Microwave Tomography With LSTM-Based Processing of the Scattered Field

The quantitative inspection of unknown targets or bodies by means of microwave tomography requires a proper modeling of the field scattered by the structures under test, which in turn depends on several factors related to the adopted antennas and measurement configuration. In this article, a multifrequency tomographic approach in nonconstant-exponent Lebesgue spaces is enhanced by a preliminary step that processes the measured scattered field with a neural network based on long short-term memory cells. In the considered cases, this approach allows dealing with measurements in three-dimensional settings obtained with non-ideal antennas and measurement points, while retaining a canonical two-dimensional formulation of the inverse problem. The adopted data-driven model is trained with a set of simulations of cylindrical targets performed with a finite-difference time domain method, considering a simplified bistatic measurement configuration as an initial case study. The inversion procedure is then validated with numerical simulations involving cylindrical and spherical structures

An improved approach for RSSI-based only calibration-free real-time indoor localization on IEEE 802.11 and 802.15.4 wireless networks

Assuming a reliable and responsive spatial contextualization service is a must-have in IEEE 802.11 and 802.15.4 wireless networks, a suitable approach consists of the implementation of localization capabilities, as an additional application layer to the communication protocol stack. Considering the applicative scenario where satellite-based positioning applications are denied, such as indoor environments, and excluding data packet arrivals time measurements due to lack of time resolution, received signal strength indicator (RSSI) measurements, obtained according to IEEE 802.11 and 802.15.4 data access technologies, are the unique data sources suitable for indoor geo-referencing using COTS devices. In the existing literature, many RSSI based localization systems are introduced and experimentally validated, nevertheless they require periodic calibrations and significant information fusion from different sensors that dramatically decrease overall systems reliability and their effective availability. This motivates the work presented in this paper, which introduces an approach for an RSSI-based calibration-free and real-time indoor localization. While switched-beam array-based hardware (compliant with IEEE 802.15.4 router functionality) has already been presented by the author, the focus of this paper is the creation of an algorithmic layer for use with the pre-existing hardware capable to enable full localization and data contextualization over a standard 802.15.4 wireless sensor network using only RSSI information without the need of lengthy offline calibration phase. System validation reports the localization results in a typical indoor site, where the system has shown high accuracy, leading to a sub-metrical overall mean error and an almost 100% site coverage within 1 m localization error

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

CubiCal: a fast radio interferometric calibration suite exploiting complex optimisation

The advent of the Square Kilometre Array and its precursors marks the start of an exciting era for radio interferometry. However, with new instruments producing unprecedented quantities of data, many existing calibration algorithms and implementations will be hard-pressed to keep up. Fortunately, it has recently been shown that the radio interferometric calibration problem can be expressed concisely using the ideas of complex optimisation. The resulting framework exposes properties of the calibration problem which can be exploited to accelerate traditional non-linear least squares algorithms. We extend the existing work on the topic by considering the more general problem of calibrating a Jones chain: the product of several unknown gain terms. We also derive specialised solvers for performing phase-only, delay and pointing error calibration. In doing so, we devise a method for determining update rules for arbitrary, real-valued parametrisations of a complex gain. The solvers are implemented in an optimised Python package called CubiCal. CubiCal makes use of Cython to generate fast C and C++ routines for performing computationally demanding tasks whilst leveraging multiprocessing and shared memory to take advantage of modern, parallel hardware. The package is fully compatible with the measurement set, the most common format for interferometer data, and is well integrated with Montblanc - a third party package which implements optimised model visibility prediction. CubiCal's calibration routines are applied successfully to both simulated and real data for the field surrounding source 3C147. These tests include direction-independent and direction dependent calibration, as well as tests of the specialised solvers. Finally, we conduct extensive performance benchmarks and verify that CubiCal convincingly outperforms its most comparable competitor

Simplified equivalent modelling of electromagnetic emissions from printed circuit boards

Characterization of electromagnetic emissions from printed circuit boards (PCBs) is an important issue in electromagnetic compatibility (EMC) design and analysis of modern electronic systems. This thesis is focused on the development of a novel modelling and characterization methodology for predicting the electromagnetic emissions from PCBs in both free space and closed environment. The basic idea of this work is to model the actual PCB radiating source with a dipole-based equivalence found from near-field scanning. A fully automatic near-field scanning system and scanning methodology are developed that provide reliable and sufficient data for the construction of equivalent emission models of PCB structures. The model of PCB emissions is developed that uses an array of equivalent dipoles deduced from magnetic near-field scans. Guidelines are proposed for setting the modelling configuration and parameters. The modelling accuracy can be improved by either improving the measurement efforts or using the mathematical regularization technique. An optimization procedure based on genetic algorithms is developed which addresses the optimal configuration of the model. For applications in closed environments, the equivalent model is extended to account for the interactions between the PCB and the enclosure. The extension comprises a dielectric layer and a ground plane which explicitly represent the necessary electromagnetic passive properties of a PCB. This is referred to as the dipole-dielectric-conducting plane (DDC) model and provides a completely general representation which can be incorporated into electromagnetic simulation or analysis tools. The modelling and characterization methodology provides a useful tool for efficient analysis of issues related to EMC design of systems with PCBs as regards predicting electromagnetic emissions in both free space and closed environment. The proposed method has significant advantages in tackling realistic problems because the equivalent models greatly reduce the computational costs and do no rely on the knowledge of detailed PCB structure

Seismic Waves

The importance of seismic wave research lies not only in our ability to understand and predict earthquakes and tsunamis, it also reveals information on the Earth's composition and features in much the same way as it led to the discovery of Mohorovicic's discontinuity. As our theoretical understanding of the physics behind seismic waves has grown, physical and numerical modeling have greatly advanced and now augment applied seismology for better prediction and engineering practices. This has led to some novel applications such as using artificially-induced shocks for exploration of the Earth's subsurface and seismic stimulation for increasing the productivity of oil wells. This book demonstrates the latest techniques and advances in seismic wave analysis from theoretical approach, data acquisition and interpretation, to analyses and numerical simulations, as well as research applications. A review process was conducted in cooperation with sincere support by Drs. Hiroshi Takenaka, Yoshio Murai, Jun Matsushima, and Genti Toyokuni

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

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