Measurement of snow water equivalent using drone-mounted ultra-wide-band radar

The use of unmanned aerial vehicle (UAV)-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate snow water equivalent (SWE) using UAV-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring SWE using ultra-wide-band (UWB) (0.7 to 4.5 GHz) pseudo-noise radar on a moving UAV, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the frequency–wavenumber (F–K) migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R > 0.92) for depth measurements up to 5.5 m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of 0.108 g/cm3. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an F–K migration technique

Unmanned Aerial Systems Research, Development, Education and Training at Embry-Riddle Aeronautical University

With technological breakthroughs in miniaturized aircraft-related components, including but not limited to communications, computer systems and sensors and, state-of-the-art unmanned aerial systems (UAS) have become a reality. This fast growing industry is anticipating and responding to a myriad of societal applications that will provide either new or more cost effective solutions that previous technologies could not, or will replace activities that involved humans in flight with associated risks. Embry-Riddle Aeronautical University has a long history of aviation related research and education, and is heavily engaged in UAS activities. This document provides a summary of these activities. The document is divided into two parts. The first part provides a brief summary of each of the various activities while the second part lists the faculty associated with those activities. Within the first part of this document we have separated the UAS activities into two broad areas: Engineering and Applications. Each of these broad areas is then further broken down into six sub-areas, which are listed in the Table of Contents. The second part lists the faculty, sorted by campus (Daytona Beach---D, Prescott---P and Worldwide--W) associated with the UAS activities. The UAS activities and the corresponding faculty are cross-referenced. We have chosen to provide very short summaries of the UAS activities rather than lengthy descriptions. Should more information be desired, please contact me directly or alternatively visit our research web pages (http://research.erau.edu) and contact the appropriate faculty member directly

Unmanned Aerial Systems: Research, Development, Education & Training at Embry-Riddle Aeronautical University

With technological breakthroughs in miniaturized aircraft-related components, including but not limited to communications, computer systems and sensors, state-of-the-art unmanned aerial systems (UAS) have become a reality. This fast-growing industry is anticipating and responding to a myriad of societal applications that will provide new and more cost-effective solutions that previous technologies could not, or will replace activities that involved humans in flight with associated risks. Embry-Riddle Aeronautical University has a long history of aviation-related research and education, and is heavily engaged in UAS activities. This document provides a summary of these activities, and is divided into two parts. The first part provides a brief summary of each of the various activities, while the second part lists the faculty associated with those activities. Within the first part of this document we have separated UAS activities into two broad areas: Engineering and Applications. Each of these broad areas is then further broken down into six sub-areas, which are listed in the Table of Contents. The second part lists the faculty, sorted by campus (Daytona Beach-D, Prescott-P and Worldwide-W) associated with the UAS activities. The UAS activities and the corresponding faculty are cross-referenced. We have chosen to provide very short summaries of the UAS activities rather than lengthy descriptions. If more information is desired, please contact me directly, or visit our research website (https://erau.edu/research), or contact the appropriate faculty member using their e-mail address provided at the end of this document

DRIVER PERFORMANCE DUE TO UNMANNED AERIAL SYSTEM APPLICATIONS IN THE VICINITY OF SURFACE TRANSPORTATION

Unmanned aerial systems (UAS), or drones, have become increasingly utilized for a myriad of applications in the vicinity of the roadway and can offer a low-cost alternative to many labor-intensive data collection techniques, including infrastructure inspection, roadway marking data collection, and more. To collect much of this data with a desired degree of accuracy, UAS must be flown near moving vehicles, pedestrians, and/or bicyclists. However, UAS, and their pilot/crew, have the potential to be a distraction to drivers. A study by Hurwitz et al. suggests that UAS operations are more distracting to drivers as the UAS traverses closer to the roadway laterally. Through a combined literature review and full-immersion driver simulator study, this study furthered the current state-ofthe-literature and investigated the potential for UAS to be flown near roadways in the future as well as potential safety implications of those circumstances. Specifically, driver performance due to drone height and the presence of drone operators was evaluated. The literature synthesis portion of this research revealed that UAS flights in the vicinity of roadways will continue to increase. The results of the driving simulation study showed that participants were more visually distracted in situations where the pilot and drone were both present compared to the drone only. Further, in 11% of all analyzed situations, participants were critically visually distracted (continuous glance of two seconds or more) by the drone or pilots. Ultimately, this research provides recommendations to policymakers for creating regulations on the use of drones in the vicinity of roadways

Fault-Tolerant Control of a Dual-Stator PMSM for the Full-Electric Propulsion of a Lightweight Fixed-Wing UAV

The reliability enhancement of electrical machines is one of the key enabling factors for spreading the full-electric propulsion to next-generation long-endurance UAVs. This paper deals with the fault-tolerant control design of a Full-Electric Propulsion System (FEPS) for a lightweight fixed-wing UAV, in which a dual-stator Permanent Magnet Synchronous Machine (PMSM) drives a twin-blade fixed-pitch propeller. The FEPS is designed to operate with both stators delivering power (active/active status) during climb, to maximize performances, while only one stator is used (active/stand-by status) in cruise and landing, to enhance reliability. To assess the fault-tolerant capabilities of the system, as well as to evaluate the impacts of its failure transients on the UAV performances, a detailed model of the FEPS (including three-phase electrical systems, digital regulators, drivetrain compliance and propeller loads) is integrated with the model of the UAV longitudinal dynamics, and the system response is characterized by injecting a phase-to-ground fault in the motor during different flight manoeuvres. The results show that, even after a stator failure, the fault-tolerant control permits the UAV to hold altitude and speed during cruise, to keep on climbing (even with reduced performances), and to safely manage the flight termination (requiring to stop and align the propeller blades with the UAV wing), by avoiding potentially dangerous torque ripples and structural vibrations

Approaches for Autonomous Vehicles in Civil Airspace: Giving Sight to the Blind

The growing prevalence of unmanned aerial vehicles (UAVs) brings great potential for public benefit, but in order to fly in civil airspace UAVs must avoid traffic without the benefit of an onboard human. Developing this capability presents many system integration challenges. This report examines the integration of automated detect, see, and avoid (DSA) systems on aircraft. For context, the need for UAV operations is reviewed. The report then examines how DSA fits into the entire framework for aviation safety. The research, test results, and conclusions that follow provide the necessary information to decide: • how to test and evaluate new DSA technology; • what is the necessary performance for installed DSA systems; • what is currently available and what possibilities are in development. Finally, after surveying available technologies, recommendations are given for some specific UAV platforms and missions. This report would be useful for persons engaged in DSA development, acquisition, or testing. It is applicable for all small aircraft because future advances may make DSA technology feasible for the entire aviation community. The emphasis, however, is on enabling safe UAV operation world-wide

Detection, identification and localization of R/C electronic devices through their unintended emissions

The accurate and reliable detection of unintended emissions from radio receivers has a broad range of commercial and security applications. This thesis presents detection, identification, and localization methods for multiple RC electronic devices in a realistic environment. First, a Hurst parameter based detection method for super-regenerative receivers (SRR) has been used for detection. Hurst parameter based detection method exploits a self-similarity property of the SRR receiver emissions to distinguish it from background noise. Second paper presents a novel detection and localization scheme of multiple RC electronic devices called Edge-Synthetic Aperture Radar (Edge-SAR). It employs cost-effective, mobile antenna-array detectors. Two types of RC devices are considered: SRR with H parameter method and super heterodyne receivers (SHR) with peak detection method. Third paper improves detection of multiple devices by proposing a dynamic antenna-array processing method called VIVEK-MVDR-GA. It combines multi-constrained genetic algorithm (GA) and minimum variance distortion-less response (MVDR) method to increase accuracy of detection and localization of multiple devices. Finally, a 4-element array mounted on an unmanned aerial vehicle (UAV) is proposed to overcome multipath and reflection due to environmental surroundings and improve the response time in compromised scenarios. Also, a time based correlation method is proposed for array detectors to identify the line of sight (LOS) and non-line of sight (N-LOS) signals. A normalized error correlation function has been implemented to improve the estimation of angle of arrival (AOA) in the presence of strong non-line of sight (N-LOS) signals --Abstract, page iv