Master of Science in Electrical Engineering (MSEE), Wright State University, 2023, Electrical Engineering

A method for software-defined radio array calibration is presented. The method implements a matched filter approach to calculate the phase shift between channels. The temporal stability of the system and calibration coefficients are shown through the standard deviation over the course of four weeks. The standard deviation of the phase correction was shown to be less than 2 deg. for most channels in the array and within 8 deg. for the most extreme case. The standard deviation in amplitude scaling was calculated to be less than 0.06 for all channels in the array. The performance of the calibration is evaluated by the antenna gain and the difference from the ideal beam shape for the peak side lobe level and first null depth. For one example data collection, the gain was 61 dB for the array with a maximum difference of 0.2246 dB for the peak side lobe level and 0.3998 dB for the first null depth.

Committee: Michael A. Saville Ph.D. (Advisor); Zhiqiang Wu Ph.D. (Committee Member); Josh Ash Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science in Electrical Engineering, University of Dayton, 2020, Electrical Engineering

In this paper two axis fixture calibration utilizing industrial robot artifact object touch sensing is explored. The background for the topic of fixture calibration is provided as well as what was done in this paper. Through this paper, two axis fixture calibration utilizing industrial robot artifact object touch sensing is theorized with mathematics, modeled in simulation, further modeled in experimental modeling, tested in experimentation, and verified with a new procedure. Overall, the goal of automating the calibration process currently used in Yaskawa controllers was achieved. The new TB calibration method produces an equivalently accurate calibration to the Yaskawa calibration method, while removing human error with touch sensing. Additionally, a numeric verification method, the TCP verification method, is developed for quantifying the accuracy of the fixture calibration.

Committee: Temesgen Kebede Ph.D. (Advisor); Raul Ordonez Ph.D. (Committee Member); Ouboti Djaneye-Boundjou Ph.D. (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2007, Electrical Engineering

Future radio transceivers are expected to deliver much higher data rates and operate at several frequencies. In 4G wireless systems, convergence of cellular and WLAN transceiver for VoIP will require the radio to operate in multiple RF bands and with different modulation schemes ranging from BPSK to 64- and 256-QAM OFDM. There is also the challenge for low power even as the handheld is pushed to achieve additional performance. While CMOS technology scaling and innovations in platform based systems and Network-on-Chip (SOC and NOC) have resulted in great strides within the digital part (digital baseband/MAC), the radio part of a wireless solution remains a major bottleneck. In today's radio design environment, a fully integrated CMOS radio requires several silicon spins before it meets all product specifications and often with relatively low yields. This results in significant increase in NRE cost, especially when considering that mask set costs increase exponentially as feature size scales down. Furthermore, additional spins could lead to missing important market windows, particularly with the decreasing life cycles of semiconductor products. In addition to the complexity of highly integrated radio transceiver, RF performance is highly susceptible to random variations in process and operating conditions. Such variations do not scale with the process. Worst-case corner simulations often lead to over-design and increased power consumption. RF models, package models and design kits are based on certain assumptions that severely limit design space exploration. All these factors prohibit first-time-right silicon. This thesis work aims to address these issues by presenting design techniques leading to first pass success and taking advantage of the increased integration of digital, analog and RF. Through the exploitation of advances in the digital baseband, this dissertation proves that it is possible to calibrate the noise of the analog and RF front end. Through careful d (open full item for complete abstract)

Committee: Mohammed El-Naggar (Advisor) Subjects:

Master of Science, The Ohio State University, 2021, Health and Rehabilitation Sciences

Manuscript 1: Methodology Dependent Variation in Volumetric Bone Mineral Density Calculation throughout the Body Introduction: Bone quality assessment using quantitative computed tomography (QCT) may provide a more in-depth and accurate assessment of osteoporosis and fracture risk than dual-energy x-ray absorptiometry (DXA). However, QCT methodologies utilizing single-scan calibration curves may not account for differential x-ray attenuation caused by the patient which may influence calculated volumetric bone mineral density (vBMD) and skew bone quality and fracture risk assessment. Methodology: Clinical CT scans were conducted on 50 male post-mortem human subjects with phantom calibration rods throughout the scan. Height and weight were collected to determine subject BMI. Hounsfield units (HU) from skeletal volumes of interest (VOIs) were collected from the lumbar spine and left femoral neck, humerus, radius, tibia, and calcaneus. The femoral neck was segmented into trabecular (Tb), cortical (Ct) and Total (Tb and Ct) VOI's, the lumbar spine and the calcaneus consisted of Tb and Total VOIs, and the humerus, radius, and tibia were assessed for Ct bone. HU from each VOI was converted to vBMD using both a general scan specific (Gen.) calibration curve constructed from phantom rods within the CT slices of the lumbar region and location specific (LS) calibration curves constructed from phantom rods in slices for each of the skeletal VOIs. Results: Significant variation in vBMD calculated from Gen. and LS calibration curves was observed in the femoral neck, calcaneus, and tibia in all skeletal compartments 15 (p<0.01). However, no significant differences were observed in any of the lumbar spine, humerus, or radius VOIs (p>0.01). Additionally, BMI was not able to explain variation in vBMD values at any site (p>0.01). Conclusions: Using a single calibration curve to calculate vBMD in other anatomical locations, may skew bone quality and differential fracture risk ass (open full item for complete abstract)

Committee: Randee Hunter PhD (Advisor); Amanda Agnew PhD (Committee Member); Jun Zhang PhD (Committee Member) Subjects: Anatomy and Physiology; Biomedical Research; Health; Health Care

Master of Science in Computer Engineering (MSCE), Wright State University, 2020, Computer Engineering

Recent advances in location acquisition services have resulted in vast amounts of trajectory data; providing valuable insight into human mobility. The field of trajectory data mining has exploded as a result, with literature detailing algorithms for (pre)processing, map matching, pattern mining, and the like. Unfortunately, obtaining trajectory data for the design and evaluation of such algorithms is problematic due to privacy, ethical, dataset size, researcher access, and sampling frequency concerns. Synthetic trajectories provide a solution to such a problem as they are cheap to produce and are derived from a fully controllable generation procedure. Citing deficiencies in modern synthetic trajectory procedures, we propose a data-driven, seasonally-aware and simulation-based procedure that incorporates macro- and micro-level patterns from reference trajectories. The procedure is implemented as an alpha-release package; allowing an analyst to produce synthetic trajectories via the use of a modular coding framework and analysis tools.

Committee: Derek Doran Ph.D. (Advisor); Adam Nolan Ph.D. (Committee Member); Michael Raymer Ph.D. (Committee Member) Subjects: Computer Engineering; Computer Science

Doctor of Philosophy, The Ohio State University, 2019, Computer Science and Engineering

In today's age of rapidly evolving smart city infrastructure, several cutting-edge applications have found interest in the research community, such as traffic monitoring, accident prediction, and prevention. Due to their reduced cost and ease of integration with other hardware, cameras are an integral part of the sensing system in these applications. Calibrating these cameras enables measurement of real-world distances from the video, thereby opening the doorway for a wide range of novel applications. However, the current camera installations are typically not calibrated, i.e., information such as their precise mounting height and orientation is not available or involves a tedious manual process that requires a trained professional who needs to use a known pattern (e.g., chessboard-like) at a calibrated distance. In this proposal, I present the automatic calibration techniques for traffic/infrastructure cameras (AutoCalib) and dashboard cameras (DashCalib). We also propose two applications that make use of the calibrated camera sensors. Soft-Swipe runs on top of calibrated infrastructure cameras and exploits Vehicle to Infrastructure communications (V2I) to enable automatic pairing of vehicles with respective lanes. Road-View uses the information from dashboard cameras by fusing with Intervehicular communication (IVC) messages from neighboring vehicles to generate a global view of the road. AutoCalib is a system for efficient, automatic calibration of traffic cameras. AutoCalib exploits deep learning to extract selected keypoint features from car images in the video and uses a novel filtering and aggregation algorithm to automatically produce a robust estimate of the camera calibration parameters from just hundreds of samples. We have implemented AutoCalib as a service on Azure that takes in a video segment and outputs the camera calibration parameters. DashCalib is a system for automatic and live calibration of dashboard cameras that always ensures highl (open full item for complete abstract)

Committee: Prasun Sinha Dr. (Advisor); Rajiv Ramnath Dr. (Advisor) Subjects: Computer Engineering; Computer Science

Master of Science in Computer Engineering (MSCE), Wright State University, 2014, Computer Engineering

Extensive use of visible electro-optical (visEO) cameras for machine vision techniques shows that most camera systems produce distorted imagery. This thesis investigates and compares several of the most common techniques for correcting the distortions based on a pinhole camera model. The methods being examined include a common chessboard pattern based on (Sturm 1999), (Z. Zhang 1999), and (Z. Zhang 2000), as well as two "circleboard" patterns based on (Heikkila 2000). Additionally, camera models from the visual structure from motion (VSFM) software (Wu n.d.) are used. By comparing reprojection error from similar data sets, it can be shown that the asymmetric circleboard performs the best. Finally, a software tool is presented to assist researchers with the procedure for calibration using a well-known fiducial.

Committee: Kuldip Rattan Ph.D. (Advisor); Juan Vasquez Ph.D. (Committee Member); Thomas Wischgoll Ph.D. (Committee Member) Subjects: Computer Engineering; Computer Science; Optics; Scientific Imaging

Master of Science in Engineering (MSEgr), Wright State University, 2009, Electrical Engineering

The objective of this thesis is to demonstrate the layered sensing concept using Master-Slave cameras. The process of 2D camera calibration and several key factors that can present error during such calibration are described. The analysis and results are based on calibration of a pinhole model camera system. The calibration is accomplished using OpenCV software and the results are analyzed using MATLAB software. These results are divided into intrinsic and extrinsic camera parameters. These parameters are then used to determine the position and orientation of the object in the camera coordinate system. This thesis also explores the use of two cameras as a Master-Slave system to demonstrate the layered sensing concept. The Master camera's orientation, zoom, and distance from the Slave camera is fixed. Using the position and orientation of the object in the Master camera coordinate system, the position of the object in the Slave coordinate system is found using transformation matrices. This information is then used to determine the pan/tilt angles of the Slave camera. The Slave camera is then directed to focus on the object using servo control.

Committee: Kuldip S. Rattan PhD (Advisor); Devert Wicker PhD (Committee Member); Doug Petkie PhD (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2006, Electrical Engineering

This dissertation describes an iterative self-calibration technique for a Direction-of-Arrival (DOA) array to automatically remove the effects of mutual coupling and near-zone resonant size scatterers. The Inverse Method of Moments (IMM) is also introduced to determine the normalized Method of Moments (MM) impedance matrix and MM voltage vector for a Uniform Linear Array (ULA) given its terminal currents produced by plane waves from known directions. The IMM can be combined with an iterative technique to determine the array DOA angles with mutual coupling effects removed.

Committee: Edward Newman (Advisor) Subjects:

Master of Science (M.S.), University of Dayton, 2011, Electrical Engineering

In applications such as computer vision and robotics, camera calibration is required to correct geometric lens distortion of images. The problem with most techniques is that they require human involvement in the calibration process. This thesis proposes a new algorithm for camera calibration with no human involvement. Typically in camera calibration process, an image of a calibration target (usually a checkerboard) is acquired for distortion correction. The checkerboard is used because it has known features and is easily segmented. If the image of checkerboard pattern undergoes distortion when the image is captured, and the distortion may be determined by analyzing the image of the checkerboard. The proposed process for coefficient estimation is accomplished by segmenting out the checkerboard of a acquired image. The segmentation is done by finding the connected pixels (components), labeling the connected components and filtering out the unnecessary components from the acquired image. Then the algorithm uses sobel edge detection to detect the vertical and horizontal edges of the checkerboard, because the lines can be used to measure the displacement of image coordinates from their ideal location. Next, the proposed distortion-correction model is applied to the edges of the image with a set of correction coefficients, resulting a set of corrected images. Next the best fit line (synthesized line) is found for each observed line in the each corrected image, and the squared distance between each synthesized and observed line is calculated in each corrected image. The average squared distance is then calculated for each corrected image. Finally, the minimum average distance is found for a set of corrected images in order to obtain the respective image correction coefficients. Both synthetically generated images and natural images have been used to measure the performance of the proposed algorithm. The amount of distortion present in images before and after correction are (open full item for complete abstract)

Committee: Eric Balster PhD (Committee Chair); Frank A. Scarpino PhD (Committee Member); Vijayan K. Asari PhD (Committee Member) Subjects: Biomedical Research; Electrical Engineering

Master of Science in Electrical Engineering (MSEE), Wright State University, 2024, Electrical Engineering

The uncertainty of the standard calibration procedure for radar cross-section (RCS) measurement is studied for different targets measured in the near-field from 550 to 700 GHz. Using common calibration spheres and squat cylinders mounted on a styrofoam pedestal at waterline (zero-degrees elevation), the calibration difference measure is determined for each target. Similarly, the difference metric is determined for square trihedral and tophat targets placed on a ground plane and measured at different elevation angles. The mean calibration measure is calculated using the dual calibration target method and repeated measurements in an anechoic chamber. The specific THz system is described and the results show how the near field scattering behaviors degrade the accuracy of the scattering measurement. Additional analysis shows the measurement uncertainty to be within a few decibels for frequencies within 580 to 650 GHz.

Committee: Michael A. Saville Ph.D., P.E. (Advisor); Josh Ash Ph.D. (Committee Member); Cheryl B. Schrader Ph.D. (Committee Member) Subjects: Electrical Engineering

Master of Science, The Ohio State University, 1961, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Science, The Ohio State University, 1962, Graduate School

Committee: Not Provided (Other) Subjects:

Master of Sciences, Case Western Reserve University, 2024, Physics

Ultra high-energy cosmic rays (UHECR) are cosmic rays with energies greater than 1~EeV. The Origin of UHECR has remained a mystery for decades. On Earth we detect UHECR indirectly due to extensive air showers. We use detection on the ground to reconstruct the arrival direction, energy, and composition of UHECR. Auger@TA is a collaboration between the two major observatories for UHECR: the Pierre Auger Observatory (Auger) and the Telescope Array (TA). The main goal for Auger@TA is to conduct an in-situ cross-calibration based on air showers detected using surface detectors from both projects: TA scintillator detectors vs.~Auger Water Cherenkov Detectors (WCD). Auger@TA (Phase 2) consists of a small array of Auger WCD surface detector stations deployed within the existing TA observatory near Delta, Utah. This allows for individual cosmic-ray air shower events to be simultaneously and independently detected and reconstructed by both Auger and TA surface detectors, providing for an event-by-event comparison. In this thesis, we will discuss laboratory experimental work on the fabrication and testing of the photomultiplier tube (PMT) base electronics to be used on each WCD surface detector. These PMT bases have been deployed into the field. We also describe an improved analysis method to calibrate the energy response of Auger@TA WCD using vertical through-going muons, which has been applied to data collected from Auger@TA detectors in the field. This work directly supports the installation and commissioning of Auger@TA which will operate to collect cosmic ray air shower data from 2024 to 2026.

Committee: Corbin Covault (Committee Chair); Harsh Mathur (Committee Member); Benjamin Monreal (Committee Member) Subjects: Astrophysics; Particle Physics

Master of Science in Engineering, Youngstown State University, 2024, Department of Civil/Environmental and Chemical Engineering

The Mill Creek watershed is located in the Northeast Ohio and covers an area of 78.3 square miles within the Mahoning River basin. The river has been experiencing significant water quality problems due to pollution from point and nonpoint source contributions from its tributaries. Before joining the Mahoning River, the river flows through several areas, including the City of Columbiana, Beaver Township, Boardman Township, and Youngstown. Mill Creek comprises seven major tributaries, namely Anderson Run, Cranberry Run, Indian Run, Bears Run, Ax Factory Run, Sawmill Run, and Turkey Run, all of which contribute to the degradation of the river water quality in terms of algal bloom, turbidity, and bacterial contamination. The water quality of rivers is significantly affected by several sources of contamination, such as combined sewer overflows, failing septic systems, animal waste, and runoff from agricultural and urban areas. Despite several studies conducted in the past, a hydrologic and hydraulic investigation in the context of water quality modeling has not been conducted in Mill Creek yet. To address this concern, monitoring stations were established in different locations along the river to record real-time flow depth data using HOBO loggers. In addition, sporadic water quality data from the past and the recent data collected by the Environmental Science Program at YSU have been used for water quality calibration and validation. The hydrologic and hydraulic model was developed using the Personal Computer Storm Water Management (PCSWMM) model. Data sourced from the National Oceanic and Atmospheric Administration (NOAA) of the National Climatic Data Center (NCDC), the Digital Elevation Model (DEM) from the United States Geological Survey (USGS), land cover data from the National Land Cover Datasets (NLCD), and soil data from the United States Department of Agriculture (USDA) were utilized to construct the model. The calibration and validation of the model were carrie (open full item for complete abstract)

Committee: Suresh Sharma PhD (Advisor); Felicia Armstrong PhD (Committee Member); Sahar Ehsani PhD (Committee Member) Subjects: Civil Engineering; Environmental Engineering; Hydrology

Master of Sciences (Engineering), Case Western Reserve University, 2024, EMC - Aerospace Engineering

The Adaptive Icing Tunnel is a new refrigerated, closed-loop, vertical icing wind tunnel designed to achieve a test section airspeed of 215 knots and a temperature of 20 °C. Test section airspeed, liquid water content, and icing cloud uniformity will be tested for both spatial and temporal uniformity. The methods of these initial characterizations are developed, and analysis is conducted to determine the theoretical capabilities of the icing cloud based on data collected at a similar wind tunnel with known nozzle characteristics. It was approximated that a single Mod1 nozzle could produce an icing cloud with an LWC of 0.15 g/m3. A redesigned nozzle was created to allow for the use of multiple nozzles while maintaining a low LWC. The results of these characterization efforts will be used to provide crucial insights into the tunnel's performance and future research opportunities.

Committee: Paul Barnhart (Advisor); Steve Hostler (Committee Member); Majid Rashidi (Committee Member) Subjects: Aerospace Engineering; Mechanical Engineering

Master of Science in Electrical Engineering (MSEE), Wright State University, 2023, Electrical Engineering

Calibration plays a critical role in the optimal performance of algorithms in digital beamforming arrays. Phase incoherency between elements results in poor beamforming with decreased gain and higher sidelobes, leading to a decrease in accuracy and sensitivity of measurements. A similar problem exists in performing multi-pass interferometric SAR (IFSAR) processing of SAR data stacks to generate topological maps of the scene, where phase errors translate to height errors. By treating each SAR image in the data stack like an element of a uniform linear array, this thesis explores several phase calibration techniques that can be used to calibrate digital beamforming arrays and introduces them to IFSAR processing to calibrate the SAR images. Three data-driven techniques are selected, where calibration coefficients are obtain using sources of opportunity, via a contrast-based method, and via a clutter-based method. These calibration algorithms are then demonstrated on synthetic data of a simulated scene, consisting of scatterers at different heights, and with added phase incoherency to the SAR images. Processing of the simulated data shows an improvement in height estimation of the scatterers, including an evident increase in the gain and focusing of the scatterers in the scene after calibration. Phase calibration is then introduced to the processing of measured Gotcha data, where results also show gain and focusing improvement of the scatterers. Additional research, however, will be needed to associate the height estimation of the scatterers in these results with ground truth data to ascertain an absolute height map of the scene.

Committee: Brian D. Rigling Ph.D. (Advisor); Michael A. Saville Ph.D., P.E. (Committee Member); Fred Garber Ph.D. (Committee Member); Josh Ash Ph.D. (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2023, Electrical and Computer Engineering

Array signal processing algorithms for direction finding and adaptive beamforming require accurate in-situ calibration of the antenna array. Unfortunately, calibrating the array inside an anechoic chamber is often not possible because the array, or the platform it is mounted on, is too large. In addition, simulations of the array using Computational Electromagnetic (CEM) software can miss crucial information about the manufacturing defects present in the real system. The limitations of these methods has lead to the development of in-situ calibration techniques that can exploit the signals the array receives while deployed in its operational environment (i.e. Signals of Opportunity [SoOp]). In-situ calibration is advantageous because the incident signals include the effects of platform scattering and manufacturing defects without the need for an anechoic chamber. However, without any coordination between the array and the sources generating the SoOp, the transmitted signals are unknown to the array and multiple SoOp can be received simultaneously. Current methods capable of using SoOp for calibration rely on restrictive models for the array response, such as the Mutual Coupling Matrix, and are unable model the effects of platform scattering. In this dissertation, we present an in-situ calibration technique that incorporates a flexible model for the array response based on a Spherical Mode Expansion (SME). By expressing the far-field patterns of the antenna elements as a SME, we are able to model the response of an array placed in a complex scattering environment using a relatively compact representation. Because the spherical harmonics are only orthogonal over the full sphere, computing the expansion coefficients is difficult when the measurement region is limited, which is a common occurrence in in-situ calibration. We resolve this issue by employing a regularized least-squares solution and an efficient regularization parameter selection procedure. The propose (open full item for complete abstract)

Committee: Inder Gupta (Advisor); Patricia Enciso (Committee Member); Fernando Teixeira (Committee Member); Joel Johnson (Committee Member) Subjects: Electrical Engineering; Electromagnetics

Master of Science in Electrical Engineering (MSEE), Wright State University, 2023, Electrical Engineering

Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, and indicate that the models' surface roughness have negligent effect on the RCS prediction.

Committee: Michael A. Saville Ph.D. (Advisor); Yan Zhuang Ph.D. (Committee Member); Elliott R. Brown Ph.D. (Committee Member) Subjects: Electrical Engineering; Electromagnetics; Engineering

Master of Science in Engineering, Youngstown State University, 2023, Department of Civil/Environmental and Chemical Engineering

Water quality in lakes and reservoirs has been significantly degraded due to anthropogenic activities including point and non-point source pollution. Agricultural practices, particularly excessive fertilizer application, have been consistently identified as a major contributor to water contamination in the lakes and reservoirs. The escalation of nutrient loading into water bodies has raised serious concerns regarding eutrophication in lakes, as well as the potability of drinking water and other consumptive use of water. In order to address these problems, Best Management Practices (BMPs) have been implemented globally to reduce nutrient loadings and improve water quality in lakes and reservoirs. This study aims to assess the effectiveness of BMPs in reducing nutrient levels in the Atwood and Tappan Lakes of the Tuscarawas basin in Ohio by monitoring the sites for water quality sampling and using the Soil and Water Assessment Tool (SWAT) for watershed modeling. Stream flow data from five USGS gauge stations were gathered for multi-site calibration and validation of the model, whereas water quality data from five representative stations within the watersheds were monitored to calibrate the model for nutrients. The performance of the model for streamflow calibration at various USGS gauging stations was satisfactory with Nash-Sutcliffe Efficiency (NSE) values ranging from 0.54 to 0.79 during calibration, and 0.50 to 0.89 during validation. However, due to limited availability of water quality data, the calibration of nutrient was not as good as hydrological calibration. Subsequently, a scenario analysis was carried out using the calibrated SWAT model to assess the effectiveness of different management practices in reducing nutrient levels from the sub-watersheds. The selection of management practices, such as filter strips, grass waterways, fertilizer reduction, crop rotation, and cover crops, were considered for analysis based on active consultation with local stake (open full item for complete abstract)

Committee: Suresh Sharma PhD (Advisor); Sahar Ehsani PhD (Committee Member); Peter Kimosop PhD (Committee Member) Subjects: Civil Engineering