900 research outputs found

    Mitigation of Through-Wall Distortions of Frontal Radar Images using Denoising Autoencoders

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    Radar images of humans and other concealed objects are considerably distorted by attenuation, refraction and multipath clutter in indoor through-wall environments. While several methods have been proposed for removing target independent static and dynamic clutter, there still remain considerable challenges in mitigating target dependent clutter especially when the knowledge of the exact propagation characteristics or analytical framework is unavailable. In this work we focus on mitigating wall effects using a machine learning based solution -- denoising autoencoders -- that does not require prior information of the wall parameters or room geometry. Instead, the method relies on the availability of a large volume of training radar images gathered in through-wall conditions and the corresponding clean images captured in line-of-sight conditions. During the training phase, the autoencoder learns how to denoise the corrupted through-wall images in order to resemble the free space images. We have validated the performance of the proposed solution for both static and dynamic human subjects. The frontal radar images of static targets are obtained by processing wideband planar array measurement data with two-dimensional array and range processing. The frontal radar images of dynamic targets are simulated using narrowband planar array data processed with two-dimensional array and Doppler processing. In both simulation and measurement processes, we incorporate considerable diversity in the target and propagation conditions. Our experimental results, from both simulation and measurement data, show that the denoised images are considerably more similar to the free-space images when compared to the original through-wall images

    Accuracy Evaluation of Ultrawideband Time Domain Systems for Microwave Imaging

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    We perform a theoretical analysis of the measurement accuracy of ultrawideband time domain systems. The theory is tested on a specific ultrawideband system and the analytical estimates of measurement uncertainty are in good agreements with those obtained by means of simulations. The influence of the antennas and propagation effects on the measurement accuracy of time domain near field microwave imaging systems is discussed. As an interesting application, the required measurement accuracy for a breast cancer detection system is estimated by studying the effect of noise on the image reconstructions. The results suggest that the effects of measurement errors on the reconstructed images are small when the amplitude uncertainty and phase uncertainty of measured data are less than 1.5 dB and 15 degrees, respectively

    Microwave Photonic Imaging Radar with a Millimeter-level Resolution

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    Microwave photonic radars enable fast or even real-time high-resolution imaging thanks to its broad bandwidth. Nevertheless, the frequency range of the radars usually overlaps with other existed radio-frequency (RF) applications, and only a centimeter-level imaging resolution has been reported, making them insufficient for civilian applications. Here, we propose a microwave photonic imaging radar with a millimeter-level resolution by introducing a frequency-stepped chirp signal based on an optical frequency shifting loop. As compared with the conventional linear-frequency modulated (LFM) signal, the frequency-stepped chirp signal can bring the system excellent capability of anti-interference. In an experiment, a frequency-stepped chirp signal with a total bandwidth of 18.2 GHz (16.9 to 35.1 GHz) is generated. Postprocessing the radar echo, radar imaging with a two-dimensional imaging resolution of ~8.5 mm×\times~8.3 mm is achieved. An auto-regressive algorithm is used to reconstruct the disturbed signal when a frequency interference exists, and the high-resolution imaging is sustained

    Hardware architectures for compact microwave and millimeter wave cameras

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    Millimeter wave SAR imaging has shown promise as an inspection tool for human skin for characterizing burns and skin cancers. However, the current state-of-the-art in microwave camera technology is not yet suited for developing a millimeter wave camera for human skin inspection. Consequently, the objective of this dissertation has been to build the necessary foundation of research to achieve such a millimeter wave camera. First, frequency uncertainty in signals generated by a practical microwave source, which is prone to drift in output frequency, was studied to determine its effect on SAR-generated images. A direct relationship was found between the level of image distortions caused by frequency uncertainty and the product of frequency uncertainty and distance between the imaging measurement grid and sample under test. The second investigation involved the development of a millimeter wave imaging system that forms the basic building block for a millimeter wave camera. The imaging system, composed of two system-on-chip transmitters and receivers and an antipodal Vivaldi-style antenna, operated in the 58-64 GHz frequency range and employed the ω-k SAR algorithm. Imaging tests on burnt pigskin showed its potential for imaging and characterizing flaws in skin. The final investigation involved the development of a new microwave imaging methodology, named Chaotic Excitation Synthetic Aperture Radar (CESAR), for designing microwave and millimeter wave cameras at a fraction of the size and hardware complexity of previous systems. CESAR is based on transmitting and receiving from all antennas in a planar array simultaneously. A small microwave camera operating in the 23-25 GHz frequency was designed and fabricated based on CESAR. Imaging results with the camera showed it was capable of basic feature detection for various applications --Abstract, page iv

    Development of a Real-time Ultra-wideband See Through Wall Imaging Radar System

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    Ultra-Wideband (UWB) See-Through-Wall (STW) technology has emerged as a musthave enabling technology by both the military and commercial sectors. As a pioneer in this area, we have led the research in addressing many of the fundamental STW questions. This dissertation is to investigate and resolve a few hurdles in advancing this technology, and produce a realizable high performance STW platform system, which will aid the STW community to find the ultimate answer through experimental and theoretical work. The architectures of a realizable STW imaging system are thoroughly examined and studied. We present both a conceptual system based on RF instruments and a standalone real-time system based on custom design, which utilize reconfigurable design architecture and allows scaling down/up to a desired UWB operating frequency with little difficulty. The systems will serve as a high performance platform for STW study and other related UWB applications. Along the way to a complete STW system, we have developed a simplified transmission line model for wall characteristic prediction; we have developed a scalable synthetic aperture array including both the RF part and the switch control/synchronization part; we have proposed a cost-effective and efficient UWB data acquisition method for real-time STW application based on equivalent-time sampling method. The measurement results reported here include static image formation and tracking moveable targets behind the wall. Even though digital signal processing to generate radar images is not the focus of this research, simple methods for image formation have been implemented and results are very encouraging

    Respiratory Rate Monitoring in Clinical Environments with a Contactless Ultra-Wideband Impulse Radar-based Sensor System

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    Respiratory rate is an extremely important but poorly monitored vital sign for medical conditions. Current modalities for respiratory monitoring are suboptimal. This paper presents a proof of concept of a new algorithm using a contactless ultra-wideband (UWB) impulse radar-based sensor to detect respiratory rate in both a laboratory setting and in a two-subject case study in the Emergency Department. This novel approach has shown correlation with manual respiratory rate in the laboratory setting and shows promise in Emergency Department subjects. In order to improve respiratory rate monitoring, the UWB technology is also able to localize subject movement throughout the room. This technology has potential for utilization both in and out of the hospital environments to improve monitoring and to prevent morbidity and mortality from a variety of medical conditions associated with changes in respiratory rate

    Advanced Dielectric Anomaly Detection for Non-Destructive Fruit Inspection Using Electromagnetic Microwave Technique

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    This paper presents a comprehensive investigation into the application of an electromagnetic microwave technique combined with the dielectric anomaly approach algorithm for the non-destructive inspection of fruits. The proposed antenna configuration comprises eight elements arranged in a circular array, enabling the collection of signals scattered by objects, specifically fruits, placed in their path. The collected data undergoes a series of processing steps, including Fast Fourier Transform, covariance matrix estimation, eigenvalue and eigenvector computation, and spatial spectrum construction. The dielectric anomaly algorithm is then applied to detect defects in the fruits. The study covers five different types of fruits, both healthy and defective, and gathers essential dielectric properties. Furthermore, a novel hybrid IQR method is introduced for outlier detection in the dielectric data. The results demonstrate the effectiveness of the proposed methodology in providing valuable insights into the internal structures of fruits and detecting anomalies, contributing to the enhancement of quality assessment in fruit inspection processes

    Design and Time-domain Analysis of Antenna Array for UWB Imaging Application.

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    PhDUWB technology has been developing in imaging applications. For security imaging applications, it is vital to detect and image metallic targets concealed in bag at airports, subway stations or other public environments. To reduce the cost of the deployment of X-ray machines, a novel UWB imaging system has been developed, including the design of the UWB rotating antenna array, the design of RF circuits and the implementation of the two-dimensional delay-and-sum (DAS) image reconstruction method. Two types of UWB antennas, the circular-edge antipodal Vivaldi antenna and the corrugated balanced antipodal Vivaldi antenna (BAVA) have been designed and studied in both frequency domain and time domain. Both of them can work across UWB frequency range from 3.1 GHz to 10.6 GHz, and have directional radiation patterns. The corrugated BAVA with smaller physical size has been improved to have a relative high gain around 7 dBi across the operating frequency range. It also causes less distortion to signals in the time domain. So the corrugated BAVA is used as the antenna element in the UWB rotating antenna array. The UWB rotating antenna array comprises one central transmitting antenna and four receiving antennas. The receiving antennas, which rotate around the central transmitting antenna, are placed side-by-side on a straight arm. The equivalent antenna elements in space are increased by the rotation of the antenna array. The two-dimensional image reconstruction method has been developed based on DAS algorithm. This UWB imaging system can detect and reconstruct the image of the single and pairs of metallic targets concealed in bag. The smallest single target with the size of 4 cm × 4 cm × 1 cm can be reconstructed in images at a maximum distance of 30 cm away from the system. It can achieve 6 cm in cross-range resolution and 15 cm in down-range resolution. Therefore, the feasibility of the proposed UWB imaging system has been proved
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