UWB Pulse Radar for Human Imaging and Doppler Detection Applications

We were motivated to develop new technologies capable of identifying human life through walls. Our goal is to pinpoint multiple people at a time, which could pay dividends during military operations, disaster rescue efforts, or assisted-living. Such system requires the combination of two features in one platform: seeing-through wall localization and vital signs Doppler detection. Ultra-wideband (UWB) radar technology has been used due to its distinct advantages, such as ultra-low power, fine imaging resolution, good penetrating through wall characteristics, and high performance in noisy environment. Not only being widely used in imaging systems and ground penetrating detection, UWB radar also targets Doppler sensing, precise positioning and tracking, communications and measurement, and etc. A robust UWB pulse radar prototype has been developed and is presented here. The UWB pulse radar prototype integrates seeing-through imaging and Doppler detection features in one platform. Many challenges existing in implementing such a radar have been addressed extensively in this dissertation. Two Vivaldi antenna arrays have been designed and fabricated to cover 1.5-4.5 GHz and 1.5-10 GHz, respectively. A carrier-based pulse radar transceiver has been implemented to achieve a high dynamic range of 65dB. A 100 GSPS data acquisition module is prototyped using the off-the-shelf field-programmable gate array (FPGA) and analog-to-digital converter (ADC) based on a low cost solution: equivalent time sampling scheme. Ptolemy and transient simulation tools are used to accurately emulate the linear and nonlinear components in the comprehensive simulation platform, incorporated with electromagnetic theory to account for through wall effect and radar scattering. Imaging and Doppler detection examples have been given to demonstrate that such a “Biometrics-at-a-glance” would have a great impact on the security, rescuing, and biomedical applications in the future

Evaluating a breast tumor monitoring vest with flexible UWB antennas and realistic phantoms:a proof-of-concept study

Abstract. The introduction provides an overview of the global significance of breast cancer as a health concern and the limitations of existing breast cancer screening methods. It introduces the concept of microwave-based breast cancer monitoring and highlights the promising findings from a previous research paper. The objective of the master thesis is presented, which is to develop and evaluate a self-monitoring vest equipped with UWB antennas and channel analysis to overcome the limitations of current screening methods and enable regular breast cancer monitoring from home. The "Background and Literature Review," provides a comprehensive overview of the relevant topics related to microwave techniques for breast cancer detection. It starts by discussing the anatomy of the female breast, highlighting the importance of understanding its structure for effective tumor detection. The section then delves into the microwave properties of the human breast, elucidating the interactions between microwaves and breast tissue. The basic principle of microwave channel analysis is explained, emphasizing its significance in detecting breast tumors. Furthermore, the advantages of microwave-based tumor detection methods are explored, showcasing their potential for improved breast cancer screening. Various microwave techniques used in breast cancer detection, including microwave tomography and radar-based UWB microwave imaging, are discussed, along with different self-monitoring vests integrated with UWB antennas. This section serves as a foundation for the subsequent chapters of the thesis, providing a comprehensive background and literature review to support the research and development of the practical self-monitoring vest for early detection of small-sized breast tumors. The "Preparation of Tissue Phantoms" section in the master’s thesis explores the comprehensive methodology for creating tissue phantoms that replicate the dielectric properties of various human tissues. While the section primarily focuses on fat tissue, it also acknowledges the existence of other phantom types. The outlined approach involves careful ingredient selection, formulation development, fabrication techniques, and stability evaluation for the creation of skin, muscle, fat, tumor, and gland tissue phantoms. By following these procedures, researchers can successfully produce tissue phantoms that closely mimic the properties of real human tissues. These phantoms serve as essential tools for investigating microwave-based applications in medical diagnostics and provide a reliable and versatile platform for further research in the field. The third section discusses the assembly of heterogeneous breast phantoms used for evaluating the performance of the tumor detection vest. The phantoms consisted of outer and inner molds, with the outer molds resembling the shape of a prone human breast. Two breast density types, representing very dense and less dense breasts, were used. For the dense breast phantoms, liquid fat material was solidified in the outer molds, and a glandular liquid was poured into the inner mold, with tumors inserted and covered with additional glandular liquid. For the less dense breast phantoms, fat liquid was solidified in the outer molds, and cylindrical glandular molds were inserted. A skin layer and muscle layer were added to complete the assembly, accurately simulating the composition and structure of a breast. This realistic breast phantom assembly allowed for accurate measurements and evaluation of the vest’s performance under different breast density conditions, contributing to breast imaging research and development. The "Monitoring Vest" section discusses the antennas used in the tumor detection vest and the design of two different vest versions. Antenna1 is a UWB monopole antenna with a flexible laminate substrate, while Antenna2 is a textile-based version of Antenna1. Antenna3 has a Kapton-based substrate and larger dimensions. The combination of these antennas ensures accurate tumor detection in various breast conditions. The section also highlights the measurement and comparison of the S11 parameter for the PCB antenna in free space and when placed on the skin, emphasizing the impact of the skin on antenna performance. The section concludes by describing the design of the vests, including the arrangement of pockets and the use of RF cables for connection. The careful design and implementation of the vests and antenna placement ensure accurate measurements and reliable performance evaluation. The results section of the study shows that the presence of tumors in breast tissue leads to a noticeable decrease in channel attenuation. The higher dielectric properties of tumors cause additional reflections and diffraction, affecting signal propagation within the breast. These changes in channel characteristics are influenced by factors such as tumor size, breast density, and antenna configuration. The study demonstrates the detectability of tumors and provides valuable insights for developing effective tumor detection systems in different breast tissue scenarios. In this master thesis, a prototype of a breast tumor monitoring vest utilizing UWB flexible antennas was developed and evaluated. The research demonstrated the effectiveness of the vest in detecting breast tumors, even as small as 1cm, by leveraging the distinct characteristics of radio channels among multiple on-body antennas embedded in the vest. Higher frequencies in the 7–8 GHz range showed improved resolution and contrast in relative permittivity, enhancing the accuracy of tumor detection. The development of tissue phantoms played a crucial role, enabling reliable experiments to mimic human tissues. Integration of advanced AI algorithms and 6G technology holds promise for enhancing diagnostic capabilities and revolutionizing healthcare. Overall, the breast tumor monitoring vest shows potential for widespread implementation in breast health checks, home monitoring, and wireless healthcare systems

Optimized intelligent classifier for early breast cancer detection using ultra-wide band transceiver

Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary to remove the cancerous cells and prolong life. For early breast cancer detection, it is crucial to propose a robust intelligent classifier with statistical feature analysis that considers parameter existence, size, and location. This paper proposes a novel Multi-Stage Feature Selection with Binary Particle Swarm Optimization (MSFS–BPSO) using Ultra-Wideband (UWB). A collection of 39,000 data samples from non-tumor and with tumor sizes ranging from 2 to 7 mm was created using realistic tissue-like dielectric materials. Subsequently, the tumor models were inserted into the heterogeneous breast phantom. The breast phantom with tumors was imaged and represented in both time and frequency domains using the UWB signal. Consequently, the dataset was fed into the MSFS–BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. Feature selection using Analysis of Variance (ANOVA) is able to distinguish between class-correlated data. Finally, the optimum feature subset was selected using a Probabilistic Neural Network (PNN) classifier with the Binary Particle Swarm Optimization (BPSO) method. The research findings found that the MSFS–BPSO method has increased classification accuracy up to 96.3% and given good dependability even when employing an enormous data sample

Ultra-Wideband (UWB) Antenna Sensor Based Microwave Breast Imaging: A Review

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

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Computational polarimetric microwave imaging

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure

Cancer Detection Using Advanced UWB Microwave Technology

Medical diagnosis and subsequent treatment efficacy hinge on innovative imaging modalities. Among these, Microwave Imaging (MWI) has emerged as a compelling approach, offering safe and cost-efficient visualization of the human body. This comprehensive research explores the potential of the Huygens principle-based microwave imaging algorithm, specifically focusing on its prowess in cancer, lesion, and infection detection. Extensive experimentation employing meticulously crafted phantoms validates the algorithm’s robustness. In the context of lung infections, this study harnesses the power of Huygens-based microwave imaging to detect lung-COVID-19 infections. Employing Microstrip and horn antennas within a frequency range of 1 to 5 GHz and a multi-bistatic setup in an anechoic chamber, the research utilizes phantoms mimicking human torso dimensions and dielectric properties. Notably, the study achieves a remarkable detection capability, attaining a signal-to-clutter ratio of 7 dB during image reconstruction using S21 signals.A higher SCR ratio indicates better contrast and clarity of the detected inclusion, which is essential for reliable medical imaging. It is noteworthy that this achievement is realized in free space without necessitating coupling liquid, underscoring the algorithm’s practicality. Furthermore, the research delves into the validation of Huygens Principle (HP)-based microwave imaging in detecting intricate lung lesions. Utilizing a meticulously designed multi-layered phantom with characteristics closely mirroring human anatomy, the study spans frequency bands from 0.5 GHz to 3 GHz within an anechoic chamber. The outcomes are compelling, demonstrating consistent lesion detection within reconstructed images. Impressively, the signal-to-clutter ratio post-artifact removal surges to 13.4 dB, affirming the algorithm’s potential in elevating medical imaging precision. To propel the capabilities of MWI further, this research unveils a novel device: 3D microwave imaging rooted in Huygens principle. Leveraging MammoWave device’s capabilities, the study ventures into 3D image reconstruction. Dedicated phantoms housing 3D structured inclusions, each embodying distinct dielectric properties, serve as the experimental bedrock. Through an intricate interplay of data acquisition and processing, the study attains a laudable feat: seamless 3D visualization of inclusions across various z-axis planes, accompanied by minimal dimensional error not exceeding 7.5%. In a parallel exploration, spiral-like measurement configurations enter the spotlight. These configurations, meticulously tailored along the z-axis, yield promising results. The research unveils an innovative approach to reducing measurement time while safeguarding imaging fidelity. Notably, spiral-like measurements achieve a notable 50% reduction in measurement time, albeit with slight trade-offs. Signal-to-clutter ratios experience a modest reduction, and there is a minor increase in dimensional analysis error, which remains within the confines of 3.5%. The research findings serve as a testament to MWI’s efficacy across diverse medical domains. The success in lung infection and lesion detection underscores its potential impact on medical diagnostics. Moreover, the foray into 3D imaging and the strategic exploration of measurement configurations lay the foundation for future advancements in microwave imaging technologies. As a result, the outcomes of this research promise to reshape the landscape of accurate and efficient medical imaging modalities

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium