The implementation and analysis of through wall radar systems

Through wall radar detecting, locating, imaging and tracking is a topic of current research interest in connection with law enforcement, urban area operations and search and rescue missions. Up to now, three different radar techniques are employed in through wall radar systems, including impulse through wall radar, continuous wave radar and swept frequency radar. In this thesis, we set out to give a comparison of these three kinds of through wall radar systems. First,we studied the challenges caused by the wall in through wall radar systems. Second,we implemented these three kinds of through wall radar system. In each kind of through wall radar, we developed Labview codes to realize automatic measurement and data acquisition, then we processed the data by different algorithms, including elliptic curve imaging method, Doppler-DOA method. Finally we analyzed the performance of each kind of radar system, compared the advantages and disadvantages to given a guide of through wall radar design

Wi-Fi Sensing: Applications and Challenges

Wi-Fi technology has strong potentials in indoor and outdoor sensing applications, it has several important features which makes it an appealing option compared to other sensing technologies. This paper presents a survey on different applications of Wi-Fi based sensing systems such as elderly people monitoring, activity classification, gesture recognition, people counting, through the wall sensing, behind the corner sensing, and many other applications. The challenges and interesting future directions are also highlighted

Wi-Fi Sensing: Applications and Challenges

Wi-Fi technology has strong potentials in indoor and outdoor sensing applications, it has several important features which makes it an appealing option compared to other sensing technologies. This paper presents a survey on different applications of Wi-Fi-based sensing systems such as elderly people monitoring, activity classification, gesture recognition, people counting, through the wall sensing, behind the corner sensing, and many other applications. The challenges and interesting future directions are also highlighted

Remote sensing based on hyperspectral data analysis

In remote sensing, accurate identification of far objects, especially concealed objects is difficult. In this study, to improve object detection from a distance, the hyperspecral imaging and wideband technology are employed with the emphasis on wideband radar. As the wideband data includes a broad range of frequencies, it can reveal information about both the surface of the object and its content. Two main contributions are made in this study: 1) Developing concept of return loss for target detection: Unlike typical radar detection methods which uses radar cross section to detect an object, it is possible to enhance the process of detection and identification of concealed targets using the wideband radar based on the electromagnetic characteristics conductivity, permeability, permittivity, and return loss of materials. During the identification process, collected wideband data is evaluated with information from wideband signature library which has already been built. In fact, several classes (e.g. metal, wood, etc.) and subclasses (ex. metals with high conductivity) have been defined based on their electromagnetic characteristics. Materials in a scene are then classified based on these classes. As an example, materials with high electrical conductivity can be conveniently detected. In fact, increasing relative conductivity leads to a reduction in the return loss. Therefore, metals with high conductivity (ex. copper) shows stronger radar reflections compared with metals with low conductivity (ex. stainless steel). Thus, it is possible to appropriately discriminate copper from stainless steel. 2) Target recognition techniques: To detect and identify targets, several techniques have been proposed, in particular the Multi-Spectral Wideband Radar Image (MSWRI) which is able to localize and identify concealed targets. The MSWRI is based on the theory of robust capon beamformer. During identification process, information from wideband signature library is utilized. The WB signature library includes such parameters as conductivity, permeability, permittivity, and return loss at different frequencies for possible materials related to a target. In the MSWRI approach, identification procedure is performed by calculating the RLs at different selected frequencies. Based on similarity of the calculated RLs and RL from WB signature library, targets are detected and identified. Based on the simulation and experimental results, it is concluded that the MSWRI technique is a promising approach for standoff target detection

ANALYSIS AND DESIGN OF ANTENNA PROBES FOR DETECTION / IMAGING APPLICATIONS

Analysis and Design of Antenna Probes for Detection / Imaging Applications Ayman Elboushi, Ph.D. Concordia University. As a result of increasing international terrorist threats, the need for an efficient inspecting tool has become urgent. Not only for seeing through wall applications, but also to be employed as a safe human body scanner at public places such as airports and borders. The usage of microwave and millimeter wave antennas and systems for detection / imaging applications is currently of increasing research interest targeting the enhancement of different security systems. There are many challenges facing researchers in order to develop such systems. One of the challenges is the proper design of a low cost, reduced size and efficient antenna probe to work as a scanning sensor. In this thesis, two different technology choices of antenna probes for the feasibility of constructing detection / imaging systems are investigated. The first one covers the Ultra Wide Band (UWB) range (3.1 GHz to 10.6 GHz), while the second operates over the Millimeter-Wave (MMW) range. In addition to the development of several antenna probes, two detection / imaging systems are demonstrated and showed reasonably accurate detection results. Three different UWB monopole antenna prototypes, with different radiator shapes (circular, crescent and elliptical) have been introduced. These antennas are designed using a standard printed circuit board (PCB) process to work as probing sensors in a proposed UWB detection / imaging system. In order to enhance the resolution and the detection accuracy of the probe, 4-element Balanced Antipodal Vivaldi Antenna (BAVA) array fed by 1-to-4 UWB modified Wilkinson power divider has been developed. Some successful experiments have been conducted using the proposed UWB detection / imaging system combined with the fabricated antenna probes to detect the presence of a gap between two walls made of different material types, to evaluate the gap width and to estimate the size and exact location of a hidden target between the walls. The second research theme of this thesis is to develop small-sized, light-weight and high gain MMW scanning antenna probes. For the realization of such probes, several gain enhancement techniques have been adopted, including hybridization and a multi-element array principle. Several high-gain hybrid antennas have been designed, fabricated and tested. For demonstration purposes, experiments have been carried out for detecting and imaging a small metallic coin under the jeans layer of a three-layer target emulating a human body’s covering layers. A performance comparison between a standard metallic MMW horn and hybrid microstrip patch/conical horn antenna has been made. The proposed reduced size antenna sensor shows increased efficiency compared with the bulky horn antenna. Resolution enhancement of the reconstructed image of the hidden target is implemented using a new triple-antenna MMW sensor. The triple-antenna sensor consists of three adjacent microstrip patch / conical horn antennas separated by 1.5 wavelengths at the center frequency for coupling reduction between these elements. The middle element of the sensor is used for monitoring the time domain back-reflected signal from the target under inspection, while the side elements are used for monitoring the scattered signals. By the aid of a special signal processing algorithm, an enhanced image of the concealed object can be obtained by combining the three readings of each point in the area under study. The proposed system shows a great ability for detecting a hidden target and enhances the reconstructed image resolution

Wi-Fi based people tracking in challenging environments

People tracking is a key building block in many applications such as abnormal activity detection, gesture recognition, and elderly persons monitoring. Video-based systems have many limitations making them ineffective in many situations. Wi-Fi provides an easily accessible source of opportunity for people tracking that does not have the limitations of video-based systems. The system will detect, localise, and track people, based on the available Wi-Fi signals that are reflected from their bodies. Wi-Fi based systems still need to address some challenges in order to be able to operate in challenging environments. Some of these challenges include the detection of the weak signal, the detection of abrupt people motion, and the presence of multipath propagation. In this thesis, these three main challenges will be addressed. Firstly, a weak signal detection method that uses the changes in the signals that are reflected from static objects, to improve the detection probability of weak signals that are reflected from the person’s body. Then, a deep learning based Wi-Fi localisation technique is proposed that significantly improves the runtime and the accuracy in comparison with existing techniques. After that, a quantum mechanics inspired tracking method is proposed to address the abrupt motion problem. The proposed method uses some interesting phenomena in the quantum world, where the person is allowed to exist at multiple positions simultaneously. The results show a significant improvement in reducing the tracking error and in reducing the tracking delay