An efficient imaging algorithm for GNSS-R bi-static SAR

Global Navigation Satellite System Reflectometry (GNSS-R) based Bi-static Synthetic Aperture Radar (BSAR) is becoming more and more important in remote sensing, given its low power, low mass, low cost, and real-time global coverage capability. Due to its complex configuration, the imaging for GNSS-R BSAR is usually based on the Back-Projection Algorithm (BPA), which is very time consuming. In this paper, an efficient and general imaging algorithm for GNSS-R BSAR is presented. A Two Step Range Cell Migration (TSRCM) correction is firstly applied. The first step roughly compensates the RCM and Doppler phase caused by the motion of the transmitter, which simplifies the SAR data into the quasi-mono-static case. The second step removes the residual RCM caused by the motion of the receiver using the modified frequency scaling algorithm. Then, a cubic phase perturbation operation is introduced to equalize the Doppler frequency modulation rate along the same range cell. Finally, azimuth phase compensation and geometric correction are completed to obtain the focused SAR image. A simulation and experiment are conducted to demonstrate the feasibility of the proposed algorithm, showing that the proposed algorithm is more efficient than the BPA, without causing significant degradation in imaging quality

Active and Passive Multi-Sensor Radar Imaging Techniques Exploiting Spatial Diversity

The work here presented reports several innovative SAR and ISAR radar imaging techniques exploiting the spatial diversity offered by multi-sensor systems in order to improve the performance with respect to the conventional, single channel cases. Both the cases of dedicated transmitters and exploitation of opportunity transmitters are considered

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

Advanced Techniques for Ground Penetrating Radar Imaging

Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives

Optical scattering for security applications

Laser Surface Authentication (LSA) has emerged in recent years as a potentially disruptive tracking and authentication technology. A strong need for such a solution in a variety of industries drove the implementation of the technology faster than the scientific understanding could keep up. The drive to miniaturise and simplify, the need to be robust against real-world problems like damage and misuse, and not least, intellectual curiosity, make it clear that a firmer scientific footing is important as the technology matures. Existing scattering and biometric work are reviewed, and LSA is introduced as a technology. The results of field-work highlight the restrictions which are encountered when the technology is applied. Analysis of the datasets collected in the trial provide, first, an indication of the performance of LSA under real-world conditions and, second, insight into the potential shortcomings of the technique. Using the particulars of the current sensor’s geometry, the LSA signal is characterised. Measurements are made of the decorrelation of the signature with linear and rotational offsets, and it is concluded that while surface microstructure has a strong impact on the rate of decorrelation, this dependency is not driven by the surface’s feature size. A new series of experiments examine that same decorrelation for interference effects with different illumination conditions, and conclude that laser speckle is not an adequate explanation for the phenomenon. The results of this experimental work inform a mathematical description of LSA based on a combination of existing bi-static scattering models used in physics and ray-tracing, which is implemented numerically. The results of the model are found to be a good fit to experimental work, and new predictions are made about LSA