Through Wall Imaging Radar Antenna with a Focus on Opening New Research Avenues

This review paper is an effort to develop insight into the development in antennas for through wall imaging radar application. Review on literature on antennas for use in through wall imaging radar, fulfilling one or more requirements/specifications such as ultrawide bandwidth, stable and high gain, stable unidirectional radiation pattern, wide scanning angle, compactness ensuring portability and facilitating real-time efficient and simple imaging is presented. The review covers variants of Vivaldi, Bow tie, Horn, Spiral, Patch and Magneto-electric dipole antennas demonstrated as suitable antennas for the through wall imaging radar application. With an aim to open new research avenues for making better through wall imaging radar antenna, review on relevant compressive reflector antennas, surface integrated waveguide antennas, plasma antennas, metamaterial antennas and single frequency dynamically configurable meta-surface antennas are incorporated. The review paper brings out possibilities of designing an optimum through wall imaging radar antenna and prospects of future research on the antenna to improve radiation pattern and facilitate overall simple and efficient imaging by the through wall imaging radar

Wall Compensation for Ultra Wideband Applications

Due to their low frequency contents, ultra wideband (UWB) signals have the ability to penetrate walls and obstacles. As the signal propagates through these obstacles, it gets attenuated, slows down, and gets dispersed. This paper demonstrates wall compensation for through-wall imaging, localization and communication receiver design purposes by first characterizing wave propagation through various building materials in the UWB frequency range. Knowledge of the walls obtained from the wall characterization is used to estimate and correct the position accuracy of a target object located behind the walls using three proposed methods namely; constant amplitude and delay (CDL), frequency dependent data (FFD), and data fitting methods (FIT). The obtained results indicated relatively acceptable measure of wall compensation for the three methods. Results from such work provide insight on how to develop algorithms for effective target position estimation in imaging and localization applications. They are also useful for channel modelling and link budget analysis

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

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

Real time Adaptive Approach for Hidden Targets Shape Identification using through Wall Imaging System

In Through-wall Imaging (TWI) system, shape-based identification of the hidden target behind the wall made of any dielectric material like brick, cement, concrete, dry plywood, plastic and Teflon, etc. is one of the most challenging tasks. However, it is very important to understand that the performance of TWI systems is limited by the presence of clutter due to the wall and also transmitted frequency range. Therefore, the quality of obtained image is blurred and very difficult to identify the shape of targets. In the present paper, a shape-based image identification technique with the help of a neural network and curve-fitting approach is proposed to overcome the limitation of existing techniques. A real time experimental analysis of TWI has been carried out using the TWI radar system to collect and process the data, with and without targets. The collected data is trained by a neural network for shape identification of targets behind the wall in any orientation and then threshold by a curve-fitting method for smoothing the background. The neural network has been used to train the noisy data i.e. raw data and noise free data i.e. pre-processed data. The shape of hidden targets is identified by using the curve fitting method with the help of trained neural network data and real time data. The results obtained by the developed technique are promising for target identification at any orientation

Fuzzy Logic and Singular Value Decomposition based Through Wall Image Enhancement

Singular value decomposition based through wall image enhancement is proposed which is capable of discriminating target, noise and clutter signals. The overlapping boundaries of clutter, noise and target signals are separated using fuzzy logic. Fuzzy inference engine is used to assign weights to different spectral components. K-means clustering is used for suitable selection of fuzzy parameters. Proposed scheme significantly works well for extracting multiple targets in heavy cluttered through wall images. Simulation results are compared on the basis of mean square error, peak signal to noise ratio and visual inspection

An Extended Virtual Aperture Imaging Model for Through-the-wall Sensing and Its Environmental Parameters Estimation

Through-the-wall imaging (TWI) radar has been given increasing attention in recent years. However, prior knowledge about environmental parameters, such as wall thickness and dielectric constant, and the standoff distance between an array and a wall, is generally unavailable in real applications. Thus, targets behind the wall suffer from defocusing and displacement under the conventional imag¬ing operations. To solve this problem, in this paper, we first set up an extended imaging model of a virtual aperture obtained by a multiple-input-multiple-output array, which considers the array position to the wall and thus is more applicable for real situations. Then, we present a method to estimate the environmental parameters to calibrate the TWI, without multiple measurements or dominant scatter¬ers behind-the-wall to assist. Simulation and field experi¬ments were performed to illustrate the validity of the pro¬posed imaging model and the environmental parameters estimation method

Modified Low Rank Approximation for Detection of Weak Target by Noise space Exploitation in Through Wall Imaging

Low dielectric materials referred as weak targets are very difficult to detect behind the wall in through wall imaging (TWI) due to strong reflections from wall. TWI Experimental data collected for low dielectric target behind the wall and transceiver on another side of the wall. Recently several researchers are using low-rank approximation (LRA) for reduction of random noise in the various data. Explore the possibilities of using LRA for TWI data for improving the detection of low dielectric material. A novel approach using modification of LRA with exploiting the noise subspace in singular value decomposition (SVD) to detect weak target behind the wall is introduced. LRA consider data has low rank in f-x domain for noisy data, local windows are implemented in LRA approach to satisfy the principle assumptions required by the LRA algorithm itself. Decomposed TWI data in the noise space of the SVD to detect the weak target adaptively. Results for modified LRA for detection of weak target behind the wall are very encouraging over LRA