A Multi-Frequency Investigation of Air-To-Ground Urban Propagation Using a GPU-based Ray Launching Algorithm

Unmanned Aerial Vehicles (UAV), also known as “drones”, are attracting increasing attention as enablers for many technical applications and services, and this trend is likely to continue in the next future. When compared to conventional terrestrial communications, those making use of UAVs as base- or relay-stations can definitely be more useful and flexible in reaction to specific events, like natural disasters and terrorist attacks. Among the many and different fields, UAV enabled communications emerge as one of the most promising solutions for next-generation mobile networks, with a special focus on the extension of coverage and capacity of mobile radio networks. Motivated by the air-to-ground (A2G) propagation conditions which are likely to be different than those experienced by traditional ground communication systems, this paper aims at investigating the narrowband properties of the air-to-ground channel for 5G communications and beyond by means of GPU accelerated ray launching simulations. Line of sight probability as well as path loss exponent and shadowing standard deviations are analysed for different UAV flight levels, frequencies and dense urban scenarios, and for different types of on board antennas. Thanks to the flexibility of the ray approach, the role played by the different electromagnetic interactions, namely reflection, diffraction and diffuse scattering, in the air-to-ground propagation process is also investigated. Computation time is reported as well to show that designing UAV communication networks and optimising their performances in a fast and reliable manner, might avoid exhausting – multiple - measurement campaigns

A methodology for using bluetooth to measure real-time work zone travel time

This thesis seeks to provide guidance on the deployment of Bluetooth sensors for travel time measurement in work zone corridors. The investigation focuses on the detection characteristics of Class 1 and Class 2 Bluetooth devices, and how cultivating an understanding of these characteristics together with the effect of the sensor inquiry cycle length can suggest a more precise method of travel time measurement. This thesis also explores the range of detection location around a Bluetooth sensor in order to recommend a minimum corridor separation of Bluetooth sensors, and to ascertain the best method of Bluetooth travel time derivation. Finally, this thesis investigates these principles further through multiple side-fire deployments on the I-285 corridor in Atlanta, Georgia; as well as two deployments capturing several hours of active work zone travel time.MSCommittee Chair: Dr. Michael Hunter; Committee Member: Dr. Angshuman Guin; Committee Member: Dr. Randall Guensle

Comparison of Summer and Winter California Central Valley Aerosol Distributions from Lidar and MODIS Measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2008. While the PM2.5 concentration is highest in the winter, the aerosol optical depth measured from MODIS is highest in the summer. A seasonal comparison shows that PM2.5 in the winter can exceed summer PM2.5 by 55%, while summer AOD exceeds winter AOD by 43%. Higher temperatures wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not surface particulate matter monitors. Measurements of the boundary layer height from lidar instruments are necessary to incorporate satellite measurements with air quality measurements

Advanced GNSS-R instruments for altimetric and scatterometric applications

This work is the result of more than eight years during a bachelor thesis, a master thesis, and the Ph.D. thesis dedicated to the development of the Microwave Interferometric Reflectometer (MIR) instrument. It summarizes all the knowledge acquired during this time, and describes the MIR instrument as detailed as possible. MIR is a Global Navigation Satellite System - Reflectometer (GNSS-R), that is, an instrument that uses Global Navigation Satellite System (GNSS) signals scattered on the Earth's surface to retrieve geophysical parameters. These signals are received below the noise level, but since they have been spread in the frequency domain using spread-spectrum techniques, and in particular using the so-called Pseudo Random Noise (PRN) codes, it is still possible to retrieve them because of the large correlation gain achieved. In GNSS-R, two main techniques are used for this purpose: the conventional technique cGNSS-R and the interferometric one iGNSS-R, each with its pros and cons. In the former technique, the reflected signal is cross-correlated against a locally generated clean-replica of the transmitted signal. In the latter technique the reflected signal is cross-correlated with the direct one. Nowadays multiple GNSS systems coexist, transmitting narrow and wide, open and private signals. A comparison between systems, signals, and techniques in fair conditions is necessary. The MIR instrument has been designed as an airborne instrument for that purpose: the instrument has two arrays, an up-looking one, and a down-looking one, each with 19 dual-band antennas in a hexagonal distribution. The instrument is able to form 2 beams at each frequency band (L1/E1, and L5/E5A), which are pointing continuously to the desired satellites taking into account their position, as well as the instrument's position and attitude. The data is sampled and stored for later post-processing. Last but not least, MIR is auto-calibrated using similar signals to the ones transmitted by the GNSS satellites. During the instrument development, the Distance Measurement Equipment/TACtical Air Navigation (DME/TACAN) signals from the Barcelona airport threatened to disrupt the interferometric technique. These signals were also studied, and it was concluded that the use of a mitigation systems were as strongly recommended. The interferometric technique was also affected by the unwanted contribution of other satellites. The impact of these contributions was studied using real data gathered during this Ph.D. thesis. During these 8 years, the instrument was designed, built, tested, and calibrated. A field campaign was carried out in Australia between May 2018 and June 2018 to determine the instrument's accuracy in sensing soil moisture and sea altimetry. This work describes each of these steps in detail and aims to be helpful for those who decide to continue the legacy of this instrument.Este trabajo es el resultado de más de 8 años de doctorado dedicados al desarrollo del instrumento Microwave Interferometric Reflectometer (MIR). Esta tesis resume todo el conocimiento adquirido durante este tiempo, y describe el MIR lo más detalladamente posible. El MIR es un Reflectómetro de señales de Sistemas Globales de Navegación por Satélite (GNSS-R), es decir, es un instrumento que usa señales de GNSS reflejadas en la superficie de la tierra para obtener parámetros geofísicos. Estas señales son recibidas bajo el nivel de ruido, pero dado que han sido ensanchadas en el dominio frecuencial usando técnicas de espectro ensanchado, y en particular usando códigos Pseudo Random Noise (PRN), es todavía posible recibirlas debido a la elevada ganancia de correlación. En GNSS-R existen dos técnicas para este propósito: la convencional (cGNSS-R), y la interferométrica (iGNSS-R), cada una con sus pros y sus contras. En la primera se calcula la correlación cruzada de la señal reflejada y de una réplica generada del código transmitido. En la segunda técnica se calcula la correlación cruzada de la señal reflejada y de la señal directa. Hoy en día muchos sistemas GNSS coexisten, transmitiendo señales de distintos anchos de banda, algunas públicas y otras privadas. Una comparación entre sistemas, señales, y técnicas en condiciones justas es necesaria. El MIR es un instrumento aerotransportado diseñado como para ese propósito: el instrumento tiene dos arrays de antenas, uno apuntando al cielo, y otro apuntando al suelo, cada uno con 19 antenas doble banda en una distribución hexagonal. El instrumento puede formar 2 haces en cada banda frecuencial (L1/E1 y L5/E5A) que apuntan continuamente a los satélites deseados teniendo en cuenta su posición, y la posición y actitud del instrumento. Los datos son guardados para ser procesados posteriormente. Por último pero no menos importante, el MIR se calibra usando señales similares a las transmitidas por los satélites de GNSS. Durante el desarrollo del instrumento, señales del sistema Distance Measuremt Equi Distance Measurement Equipment/TACtical Air Navigation (DME/TACAN) del aeropuerto de Barcelona mostraron ser una amenaza para la técnica interferométrica. Estas señales fueron estudiadas y se concluyó que era encarecidamente recomendado el uso de sistemas de mitigación de interferencias. La técnica interferométrica también se ve afectada por las contribuciones no deseadas de otros satélites, llamado cross-talk. El impacto del cross-talk fue estudiado usando datos reales tomados durante esta tesis doctoral. A lo largo de estos 8 años el instrumento ha sido diseñado, construido, testeado y calibrado. Una campaña de medidas fue llevada a cabo en Australia entre Mayo de 2018 y Junio de 2018 para determinar la capacidad del instrumento para estimar la humedad del terreno y la altura del mar. Este documento describe cada uno de estos pasos al detalle y espera resultar útil para aquellos que decidan continuar con el legado de este instrumento.Postprint (published version

Comparison of Summer and Winter California Central Valley Aerosol Distributions from Lidar and MODIS Measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2007. While the ground PM(sub 2.5) concentration is highest in the winter, the aerosol optical depth measured from MODIS is highest in the summer. A seasonal comparison shows that PM(sub 2.5) in the winter can exceed summer PM(sub 2.5) by 55%, while summer AOD exceeds winter AOD by 43%. Higher temperatures and wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not surface particulate matter monitors. Temperature inversions, especially during the winter, contribute to higher PM(sub 2.5) measurements at the surface. Measurements of the boundary layer height from lidar instruments provide valuable information need to understand the relationship between satellite measurements of optical depth and in-situ measurements of PM(sub 2.5)

Exploring the limits of variational passive microwave retrievals

2017 Summer.Includes bibliographical references.Passive microwave observations from satellite platforms constitute one of the most important data records of the global observing system. Operational since the late 1970s, passive microwave data underpin climate records of precipitation, sea ice extent, water vapor, and more, and contribute significantly to numerical weather prediction via data assimilation. Detailed understanding of the observation errors in these data is key to maximizing their utility for research and operational applications alike. However, the treatment of observation errors in this data record has been lacking and somewhat divergent when considering the retrieval and data assimilation communities. In this study, some limits of passive microwave imager data are considered in light of more holistic treatment of observation errors. A variational retrieval, named the CSU 1DVAR, was developed for microwave imagers and applied to the GMI and AMSR2 sensors for ocean scenes. Via an innovative method to determine forward model error, this retrieval accounts for error covariances across all channels used in the iteration. This improves validation in more complex scenes such as high wind speed and persistently cloudy regimes. In addition, it validates on par with a benchmark dataset without any tuning to in-situ observations. The algorithm yields full posterior error diagnostics and its physical forward model is applicable to other sensors, pending intercalibration. This retrieval is used to explore the viability of retrieving parameters at the limits of the available information content from a typical microwave imager. Retrieval of warm rain, marginal sea ice, and falling snow are explored with the variational retrieval. Warm rain retrieval shows some promise, with greater sensitivity than operational GPM algorithms due to leveraging CloudSat data and accounting for drop size distribution variability. Marginal sea ice is also detected with greater sensitivity than a standard operational retrieval. These studies ultimately show that while a variational algorithm maximizes the effective signal to noise ratio of these observations, hard limitations exist due to the finite information content afforded by a typical microwave imager