Active microwave sensing of the atmosphere, chapter 4

The use of active microwave systems to study atmospheric phenomena is studied. Atmospheric pollution, weather prediction, climate and weather modification, weather danger and disaster warning, and atmospheric processes and interactions are covered

Near-Surface Interface Detection for Coal Mining Applications Using Bispectral Features and GPR

The use of ground penetrating radar (GPR) for detecting the presence of near-surface interfaces is a scenario of special interest to the underground coal mining industry. The problem is difficult to solve in practice because the radar echo from the near-surface interface is often dominated by unwanted components such as antenna crosstalk and ringing, ground-bounce effects, clutter, and severe attenuation. These nuisance components are also highly sensitive to subtle variations in ground conditions, rendering the application of standard signal pre-processing techniques such as background subtraction largely ineffective in the unsupervised case. As a solution to this detection problem, we develop a novel pattern recognition-based algorithm which utilizes a neural network to classify features derived from the bispectrum of 1D early time radar data. The binary classifier is used to decide between two key cases, namely whether an interface is within, for example, 5 cm of the surface or not. This go/no-go detection capability is highly valuable for underground coal mining operations, such as longwall mining, where the need to leave a remnant coal section is essential for geological stability. The classifier was trained and tested using real GPR data with ground truth measurements. The real data was acquired from a testbed with coal-clay, coal-shale and shale-clay interfaces, which represents a test mine site. We show that, unlike traditional second order correlation based methods such as matched filtering which can fail even in known conditions, the new method reliably allows the detection of interfaces using GPR to be applied in the near-surface region. In this work, we are not addressing the problem of depth estimation, rather confining ourselves to detecting an interface within a particular depth range

Radar signature characterization from wind turbine scattering

textThe growth in the number of wind farms has raised significant concerns in the radar community due to their potential interference on radar systems. The motion of the turbine blades creates unwanted Doppler clutter that can interfere in the tracking of moving targets. Large turbine structures can also produce electromagnetic shadows that may make observing objects behind a wind farm difficult. Detailed characterization of the clutter is the first step towards effective mitigation techniques. The goal of this dissertation research is to gain a better understanding of the dynamic radar signatures resulting from scattering by wind turbines. First, the scattering characteristics of turbines in the presence of ground surface are studied. Image theory in conjunction with a shooting-and-bouncing ray code, Ahilo, is used to carry out the dynamic signature simulation. The observed features in the simulation are corroborated with laboratory model measurements. Second, the effects of higher order motions of a turbine undergoing rotation on the radar signatures are investigated and characterized. Mathematical models for the motions are proposed and used to simulate the joint time-frequency and inverse synthetic aperture radar characteristics of the turbine undergoing these motions. The motions are studied for an isolated turbine as well as for a turbine rotating above a ground. Selected motions are corroborated by laboratory model measurements. Next, a method to remove the dynamic clutter produced by wind turbines is presented. A physics-based basis is constructed to model the radar backscattering from a wind turbine. This basis is used in conjunction with the matching pursuit algorithm to iteratively remove the Doppler clutter due to wind turbines. The algorithm is tested using radar return generated using Ahilo. Finally, radar features of wind turbines are simulated and studied in the HF (high frequency) band. The features are presented in the range-Doppler plane for single as well as arrays of turbines. Doppler aliasing due to the limited pulse repetition frequency of HF radars is examined. Shadowing characteristics of arrays of turbines are simulated and analyzed. Electromagnetic modeling details including effects of thin-wire modeling, non-conducting turbine components, and the presence of a conducting ground surface are discussed.Electrical and Computer Engineerin

Final Report DE-EE0005380: Assessment of Offshore Wind Farm Effects on Sea Surface, Subsurface and Airborne Electronic Systems

Offshore wind energy is a valuable resource that can provide a significant boost to the US renewable energy portfolio. A current constraint to the development of offshore wind farms is the potential for interference to be caused by large wind farms on existing electronic and acoustical equipment such as radar and sonar systems for surveillance, navigation and communications. The US Department of Energy funded this study as an objective assessment of possible interference to various types of equipment operating in the marine environment where offshore wind farms could be installed. The objective of this project was to conduct a baseline evaluation of electromagnetic and acoustical challenges to sea surface, subsurface and airborne electronic systems presented by offshore wind farms. To accomplish this goal, the following tasks were carried out: (1) survey electronic systems that can potentially be impacted by large offshore wind farms, and identify impact assessment studies and research and development activities both within and outside the US, (2) engage key stakeholders to identify their possible concerns and operating requirements, (3) conduct first-principle modeling on the interactions of electromagnetic signals with, and the radiation of underwater acoustic signals from, offshore wind farms to evaluate the effect of such interactions on electronic systems, and (4) provide impact assessments, recommend mitigation methods, prioritize future research directions, and disseminate project findings. This report provides a detailed description of the methodologies used to carry out the study, key findings of the study, and a list of recommendations derived based the findings

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Detection Strategies and Intercept Metrics for Intra-Pulse Radar-Embedded Communications

This thesis presents various detection strategies and intercept metrics to evaluate and design an intra-pulse radar-embedded communication system. This system embeds covert communication symbols in masking interference provided by the reflections of a pulsed radar emission. This thesis considers the case where the communicating device is a transponder or tag present in an area that is illuminated by a radar. The radar is considered to be the communication receiver. As with any communication system, performance (as measured by reliability and data rate) should be maximized between the tag and radar. However, unlike conventional communication systems, the symbols here should also have a low-probability of intercept (LPI). This thesis examines the trade-offs associated with the design of a practical radar-embedded communication system. A diagonally-loaded decorrelating receiver is developed and enhanced with a second stage based on the Neyman-Pearson criterion. For a practical system, the communication symbols will likely encounter multipath. The tag may then use a pre-distortion strategy known as time-reversal to improve the signal-to-noise ratio at the radar receiver thereby enhancing communication performance. The development of several intercept metrics are shown and the logic behind the design evolutions are explained. A formal analysis of the processing gain by the desired receiver relative to the intercept receivers is given. Finally, simulations are shown for all cases, to validate the design metrics

Technical approaches, chapter 3, part E

Radar altimeters, scatterometers, and imaging radar are described in terms of their functions, future developments, constraints, and applications

The Case for Combining a Large Low-Band Very High Frequency Transmitter With Multiple Receiving Arrays for Geospace Research: A Geospace Radar

We argue that combining a high‐power, large‐aperture radar transmitter with several large‐aperture receiving arrays to make a geospace radar—a radar capable of probing near‐Earth space from the upper troposphere through to the solar corona—would transform geospace research. We review the emergence of incoherent scatter radar in the 1960s as an agent that unified early, pioneering research in geospace in a common theoretical, experimental, and instrumental framework, and we suggest that a geospace radar would have a similar effect on future developments in space weather research. We then discuss recent developments in radio‐array technology that could be exploited in the development of a geospace radar with new or substantially improved capabilities compared to the radars in use presently. A number of applications for a geospace radar with the new and improved capabilities are reviewed including studies of meteor echoes, mesospheric and stratospheric turbulence, ionospheric flows, plasmaspheric and ionospheric irregularities, and reflection from the solar corona and coronal mass ejections. We conclude with a summary of technical requirements

Additional applications and related topics, chapter 4, part B

Satellite mounted microwave instruments and their use to measure surface pressure are investigated. Data cover instrument accuracy, atmospheric transmission, and meteorological parameter determinations

Through-the-Wall Imaging and Multipath Exploitation

We consider the problem of using electromagnetic sensing to estimate targets in complex environments, such as when they are hidden behind walls and other opaque objects. The often unknown electromagnetic interactions between the target and the surrounding area, make the problem challenging. To improve our results, we exploit information in the multipath of the objects surrounding both the target and the sensors. First, we estimate building layouts by using the jump-diffusion algorithm and employing prior knowledge about typical building layouts. We also take advantage of a detailed physical model that captures the scattering by the inner walls and efficiently utilizes the frequency bandwidth. We then localize targets hidden behind reinforced concrete walls. The sensing signals reflected from the targets are significantly distorted and attenuated by the embedded metal bars. Using the surface formulation of the method of moments, we model the response of the reinforced walls, and incorporate their transmission coefficients into the beamforming method to achieve better estimation accuracy. In a related effort, we utilize the sparsity constraint to improve electromagnetic imaging of hidden conducting targets, assuming that a set of equivalent sources can be substituted for the targets. We derive a linear measurement model and employ l1 regularization to identify the equivalent sources in the vicinity of the target surfaces. The proposed inverse method reconstructs the target shape in one or two steps, using single-frequency data. Our results are experimentally verified. Finally, we exploit the multipath from sensor-array platforms to facilitate direction finding. This in contrast to the usual approach, which utilizes the scattering close to the targets. We analyze the effect of the multipath in a statistical signal processing framework, and compute the Cramer-Rao bound to obtain the system resolution. We conduct experiments on a simple array platform to support our theoretical approach