Learning to Detect Open Carry and Concealed Object with 77GHz Radar

Detecting harmful carried objects plays a key role in intelligent surveillance systems and has widespread applications, for example, in airport security. In this paper, we focus on the relatively unexplored area of using low-cost 77GHz mmWave radar for the carried objects detection problem. The proposed system is capable of real-time detecting three classes of objects - laptop, phone, and knife - under open carry and concealed cases where objects are hidden with clothes or bags. This capability is achieved by the initial signal processing for localization and generating range-azimuth-elevation image cubes, followed by a deep learning-based prediction network and a multi-shot post-processing module for detecting objects. Extensive experiments for validating the system performance on detecting open carry and concealed objects have been presented with a self-built radar-camera testbed and collected dataset. Additionally, the influence of different input formats, factors, and parameters on system performance is analyzed, providing an intuitive understanding of the system. This system would be the very first baseline for other future works aiming to detect carried objects using 77GHz radar.Comment: 12 page

Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool

Accelerated by the increasing attention drawn by 5G, 6G, and Internet of Things applications, communication and sensing technologies have rapidly evolved from millimeter-wave (mmWave) to terahertz (THz) in recent years. Enabled by significant advancements in electromagnetic (EM) hardware, mmWave and THz frequency regimes spanning 30 GHz to 300 GHz and 300 GHz to 3000 GHz, respectively, can be employed for a host of applications. The main feature of THz systems is high-bandwidth transmission, enabling ultra-high-resolution imaging and high-throughput communications; however, challenges in both the hardware and algorithmic arenas remain for the ubiquitous adoption of THz technology. Spectra comprising mmWave and THz frequencies are well-suited for synthetic aperture radar (SAR) imaging at sub-millimeter resolutions for a wide spectrum of tasks like material characterization and nondestructive testing (NDT). This article provides a tutorial review of systems and algorithms for THz SAR in the near-field with an emphasis on emerging algorithms that combine signal processing and machine learning techniques. As part of this study, an overview of classical and data-driven THz SAR algorithms is provided, focusing on object detection for security applications and SAR image super-resolution. We also discuss relevant issues, challenges, and future research directions for emerging algorithms and THz SAR, including standardization of system and algorithm benchmarking, adoption of state-of-the-art deep learning techniques, signal processing-optimized machine learning, and hybrid data-driven signal processing algorithms...Comment: Submitted to Proceedings of IEE

Frequency-modulated continuous-wave LiDAR compressive depth-mapping

We present an inexpensive architecture for converting a frequency-modulated continuous-wave LiDAR system into a compressive-sensing based depth-mapping camera. Instead of raster scanning to obtain depth-maps, compressive sensing is used to significantly reduce the number of measurements. Ideally, our approach requires two difference detectors. % but can operate with only one at the cost of doubling the number of measurments. Due to the large flux entering the detectors, the signal amplification from heterodyne detection, and the effects of background subtraction from compressive sensing, the system can obtain higher signal-to-noise ratios over detector-array based schemes while scanning a scene faster than is possible through raster-scanning. %Moreover, we show how a single total-variation minimization and two fast least-squares minimizations, instead of a single complex nonlinear minimization, can efficiently recover high-resolution depth-maps with minimal computational overhead. Moreover, by efficiently storing only $2m$ data points from $m<n$ measurements of an $n$ pixel scene, we can easily extract depths by solving only two linear equations with efficient convex-optimization methods

Remote Detection of Concealed Guns and Explosives

A reliable method of remotely detecting concealed guns and explosives attached to the human body is of great interest to governments and security forces throughout the world. This thesis describes the development and trials of a new remote non-imaging concealed threat detection method using active millimetre wave radar using the microwave and mmwave frequencies bands 14 – 40 and 75 – 110 GHz (Ku, K, Ka and W). The method is capable of not only screening for concealed objects, like the current generation of concealed object detectors, but also of differentiating between mundane and threat objects. The areas focused upon during this investigation were: identifying the impact of different commonly worn fabrics as barriers to detection; consulting with end users about their requirements and operational needs; a comparison of different frequency bands for the detection of guns and explosives; exploring the effects of polarisation on object detection; a performance comparison of different detection schemes using Artificial Neural Networks; improving existing data acquisition systems and prototyping of a real-time capture system

Millimetre wave imaging for concealed target detection

PhDConcealed weapon detection (CWD) has been a hot topic as the concern about pub- lic safety increases. A variety of approaches for the detection of concealed objects on the human body based on earth magnetic ¯eld distortion, inductive magnetic ¯eld, acoustic and ultrasonic, electromagnetic resonance, MMW (millimetre wave), THz, Infrared, x-ray technologies have been suggested and developed. Among all of them, MMW holographic imaging is considered as a promising approach due to the relatively high penetration and high resolution that it can o®er. Typical concealed target detection methods are classi¯ed into 2 categories, the ¯rst one is a resonance based target identi¯cation technique, and the second one is an imaging based system. For the former, the complex natural resonance (CNR) frequencies associated with a certain target are extracted and used for identi¯cation, but this technique has an issue of high false alarm rate. The microwave/millimetre wave imaging systems can be categorized into two types: passive systems and active sys- tems. For the active microwave/millimetre wave imaging systems, the microwave holographic imaging approach was adopted in this thesis. Such a system can oper- ate at either a single frequency or multiple frequencies (wide band). An active, coherent, single frequency operation millimetre wave imaging system based on the theory of microwave holography was developed. Based on literature surveys and ¯rst hand experimental results, this thesis aims to provide system level parame- ter determination to aid the development of a target detection imager. The goal is approached step by step in 7 chapters, with topics and issues addressed rang- ing from reviewing the past work, ¯nding out the best candidate technology, i.e. the MMW holographic imaging combined with the resonance based target recog- i nition technique, the construction of the 94 GHz MMW holographic prototype imager, experimental trade-o® investigation of system parameters, imager per- formance evaluation, low pro¯le components and image enhancement techniques, feasibility investigation of resonance based technique, to system implementation based on the parameters and results achieved. The task set forth in the beginning is completed by coming up with an entire system design in the end.

NASA SBIR abstracts of 1990 phase 1 projects

The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number

Application of quantum magnetometers to security and defence screening

Over recent years the sensitivity of alkali-metal vapour magnetometers has been demonstrated to surpass that of even Superconducting Quantum Interference Devices (SQUIDs), the current commercial gold standard in laboratory weak- field magnetometry sensing. Here we present a proof-of-principle approach to building an RF atomic magnetometer which is robust, portable, tunable, non-invasive and operable at room temperature in an unshielded environment. In view of these characteristics, we discuss the potential application of alkali-metal magnetometry in imaging concealed objects, non-destructive evaluation of the structural integrity of metallic objects (e.g. pipelines and aircraft), and detection of rotating motors. We present a cost-effective approach to operating an atomic magnetometer in a Magnetic Induction Tomography (MIT) modality, to non-invasively map the conductivity of conductive objects concealed by conductive materials remotely and in real time. This is achieved by measuring the secondary eld in the subject due to eddy currents circulating as a result of application of a tunable radio-frequency oscillating eld, which overcomes the bandwidth and sensitivity limitations of using coils for sensing as in conventional MIT. In addition, we demonstrate the use of the atomic magnetometer for the remote detection of DC and AC electric motors with an improved response compared with a commercial fluxgate magnetometer in the sub 50 Hz regime (particularly detection down to 15 Hz). Its capability for non-invasive measurement through concrete walls is established, with potential for use in industrial monitoring and detection of illicit activity. Finally, the possibility of detection of submerged targets or for the atomic magnetometer to be mounted on submarine vehicles was explored. Promising results were obtained, but further investigation is required in this environment to establish this as a viable marine detector

Ultrasound Imaging

This book provides an overview of ultrafast ultrasound imaging, 3D high-quality ultrasonic imaging, correction of phase aberrations in medical ultrasound images, etc. Several interesting medical and clinical applications areas are also discussed in the book, like the use of three dimensional ultrasound imaging in evaluation of Asherman's syndrome, the role of 3D ultrasound in assessment of endometrial receptivity and follicular vascularity to predict the quality oocyte, ultrasound imaging in vascular diseases and the fetal palate, clinical application of ultrasound molecular imaging, Doppler abdominal ultrasound in small animals and so on

mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor

Target material sensing in non-invasive and ubiquitous contexts plays an important role in various applications. Recently, a few wireless sensing systems have been proposed for material identification. In this paper, we introduce mm-CUR, A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles using a Millimeter-Wave Sensor. This system eliminates the need for individual note inspection and pinpoints the location of counterfeit notes within the bundle. We use Frequency Modulated Continuous Wave (FMCW) radar sensors to classify different counterfeit currency bundles on a tabletop setup. To extract informative features for currency detection from FMCW signals, we construct a Radio Frequency Snapshot (RFS) and build signal scalogram representations that capture the distinct patterns of currency received from different currency bundles. We refine the RFS by eliminating multi-path interference, and noise cancellation and apply high pass filters for mitigating the smearing effect with the continuous wavelet transform (CWT). To broaden the usage of mm-CUR, we built a transferable learning model that yields robust detection results in different scenarios. The classification results demonstrated that the proposed counterfeit currency detection system can detect counterfeit notes in 100-note bundles with an accuracy greater than 93%. Compared to the standard CNN and DNN methods, the proposed mm-CUR model showed superior performance in distinguishing each bundle data, even for a limited-size dataset