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Radio-frequency sensing and communication systems which use a waveform for more than one function offer the promise of improved spectral efficiency and streamlined hardware requirements. Control of orbital angular momentum (OAM) may be used to increase data-rates and improve radar sensitivity to certain chiral targets. This paper presents finite-difference time-domain simulations which model a gigahertz-frequency OAM radar capable of transmitting information via OAM-mode modulation. The unique chirality-detection capability of OAM radar is demonstrated, as well as simple information transmission. Simulation scope and radar specifications are designed with an eye toward developing a dual function ground penetrating radar (GPR) with OAM mode control. 

Ultra-wideband (UWB) ground penetrating radar (GPR) is an effective, widely used tool for detection and mapping of buried targets. However, traditional ground penetrating radar systems struggle to resolve and identify congested target configurations and irregularly shaped targets. This is a significant limitation for many municipalities who seek to use GPR to locate and image underground utility pipes. This research investigates the implementation of orbital angular momentum (OAM) control in an UWB GPR, with the goal of addressing these limitations. Control of OAM is a novel technique which leverages an additional degree of freedom offered by spatially structured helical waveforms. This paper examines several free-space and buried target configurations to determine the ability of helical OAM waveforms to improve detectability and distinguishability of buried objects including those with symmetric, asymmetric, and chiral geometries. Microwave OAM can be generated using a uniform circular array (UCA) of antennas with phase delays applied according to azimuth angle. Here, a four-channel network analyzer transceiver is connected to a UCA to enable UWB capability. The characteristic phase delays of OAM waveforms are implemented synthetically via signal processing. The viability demonstrated with the method opens design and analysis degrees of freedom for penetrating radar that may help with discerning challenging targets, such as buried landmines and wires. 

Location and identification of subterranean infrastructure is crucial for managing and maintaining urban infrastructure and utility, and locating subsurface hazards. Low-frequency oscillating magnetic fields suffer less attenuation due to propagating media than ground penetrating radar. Here, electronically-geared, rotating neodymium magnets project oscillating magnetic fields which are manipulated to provide object identification from rapid analysis of dynamic magnetometer data. Ferromagnetic materials interact directly with the rotating magnetic field. Eddy currents, which induce a counter-propagating magnetic field, are generated in conductive, non-ferromagnetic materials. Two applications are highlighted by preliminary experiments: discrimination between copper, aluminum and steel pipes, and improved detection of buried explosive devices. 

Multistatic GPR has the advantages of reducing survey time and leverages more comprehensive data collection. Traditionally in multistatic GPR data processing, the 2D Bscan image obtained from each receive antenna are simply stacked for 3D image reconstructions. However, such approach is typically inadequate as the multistatic GPR receivers are mounted with spatial offsets, causing back-scattering signals from the same target to have differing time of arrivals. For proper fusion of multistatic GPR data, migration methods that consider the transmitters and receivers spatial offset and data variations among different receiving antennas may be employed. In this study, the back-projection algorithm (BPA) is investigated. The algorithm consists of determining the wave travel path and associated travel time, and projecting the corresponding signal value back into space domain. Furthermore, antenna radiation pattern is incorporated. The BPA enables scatter shape reconstruction and is prone to parallel computing. For validation, multistatic GPR 3D tomographic image reconstruction is successfully applied to laboratory data. 

This paper explores using Orbital Angular Momentum (OAM) controlled electromagnetic waves for enhanced ground penetrating radar (GPR) imaging and detection. A macroscopic interpretation of OAM is propagating waves with vortex-shaped wave fronts. At the photon level OAM appears as a quantum degree of freedom with integer quanta of angular momentum added to each photon. This is in addition to Spin Angular Momentum (SAM). The use of OAM in GPR has at least two potential advantages. The vortex shape may enable better discernment of cylindrical versus non-cylindrical buried objects. At the quantum level entanglement of OAM with other quantum degrees of freedom may enable enhanced imaging, such as the ghost imaging of objects that produce weak signal returns. The results include experiments that demonstrate the generation and reception of EM waves with a circular pattern of antennas operating as phased arrays to produce vortex-shaped waves at frequencies and dimensions typical of conventional GPRs. 

The development of modern cities heavily relies on the availability and quality of underground utilities that provide drinking water, sewage, electric power, and telecommunication services to sus- tain its growing population. However, the information of localiza- tion and condition of subterranean infrastructures is generally not readily available, especially in areas with congested pipes, which impacts urban development, as poorly documented pipes may be hit during construction, affecting services and causing costly de- lays. Furthermore, aging components are prone to failure and may lead to resources waste or the interruption of services. Ground penetrating radar (GPR) is a promising remote sensing technique that has been recently used for mapping and assessment of under- ground infrastructure. However, current commercial GPR survey systems are designed with wheel-encoders or GPS for positioning. Wheel-encoder based GPR surveys are restrained to linear-route only, preventing the use of GPR for accurate localization of city wide underground infrastructure inspection. While GPS signal is degraded in urban canyons and unavailable in city tunnels. In this work, we present a new GPR system integration with augmented reality (AR) based positioning that can overcome the limitations of current GPR systems to enable arbitrary-route scanning with a high fidelity. It has the potential for automation of GPR survey and integration with AR smartphone applications that could be used for better planning in urban development.