Signal Processing Commons^™

Multicarrier Modulation Using Discrete Fractional Fourier Transform, Amir Raeisi Nafchi

Electrical and Computer Engineering ETDs

The focus of the research was to investigate the application of the discrete fractional Fourier transform (DFRFT) in communication systems. We investigated the compactness of the Gauss-Hermite like eigenvectors of the DFRFT and showed how a multi-carrier modulation system could benefit from it. This led to identifying an affine DFRFT. We proved the circular convolution property for the proposed DFRFT. Using this affine transform, we were able to design an orthogonal frequency division multiplexer (OFDM) communication system. In the process of implementing the OFDM, we developed a method for fast computation of the DFRFT using the chirp-z transform. Using the …

Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …

Dc Microgrid Fault Detection Using Multiresolution Analysis Of Traveling Waves, Rudy Montoya

Mechanical Engineering ETDs

Fast detection and isolation of faults in a DC microgrid is of particular importance. Fast tripping protection (i) increases the lifetime of power electronics (PE) switches by avoiding high fault current magnitudes and (ii) enhances the controllability of PE converters. This thesis proposes a traveling wave (TW) based scheme for fast tripping protection of DC microgrids. The proposed scheme utilizes a discrete wavelet transform (DWT) to calculate the high-frequency components of DC fault currents. Multiresolution analysis (MRA) using DWT is utilized to detect TW components for different frequency ranges. The Parseval energy calculated from the MRA coefficients are then used …

Multi-Device Data Analysis For Fault Localization In Electrical Distribution Grids, Jacob D L Hunte

Electronic Thesis and Dissertation Repository

The work presented in this dissertation represents work which addresses some of the main challenges of fault localization methods in electrical distribution grids. The methods developed largely assume access to sophisticated data sources that may not be available and that any data sets recorded by devices are synchronized. These issues have created a barrier to the adoption of many solutions by industry. The goal of the research presented in this dissertation is to address these challenges through the development of three elements. These elements are a synchronization protocol, a fault localization technique, and a sensor placement algorithm.

The synchronization protocol …

Machine Learning Based Medical Image Deepfake Detection: A Comparative Study, Siddharth Solaiyappan, Yuxin Wen

Engineering Faculty Articles and Research

Deep generative networks in recent years have reinforced the need for caution while consuming various modalities of digital information. One avenue of deepfake creation is aligned with injection and removal of tumors from medical scans. Failure to detect medical deepfakes can lead to large setbacks on hospital resources or even loss of life. This paper attempts to address the detection of such attacks with a structured case study. Specifically, we evaluate eight different machine learning algorithms, which include three conventional machine learning methods (Support Vector Machine, Random Forest, Decision Tree) and five deep learning models (DenseNet121, DenseNet201, ResNet50, ResNet101, VGG19) …

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

Three Wave Mixing In Epsilon-Near-Zero Plasmonic Waveguides For Signal Regeneration, Nicholas Mirchandani, Mark C. Harrison

Engineering Faculty Articles and Research

Vast improvements in communications technology are possible if the conversion of digital information from optical to electric and back can be removed. Plasmonic devices offer one solution due to optical computing’s potential for increased bandwidth, which would enable increased throughput and enhanced security. Plasmonic devices have small footprints and interface with electronics easily, but these potential improvements are offset by the large device footprints of conventional signal regeneration schemes, since surface plasmon polaritons (SPPs) are incredibly lossy. As such, there is a need for novel regeneration schemes. The continuous, uniform, and unambiguous digital information encoding method is phase-shift-keying (PSK), so …

The Role Of Transient Vibration Of The Skull On Concussion, Rodrigo Dalvit Carvalho Da Silva

Electronic Thesis and Dissertation Repository

Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to …

Relative Magnetic Position And Rotation Sensor Assisted Dual-Foot Pedestrian Dead Reckoning, Jenario Y. Johnson

Theses and Dissertations

The use of wearable foot-based inertial measurement units (IMUs) incorporated in a navigation system can address the problem of single-person location tracking in situations and environments where GPS signals may be unavailable or inconsistent. This Pedestrian Dead Reckoning (PDR) approach enables standalone personal tracking. A notable solution involves using inertial measurement units (IMUs) in a filter to apply zero-velocity updates to a Kalman filter to get a position solution. This paper continues on the path of the former method by investigating the feasibility of PDR using a pair of low cost IMUs along with a pair of relative position and …

Deep Learning Techniques To Estimate 3d Position In Stereoscopic Imagery, Jonathan I. Nicholson

Theses and Dissertations

Current AAR efforts utilize machine vision algorithms to estimate the pose of a receiver aircraft. However, these algorithms are dependent on several conditions such as the availability of precise 3D aircraft models; the accuracy of the pipeline significantly degrades in the absence of high-quality information given beforehand. We propose a deep learning architecture that estimates the 3D position of an object based on stereoscopic imagery. We investigate the use of both machine learning techniques and neural networks to directly regress the 3D position of the receiver aircraft. We present a new position estimation framework that is based on the differences …

Detection And Identification Of Cellphone Emitted Light Detection And Ranging Light In Security Camera Video Footage, Tristan V. Creek

Theses and Dissertations

The prevalence of Light Detection and Ranging (LiDAR) sensors in consumer cellphones has ushered in an era of access to technologies previously inaccessible to the average person. Although LiDAR sensors emit light in the infrared spectrum invisible to the naked eye, many security cameras possess the ability to capture infrared light reflected off surfaces to detect LiDAR light in an environment. Once detected and recorded to video footage, current classification methods fail to identify the LiDAR light. Therefore, this research develops a methodology to detect LiDAR light in security camera video footage and identify it as cellphone LiDAR. A proposed …

Monocular Camera Localization Using A Bag Of Visual Words From Virtual World Data, Joshua A. Rinaldi

Theses and Dissertations

The Visual Localization problem is the question of how to use visual information to determine the location of the camera that captured that data. The wide availability and low price of RGB cameras has made this useful in many fields such as SLAM, SAM and AR. This research seeks to determine if a BOVW can adequately overcome repetitious features in indoor environments and be effectively incorporated into a VL pipeline.

Testbed Creation To Study Noise Radar Network Weighting Models And Data Fusion With Radio Tomographic Imaging, Ryan M. Jans

Theses and Dissertations

Significant research has been conducted on RTI weighting models; however, very little comparative research has been conducted for NRN weighting methods. In order to create comparative weighting methods for NRN, it is necessary to create a testbed which allows for RTI and NRN research to be conducted simultaneously and allow for data fusion methods to also be researched. After creating the testbed and analyzing results, the newly proposed weighting method provides an up to 33% performance increase in target localization accuracy when compared to the previous weighting model used for NRN. The attenuation image resolution improvements resulted in a 79% …

Evaluation Of The Armas-Som Framework With Real Data, Brandon M. Blakely

Theses and Dissertations

The ARMAS framework was created with the goal of developing a framework for all-source sensors which is able to combine detection, identification, calibration, model selection, and independent evaluation into a single system. Stable Observability Monitoring (SOM), augments the original ARMAS framework by enabling ARMAS to detect whether or not its Fault Detection and Exclusion (FDE) capabilities can be trusted and when additional sensor information is required to maintain resiliency. While previously tested with simulated sensor data, SOM has yet to be tested with real-life sensor data. Furthermore, ARMAS has only been tested with real-life GNSS data. This work expands on …

Uav Positioning Data Determined Via Aruco Tags For Aircraft Surface Inspection, Caleb B. Schmidt

Theses and Dissertations

Aircraft are frequently inspected to ensure that military and civilian safety standards are adhered to. These inspections are performed pre- and post-flight and are currently performed by trained maintenance personnel. This work furthers the automation of aircraft surface inspection by using ArUco tags to determine the position of the UAV during aerial inspections. The ArUco tag based position data was then compared to a highly accurate infrared motion capture system to determine the viability of this for accurate positioning of the vehicle. This work includes flight experiments with two different UAVs to perform a system viability comparison.

Global Sporadic-E Climatological Analysis Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos

Theses and Dissertations

A climatology of sporadic-E (Es) derived from a combined data set of GPS radio occultation (GPS-RO) and ground-based ionosonde soundings is presented for the period from September 2006 to February 2019. The ionosonde soundings were measured using the Lowell Digisonde International (LDI) Global Ionosphere Radio Observatory (GIRO) network consisting of 65 sites and 13,141,060 total soundings. The GPS-RO observations were taken aboard the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites and processed using two binary Es detection algorithms, totaling 9,072,922 occultations. The first algorithm is an S4 amplitude threshold calibrated to the occurrence of any blanketing Es …

Performance Assessment Of Navigation Using Carrier Doppler Measurements From Multiple Leo Constellations, Michael J. Hartnett

Theses and Dissertations

The goal of this work is to characterize a novel navigation method which uses carrier Doppler shift measurements from LEO satellites. An ever-growing reliance on the GNSS has coincided with an increase in ways it can be degraded or denied, whether naturally occurring or man-made. These potentially disastrous threats to traditional navigation and timing have necessitated new technologies to augment GNSS in the case of an outage. LEO constellations, whose size and higher signal power make them potentially useful for navigation, are one technology that has been explored. The navigation algorithms detailed in this research use Doppler measurements from 8 …

Design Study For An Antenna Radar Cross Section Measurement Test Fixture, Wayne C. Kreimeyer

Theses and Dissertations

Military technology requires equipment to be undetected by adversaries. Stealth aircraft are designed to be undetected through electromagnetic means by minimizing a return signature called the RCS. Therefore, it is essential to understand how antennas, which are necessary for communication, affect the overall RCS of the aircraft. The antenna is measured in a compact RADAR range. The antenna needs a structure to support it, also referred to as a test fixture, that does not interfere with the measuring process of the antenna’s RCS. This thesis set out to get the lowest RCS possible of a test fixture by evaluating different …

Physiological Signal Analysis For Emotion Estimation Of Children With Autism Spectrum Disorder, Janet Pulgares Soriano, Karla Conn Welch Phd

Posters-at-the-Capitol

The diagnosis of Autism Spectrum Disorder (ASD) in children is based on human observations by a clinician. The medical evaluation assesses deficits in social communication, social interaction, and restricted, repetitive behaviors. Robotic technology can assist in quantitatively measuring the observations to be used as a future tool for autism diagnosis and intervention. The project explores this technology to produce robotic partners that can adapt to the needs of the ASD population. This way, such robots could serve as instructors or learning peers. A friendly, partner robot, specifically designed for children with ASD could be used to investigate the effect of …

Kemar Hats Head Orientation Directivity, Samuel D. Bellows, Timothy W. Leishman

Directivity

No abstract provided.