical challenges in solving such problems are non-uniqueness, non-linearity, and ill-posedness. Due to these issues, the optimization algorithm converges to a local minimum. This drawback can be overcome by selecting the correct initial guess solution, which helps to escape local minima and thus guides the inversion algorithm to a satisfactory result. This study uses a back-propagation algorithm to calculate the initial estimate, which significantly accelerates the rate of convergence and improves the accuracy of the standard DBIM approach. The results of this method are compared with zero initialization and Born-approximated initialization. For comparison, weak as well as strong scattering profiles of synthetic and experimental dataset are considered. The results suggest that the proposed method provides a significant improvement in terms of computing cost and efficiency. Furthermore, the proposed technique has the potential to successfully push the limits of reconstructible contrast.

The progressions in the field of wireless technology can be highly attributed to the development of antennas, which can access high data rates, provide significant gain and uniform radiation characteristics. One such antenna called the Vivaldi antenna has attracted the utmost attention of the researchers owing to its high gain, wide bandwidth, low cross-polarization, and stable radiation characteristics. Over the years, different procedures have been proposed by several researchers to improve the performance of the Vivaldi antennas. Some of these different approaches are feeding mechanisms, integration of slots, dielectric substrate selection, and radiator shape. Correspondingly, the performance of a Vivaldi antenna can be increased by including dielectric lens, parasitic patch in between two radiators, corrugations, as well as metamaterials. This paper gives a systematic identification, location, and analysis of a large number of performance enhancement methods of Vivaldi antenna design depicting their concepts, advantages, drawbacks, and applications. The principal emphasis of this article is to offer an outline of the developments in the design of Vivaldi antennas over the last few years, where the most important offerings, mostly from IEEE publications, have been emphasized. This review work aims to reveal a promising path to antenna researchers for its advancement using Vivaldi antennas.

The design of proper antenna element (AE) for microwave-based head imaging or brain stroke detection is a crucial challenge in the development process of microwave imaging (MWI) systems. The main purpose of this paper was to design, fabricate, and experimentally verify the compact and dimensions-reduced H-slot antenna suitable for the new generation of multichannel MWI system for brain stroke detection. The slot antenna type was chosen based on the numerical study of three AEs available in the literature, i.e. bow tie, slot, and waveguide-based. The study was focused on the sensitivity of the antennae (change of magnitude and phase of S21) due to dielectric parameters change or type and diameter of inclusion in a head phantom representing a hemorrhagic (HEM) or ischemic (ISCH) stroke phantom, respectively. Further, the analysis of antenna radiation to lossy medium/air and its immunity against plane wave exposure was carried out. The H-slot antenna was fabricated and experimentally verified (measurements of reflection as well as transmission coefficients) using a liquid head phantom with inserted HEM stroke phantom (both prepared as a mixture of propylene glycol, water, and salt). The phantoms were filled inside the designed two-port test system. Numerical models were validated by comparing calculated and measured S-parameters. The sensitivity of the H-slot antenna to the presence of the HEM stroke phenomenon within the phantom of the head was also demonstrated. The main advantage of the proposed H-slot antenna is its small dimensions, easy, inexpensive, and repeatable fabrication as well as mechanical stability.

This work examines the impact of the inverse chirp z-transform (ICZT) for frequency-to-time-domain conversion during image reconstruction of a pre-clinical radar-based breast microwave imaging system operating over 1–8 GHz. Two anthropomorphic breast phantoms were scanned with this system, and the delay-multiply-and-sum beamformer was used to reconstruct images of the phantoms, after using either the ICZT or the inverse discrete Fourier transform (IDFT) for frequency-to-time domain conversion. The contrast, localization error, and presence of artifacts in the reconstructions were compared. The use of the IDFT resulted in prominent ring artifacts that were not present when using the ICZT, and the use of the ICZT resulted in higher contrast between the tumor and clutter responses. In one of the phantoms, the tumor response was only visible in reconstructions that used the ICZT. The use of the ICZT evaluated with a time-step size of 11 ps resulted in the reduction of prominent artifacts present when using the IDFT and the successful identification of the tumor response in the reconstructed images.

Early detection of breast cancer is required to increase the chances of a successful treatment. However, current breast-imaging systems such as X-Ray mammography, breast ultrasound, and magnetic resonance imaging have technological limitations so that novel solutions are needed to address this major societal problem. The current paper considers ultra-wideband (UWB) microwave radiation in the frequency band from 1 to 9 GHz. Given by the non-ionizing nature of microwaves frequent check-ups are more feasible. In this work, we propose algorithms for qualitative and quantitative microwave breast imaging for a transmission-based UWB system. Based on numerical and experimental data, the performance of the algorithms has been investigated and compared. Finally, microwave images obtained during an initial patient study are discussed relative to corresponding X-ray images.

Microwave imaging is an efficient technique that can be used for the early detection of breast cancer. Therefore the current research article presents the microwave imaging of two spherical tumors (radius 4 and 5 mm) in the breast phantom by using the monostatic radar-based technique. This is carried out by using an ultra-wideband (4.9–10.9 GHz), three-layered stacked aperture coupled microstrip antenna (SACMPA) with a defected ground structure to scan the breast phantom and make near field S parameter measurements from a breast phantom. The S parameter data from different locations and at different time intervals are noted and then used in a beam-forming algorithm; Delay and Sum to process it and form a 2D image of the tumor location in the breast phantom using MATLAB.

The proposed SACMPA is a three-layered structure with overall dimensions of 37 × 43 × 4.85 mm3 that shows an impedance bandwidth of 6 GHz (4.9–10.9 GHz) and a simulated peak gain of 6.32 dB at a frequency of 9.1 GHz. The validation of S parameters and gain results are done using a Vector Network Analyzer (VNA) and an anechoic chamber. The experimental validation of the proposed microwave imaging procedure is done by allowing the SACMPA to radiate parallel to the breast phantom made from polythene (skin), petroleum jelly (fat), and wheat flour (with water as tumor) and record the S parameters on the VNA. The proposed microwave method is safe for human exposure as the antenna also shows simulated specific absorption rates of 0.271 and 1.115 W/Kg (on the breast phantom) at frequencies of 5.7 and 6.5 GHz, respectively (for 1 g of body tissue).

Microwave holography technique reconstructs a target image using recorded amplitudes and phases of the signals reflected from the target with Fast Fourier Transform (FFT)-based algorithms. The reconstruction algorithms have two or more steps of two- and three-dimensional Fourier transforms, which have a high computational load. In this paper, by neglecting the impact of target depth on image reconstruction, an efficient Fresnel-based algorithm is proposed, involving only one-step FFT for both single- and multi-frequency microwave imaging. Numerous tests have been performed to show the effectiveness of the proposed algorithm including planar and non-planar targets, using the raw data gathered by means of a scanner operating in X-band. Finally, a low-cost and high-speed hardware architecture based on fixed-point arithmetic is introduced which reconstructs the planar targets. This pipeline architecture was tested on field programmable gate arrays operating at 200 MHz clock frequency, which illustrates more than 30 times improvement in computation time compared with a computer.

Microwave and millimeter-wave reflectometry is one of the potential techniques for the diagnosis and detection of biological abnormalities, such as subcutaneous masses or cancerous tumors in human body. In this paper, a high-quality microwave sensor based on planar misrostrip resonator is designed, fabricated, and successfully tested with different kinds of biological samples. The proposed sensor has unique properties such as small size, simple fabrication, non-contact with a sample, excellent de-coupling from surroundings, and high microwave power is directly coupled into the tissue. Two experiments are performed for the detection of visible and hidden “lipoma” (fat masses), and minimum size of “lipoma” that is diagnosed by the sensor is obtained as well. In this regard, a two-dimensional image of hidden “lipomas” with amplitude contrast about 30 dB and frequency shifts contrast about 60 MHz at a λ/10 (at 13.5 GHz) stand-off distance is provided. Finally, a measurement scenario for the detection of skin cancer based on the artificial model using different layers of raw chicken with different water content is described. Results show that the proposed microscope is easy to fabricate and provide a low-cost solution for fast and accurate skin cancer detection.

Microwave ablation is widely recognized as a promising minimally invasive tool for treating cancer. Real-time monitoring of the dimensions of the ablation zone is indispensable for ensuring an effective and safe treatment. In this paper, we propose a microwave imaging algorithm for monitoring the evolution of the ablation zone. Our proposed algorithm determines the boundary of the ablation zone by exploiting the time difference of arrival (TDOA) between signals received before and during the ablation at external antennas surrounding the tissue, using the interstitial ablation antenna as the transmitter. A significant advantage of this method is that it requires few assumptions about the dielectric properties of the propagation media. Also the simplicity of the signal processing, wherein the TDOA is determined from a cross-correlation calculation, allows real-time monitoring and provides robust performance in the presence of noise. We investigate the performance of this approach for the application of breast tumor ablation. We use simulated array measurements obtained from finite-difference time-domain simulations of magnetic resonance imaging-derived numerical breast phantoms. The results demonstrate that our proposed method offers the potential to achieve millimeter-order accuracy and real-time operation in estimating the boundary of the ablation zone in heterogeneous and dispersive breast tissue.