Ultra-wideband Radar Imaging Research Articles

ULTRA WIDE BAND RADAR BASED BREAST CANCER DETECTION USING STACKED PATCH AND WIDE SLOT ANTENNA

A wide slot UWB antenna is used for the detection of breast cancer .This method works on the principle of ultra wide band radar imaging technique. In this paper comparing the performance of both stacked patch and wide slot antenna used for the purpose of breast cancer detection. Calculating specific absorption rate of both antenna, when it is placed in a normal tissue and tumors tissue, and comparing its results .And also measuring certain parameters of both simulated and measured results. From this comparative study its clear that wide slot UWB antenna has excellent performance in this UWB frequency range. And also wide slot antenna is three times smaller than stacked patch antenna.

A PREPROCESSING FILTER FOR MULTISTATIC MICROWAVE BREAST IMAGING FOR ENHANCED TUMOUR DETECTION

Ultra Wideband Radar imaging has shown promising results in the detection of small tumours within low to medium density human breasts. A wide range of beamforming algorithms has been presented in several recent studies with good tumour localization capabilities, but most of these sufier a deterioration in performance with an increase in breast tissue density. In this paper, a preprocessing fllter is used to compensate for path-dependent attenuation and phase efiects, in conjunction with a range of existing data-dependent and data-independent confocal microwave imaging algorithms. Results indicate that this data preprocessing improves the performance of all beamformers, enabling detection and accurate localization of multiple tumours in mild to moderately dense human breasts. The proposed framework is tested on 3D anatomically accurate numerical breast models and the performance is evaluated across a range of appropriate metrics.

Target detection and reconstruction for compressive multiple-input, multiple-output ultra-wideband noise radar imaging

We propose a sample selection method for multiple-input, multiple-output ultra-wideband noise radar imaging using compressive sensing. The proposed sample selection is based on comparing the norm values of candidates among the potential received signal and selecting the largest M samples among N per antenna to obtain selection diversity. Moreover, we propose an adaptive weighting allocation that improves reconstruction accuracy of compressive sensing by maximizing the mutual information between target echoes and transmitted signals. This weighting scheme is applicable to both sample selection schemes, a conventional random sampling and the proposed selection. Further, the weighting allocation with the knowledge of recovery error is proposed for more practical scenarios. Simulations show that the proposed selection and weighting allocation enhance multiple target detection probability and reduce normalized mean square error.

Prefiltered Beamforming for Early-Stage Breast Cancer Detection

Ultrawideband radar imaging has been extensively investigated as a potential alternative to X-ray mammography and has shown promising results in the detection of small tumors within dielectrically homogeneous breast tissue. A range of confocal microwave imaging algorithms has been reported in the literature, showing good tumor detection capabilities, but most of these algorithms suffer significant deterioration in performance with increased amounts of fibro-glandular tissue in the breast. This letter proposes an improved beamformer based on a prefiltering approach to compensate for dispersion and phase effects in a dielectrically heterogeneous breast. The use of prefiltering is shown to improve on conventional beamformer performance and enables detection of multiple scatterers in dense breast tissue. The proposed improved beamformer is tested on 3-D anatomically and dielectrically accurate finite-difference time-domain (FDTD) breast models and the corresponding performance of the beamformer is evaluated across a range of appropriate metrics.

Robust and Accurate Ultrasound 3-D Imaging Algorithm Incorporating Adaptive Smoothing Techniques

Many researchers have proposed ultrasound imaging techniques for product inspection; however, most of these techniques are aimed at detecting the existence of flaws in products. The acquisition of an accurate three-dimensional image using ultrasound has the potential to be a useful product inspection tool. In this paper we apply the Envelope algorithm, which was originally proposed for accurate UWB (Ultra Wide-Band) radar imaging systems, to ultrasound imaging. We show that the Envelope algorithm results in image deterioration, because it is difficult for ultrasound measurements to achieve high signal to noise (S/N) ratio values as a result of a high level of noise and interference from the environment. To reduce errors, we propose two adaptive smoothing techniques that effectively stabilize the estimated image produced by the Envelope algorithm. An experimental study verifies that the proposed imaging algorithm has accurate 3-D imaging capability with a mean error of 6.1µm, where the transmit center frequency is 2.0MHz and the S/N ratio is 23dB. These results demonstrate the robustness of the proposed imaging algorithm compared with a conventional Envelope algorithm.

Method for the Three-Dimensional Imaging of a Moving Target Using an Ultra-Wideband Radar with a Small Number of Antennas

Ultra wideband (UWB) radar is considered a promising technology to complement existing camera-based surveillance systems because, unlike cameras, it provides excellent range resolution. Many of the UWB radar imaging algorithms are based on large-scale antenna arrays that are not necessarily practical because of their complexity and high cost. To resolve this issue, we previously developed a two-dimensional radar imaging algorithm that estimates unknown target shapes and motion using only three antennas. In this paper, we extend this method to obtain three-dimensional images by estimating three-dimensional motions from the outputs of five antennas. Numerical simulations confirm that the proposed method can estimate accurately the target shape under various conditions.

Accurate Image Expansion Method Using Range Points Based Ellipse Fitting for UWB Imaging Radar

Ultra-wideband (UWB) pulse radars have a definite advantage in high-range resolution imaging, and are suitable for short-range measurements, particularly at disaster sites or security scenes where optical sensors are rarely suitable because of dust or strong backlighting. Although we have already proposed an accurate imaging algorithm called Range Points Migration (RPM), its reconstructible area is too small to identify the shape of an object if it is far from the radar and the size of the aperture is inadequate. To resolve this problem, this paper proposes a novel image expansion method based on ellipse extrapolation; it enhances extrapolation accuracy by deriving direct estimates of the observed range points distributed in the data space. Numerical validation shows that the proposed method accurately extrapolates part of the target boundary, even if an extremely small region of the target boundary is obtained by RPM. key words: UWB pulse radars, range points migration, ellipse fitting, image expansion

Two-Dimensional Ultrawideband Radar Imaging of a Target With Arbitrary Translation and Rotation

Indoor target detection and imaging technologies hold great interest for security surveillance systems. The ultrawideband (UWB) radar is promising because it can complement conventional camera-based systems. However, conventional UWB radar imaging systems are costly and impractical because they require large antenna arrays for acceptable resolution. This paper proposes a low-cost UWB radar imaging method using the motion of a target. The method employs five antennas for estimating the motion of a target, including its rotation, to obtain an image. Previous work deals only with a target in translation without rotation, which makes the method difficult to apply in practice. The proposed method, an extension of such previous methods, obtains an accurate image for an elliptical or distorted nonelliptical target with arbitrary translation and rotation. Numerical simulation and experimental results show that the proposed method is capable of accurately estimating motions and shapes.

Super-Resolution UWB Radar Imaging Algorithm Based on Extended Capon With Reference Signal Optimization

Near field radar employing ultrawideband (UWB) signals with its high range resolution has great promise for various sensing applications. It enables non-contact measurement of precision devices with specular surfaces like an aircraft fuselage and wing, or a robotic sensor that can identify a human body in invisible situations. As one of the most promising radar algorithms, the range points migration (RPM) was proposed. This achieves fast and accurate surface extraction, even for complex-shaped objects, by eliminating the difficulty of connecting range points. However, in the case of a more complex shape whose variation scale is less than a pulsewidth, it still suffers from image distortion caused by multiple interference signals with different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon method, known as frequency domain interferometry (FDI). This algorithm combines reference signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The results obtained from numerical simulations and an experiment with bi-static extension of the RPM prove that super-resolution UWB radar imaging is accomplished by the combination between the RPM and the extended Capon methods, even for an extremely complex-surface target including edges.

UWB MICROWAVE IMAGING FOR BREAST CANCER DETECTION --- EXPERIMENTS WITH HETEROGENEOUS BREAST PHANTOMS

The paper describes pulse-based ultra-wideband (UWB) radar microwave imaging experiments for breast cancer detection using breast phantoms with dielectric properties mimicking the human breast. Three homogeneous and seven heterogeneous breast phantoms are designed with a series of dielectric permittivity and variability and are used in tumor detection experiments. The experiments are conducted in time-domain with pulse generator and real-time oscilloscope.

An Imaging Algorithm of a Target with Arbitrary Motion for Ultra Wide-Band Radar with a Small Number of Antennas

UWB (ultra wide-band) pulse radar is a promising candidate for surveillance systems. The fast SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm is deployed in the application of UWB pulse radar in fields that require real-time operations. However, since the SEABED algorithm uses signals received at multiple locations, this method either needs to scan antennas or to install many antennas. Such systems are inevitably costly and unrealistic for applications such as surveillance. To overcome this problem, a revised SEABED algorithm that estimates unknown target shape based on target motion using only a pair of fixed antennas was developed. However, the method cannot be used when the target moves arbitrarily because it assumes the target motion is parallel to the baseline of the pair of antennas. In this paper, we propose a new UWB radar imaging algorithm that is applicable even for targets with arbitrary motion. The proposed method introduces another antenna which is added to the pair of antennas used in the revised SEABED, and estimates unknown target motion based on the target surface using the three antennas. Next, the proposed method applies the SEABED imaging algorithm to the estimated motion and obtains the target image. Some numerical simulations establishes that the proposed method can accurately estimate the target shape even under severe conditions.

2-Dimensional Accurate Imaging with UWB Radar Using Indoor Multipath Echoes for a Target in Shadow Regions

UWB (Ultra Wide-Band) pulse radar is promising for surveillance systems because it has an outstanding high range-resolution. To realize an accurate UWB radar imaging system, we propose a new approach that employs multipath echoes from a target in an indoor environment. Using multipath echoes, the proposed system can accurately estimate images, even for targets in a shadow region where the targets are out of sight of the antenna. We apply a simple interferometry technique using the multiple mirror image antennas generated by multipath propagation. We find that this simple method also produces many undesired false image points. To tackle this issue, we also propose an effective false image reduction algorithm to obtain a clear image. Numerical simulations verify that most of the false image points are removed and the target shape is accurately estimated.

SPIKING NEURAL NETWORKS FOR BREAST CANCER CLASSIFICATION USING RADAR TARGET SIGNATURES

Recent studies have shown that the dielectric properties of normal breast tissue vary considerably. This dielectric heterogeneity may mean that the identiflcation of tumours using Ultra Wideband Radar imaging alone may be quite di-cult. Signiflcantly, since the dielectric properties of benign tissue were shown to overlap with those of malignant, breast tumour classiflcation using traditional UWB Radar imaging algorithms could be very problematic. Rather than simply examining the dielectric properties of scatterers within the breast, other features of scatterers must be used for classiflcation. Radar Target Signatures have been previously used to classify tumours due to the signiflcant difierence in size, shape and surface texture between benign and malignant tumours. This paper investigates Spiking Neural Networks (SNNs) applied as a novel tumour classiflcation method. This paper will describe the creation of 3D tumour models, the generation of representative backscatter, the application of a feature extraction method and the use of SNNs to classify tumours as either benign or malignant. The performance of the SNN classifler is shown to outperform existing UWB Radar classiflcation algorithms.

DATA INDEPENDENT RADAR BEAMFORMING ALGORITHMS FOR BREAST CANCER DETECTION

Ultra wideband (UWB) Microwave imaging is one of the most promising emerging imaging technologies for breast cancer detection, and is based on the dielectric contrast between normal and cancerous tissues at microwave frequencies. UWB radar imaging involves illuminating the breast with a microwave pulse and re∞ected signals are used to determine the presence and location of signiflcant dielectric scatterers, which may be representative of cancerous tissue within the breast. Beamformers are used to spatially focus the re∞ected signals and to compensate for path dependent attenuation and phase efiects. While these beamforming algorithms have often been evaluated in isolation, variations in experimental conditions and metrics prompts the assessment of the beamformers on common anatomically and dielectrically representative breast models in order to efiectively compare the performance of each. This paper seeks to investigate the following beamforming algorithms: Monostatic and Multistatic Delay- And-Sum (DAS), Delay-Multiply-And-Sum (DMAS) and Improved Delay-And-Sum (IDAS). The performance of each beamformer is evaluated across a range of appropriate metrics.

Ultrawideband (UWB) Radar Imaging of Building Interior: Measurements and Predictions

In this paper, we explore using the ultrawideband radar technology for sensing through-the-wall imaging. We conducted a field experiment with our in-house designed impulse-based radar, in which a stripmap synthetic aperture radar (SAR) geometry was employed in mapping an abandoned army barrack building with a large footprint area. The images obtained from two sides of the building were combined in order to obtain the full building layout, including the interior structure. Computer simulations performed with Xpatch, a physical optics-based ray tracing code, are used to explain some phenomena observed in the measured SAR images.

Code-Division Multiple Transmission for High-Speed UWB Radar Imaging With an Antenna Array

The ultrawideband (UWB) radar is a promising high-resolution 3-D imaging technique for near targets. We have developed a high-speed imaging algorithm, SEABED, for a UWB pulse radar, a key real-time imaging technology. When the algorithm is applied to UWB, antenna scanning for data acquisition takes significantly longer than calculating the SEABED algorithm itself. This presents a serious problem for the real-time application of UWB radar. In this paper, we use pseudonoise (PN) sequences as the transmitting waveforms, while the original work on the SEABED algorithm assumed impulsive short-wave pulses. Using PN sequences enables us to simultaneously transmit signals with multiple antennas, eliminating the need to scan antennas. We demonstrate that the proposed radar system works well using random sequences to suppress direct waves, which is critical in achieving high speeds for imaging.

A high‐directive bowtie radar antenna with a pyramidal reflector for ultra wideband radar imaging applications

AbstractWe propose a novel bowtie radar antenna with a pyramidal reflector, which shows low return loss and high directional gain, capable of covering the whole ultra wideband (UWB) frequency band. The measured return loss is less than −10 dB over 3.0–11.7 GHz, and the radiation pattern is unidirectional with a high front‐to‐back ratio for UWB radar imaging applications. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 387–390, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24043

Estimation Method of Quasi-wavefronts for UWB Radar Imaging with LMS Filter and Fractional Boundary Scattering Transform

UWB (Ultra Wide-Band) radar has a variety of applications including security surveillance systems. The SEABED algorithm is a fast imaging method for UWB radar, that uses a reversible transform between the real and data spaces (1). We introduce an intermediate space between the real and data spaces (2). Curves in the intermediate space can be smooth, and can be used to extract quasi-wavefronts (the equi-phase surface). In this paper, we use LMS (Least-Mean-Square) fllters in the intermediate space for imaging arbitrary target shapes.

Ultrawideband radar imaging system for biomedical applications

Ultrawideband (UWB) (3–10GHz) radar imaging systems offer much promise for biomedical applications such as cancer detection because of their good penetration and resolution characteristics. The underlying principle of UWB cancer detection is a significant contrast in dielectric properties, which is estimated to be greater than 2:1 between normal and cancerous tissue, compared to a few-percent contrast in radiographic density exploited by x rays. This article presents a feasibility study of the UWB imaging of liver cancer tumors, based on the frequency-dependent finite difference time domain method. The reflection, radiation, and scattering properties of UWB pulses as they propagate through the human body are studied. The reflected and back-scattered electromagnetic energies from cancer tumors inside the liver are also investigated. An optimized, ultrawideband antenna was designed for near field operation, allowing for the reduction of the air-skin interface. It will be placed on the fat-liver tissue phantom with a malignant tumor stimulant. By performing an incremental scan over the phantom and removing early time artifacts, including reflection from the antenna ends, images based on the back-scattered signal from the tumor can be constructed. This research is part of our effort to develop a UWB cancer detection system with good detection and localization properties.

Ultra-wideband synthetic aperture radar time-frequency representation image formation

In ultra-wideband synthetic aperture radar (UWB SAR) imaging, scatterers often perform the frequency- and aspect angle-dependent reflectivity characteristic, which is usually neglected in traditional imaging processing. A novel UWB SAR time-frequency representation image formation (TFRIF) is proposed to retrieve the frequency- and aspect angle-dependent information, which is valuable in target detection. Based on the TFRIF, two fusion schemes are studied: pixel level fusion (PLF) and decision level fusion (DLF). Based on the analytical expressions, it is concluded that TFRIF can extract the reflectivity pattern information with high precision and little sacrifice of the spatial resolutions. Quantitative analyses of spatial resolutions and detectability improvement of the proposed fusion schemes are tested on airborne UWB SAR data. The real data results validate the proposed TFRIF and its associated PLF and DLF schemes.