Engineering Commons^™

Modeling Performance Of Microgrid And Electric Vehicle Technology On The Utah State University Electric Distribution Network, Jackson Morgan

Fall Student Research Symposium 2020

To estimate the value of solar power, energy storage, and electric vehicle charging on a small utility's distribution network, power system simulation was performed to compare the load profiles and bills of various levels of deployment. This project used Utah State University's south distribution network and its new parking structure as a testbed for simulation and analysis of new energy technology. The project found that for a rate structure with a fixed capacity reservation and a low energy charge, campus solar power is not currently viable for significantly reducing costs. Conversely, electric vehicle charging could be implemented at a low …

Hardware Verification Of Lunar Terrain Relative Navigation, Sam Christensen

Fall Student Research Symposium 2020

Autonomous delivery to the lunar surface requires proven, cost-effective navigation techniques, especially during the final descent. Terrain Relative Navigation (TRN) is a compelling solution because it has no infrastructure requirements, such as beacons on the lunar surface. However, previous validation of this technique has relied on software simulation of image acquisition and vehicle state estimation. This research leverages the autonomous drone facilities at USU to validate the TRN technique in a hardware system. A hardware demonstration will verify the effectiveness of the TRN technique in a realistic environment simulating the final descent of a lunar lander. This environment will provide …

Formal Verification Of The Adversarial Robustness Property Of Deep Neural Networks Through Dimension Reduction Heuristics, Refutation-Based Abstraction, And Partitioning, Joshua Smith

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Neural networks are tools that are often used to perform functions such as object recognition in images, speech-to-text, and general data classification. Because neural networks have been successful at approximating these functions that are difficult to explicitly write, they are seeing increased usage in fields such as autonomous driving, airplane collision avoidance systems, and other safety-critical applications. Due to the risks involved with safety-critical systems, it is important to provide guarantees about the networks performance under certain conditions. As an example, it is critically important that self driving cars with neural network based vision systems correctly identify pedestrians 100% of …

Soft-Switched Resonant Dc-Dc Converter In Underwater Dc Power Distribution Network, Tarak Saha

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Power distribution with DC source is advantageous over its AC counterpart in long distance distribution network due to the absence of effects of reactive components. Long distance power distribution with traditional voltage source suffers from drop in voltage over the length of the cable due to its impedance and forces the converters in the network to be over-designed with higher power rating than needed. In underwater power distribution network such as ocean observatory, marine sensors on the sea-bed etc., power conversion modules are situated at a distance far away from the shore, ranging from tens of kilometers to hundreds of …

System Level Characterization Of The Gridded Retarding Ion Drift Sensor (Grids) For The Petitsat Mission, Benjamin B. Oborn

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Weather prediction, wherever people live, serves as a beneficial part of everyday life. Weather in the upper portions of Earth’s atmosphere also impacts life on Earth but it is not able to be predicted as well as its terrestrial counterpart. PetitSat is a cube satellite (CubeSat) mission proposed to help remedy this issue. It will collect measurements of charged particles in the upper atmosphere called a plasma. The measurements taken by PetitSat will facilitate better prediction of upper-atmospheric weather. Prediction of when and where weather phenomenon will occur will allow avoidance of negative consequences that can result. Once such negative …

A Study In Gps-Denied Navigation Using Synthetic Aperture Radar, Colton P. Lindstrom

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In modern navigation systems, GPS is vital to accurately piloting a vehicle. This is especially true in autonomous vehicles, such as UAVs, which have no pilot. Unfortunately, GPS signals can be easily jammed or spoofed. For example, canyons and urban cities create an environment where the sky is obstructed and make GPS signals unreliable. Additionally, hostile individuals can transmit personal signals intended to block or spoof GPS signals. In these situations, it is important to find a means of navigation that doesn’t rely on GPS.

Navigating without GPS means that other types of sensors or instruments must be used to …

Hardware Implementations Of Ccsds Deep Space Ldpc Codes For A Satellite Transponder, Dana R. Sorensen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Error-correction coding is a technique that adds mathematical structure to a message, allowing corruptions to be detected and corrected when the message is received. This is especially important for deep space satellite communications, since the long distances and low signal power levels often cause message corruption. A very strong type of error-correction coding known as LDPC codes was recently standardized for use with space communications. This project implements the encoding and decoding algorithms required for a small satellite radio to be able to use these LDPC codes. Several decoder architectures are implemented and compared by their performance, speed, and complexity. …

Emerging Works On Wireless Inductive Power Transfer: Auv Charging From Constant Current Distribution And Analysis Of Controls In Ev Dynamic Charging, Anindya Chitta Bagchi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Wireless power transfer through inductive coupling, termed as inductive power transfer (IPT), is one of the important technologies in power electronics that enable transfer of power between entities without physical connections. While it has seen significant growth in the areas such as electric vehicle charging, phone charging and biomedical implants, its emerging applications include charging of autonomous underwater vehicles (AUVs) and dynamic charging of electric vehicles from the roadway. This dissertation addresses a few key challenges in these areas of IPT applications, paving the way for future developments.

For the WPT for AUV, the recently developing sea-bed installed marine systems …

Self-Describing Fiducials For Gps-Denied Navigation Of Unmanned Aerial Vehicles, Amanda J. Strate

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Accurate estimation of an Unmanned Aerial Vehicle’s (UAV’s) location is critical for the operation of the UAV when it is controlled completely by its onboard processor. This can be particularly challenging in environments in which GPS is not available (GPS-denied). Many of the options previously explored for estimation of a UAV’s location without the use of GPS require more sophisticated processors than can feasibly be mounted on a UAV because of weight, size, and power restrictions. Many options are also aimed at indoor operation without the range capabilities to scale to outdoor operations. This research explores an alternative method of …

Challenges And Opportunities In Near-Threshold Dnn Accelerators Around Timing Errors, Pramesh Pandey, Noel Daniel Gundi, Prabal Basu, Tahmoures Shabanian, Mitchell Craig Patrick, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

AI evolution is accelerating and Deep Neural Network (DNN) inference accelerators are at the forefront of ad hoc architectures that are evolving to support the immense throughput required for AI computation. However, much more energy efficient design paradigms are inevitable to realize the complete potential of AI evolution and curtail energy consumption. The Near-Threshold Computing (NTC) design paradigm can serve as the best candidate for providing the required energy efficiency. However, NTC operation is plagued with ample performance and reliability concerns arising from the timing errors. In this paper, we dive deep into DNN architecture to uncover some unique challenges …

Titan: Uncovering The Paradigm Shift In Security Vulnerability At Near-Threshold Computing, Prabal Basu, Pramesh Pandey, Aatreyi Bal, Chidhambaranathan Rajamanikkam, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

In this paper, we investigate the emerging security threats at Near-Threshold Computing (NTC) that are poised to jeopardize the trustworthy operation of future low-power electronic devices. A substantial research effort over the last decade has bolstered energy efficient operation in low-power computing. However, innovation in low-power security has received only marginal attention, thwarting a ubiquitous adoption of critical Internet of Things applications, such as wearable gadgets. Using a cross-layer methodology, we demonstrate that the timing fault vulnerability of a circuit rapidly increases as the operating conditions of the transistor devices shift from super-threshold to near-threshold values. Exploiting this vulnerability, we …

Collaborative Research: Cns Core: Small: Secure And Efficient Mobile Edge Computing In Wireless Heterogeneous Networks, Rose Qingyang Hu

Funded Research Records

No abstract provided.

Indoor Source Localization Of Radio Frequency Transmitters Using Blind Channel Identification Techniques, Madison L. Rose

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Locating transmitters is a research area that is becoming increasingly relevant as technology advances. It is especially useful for determining the location of livestock, drones, keys, phones, tablets, etc. As a result of this push for locating devices, many algorithms have been developed to determine source locations. Most source location algorithms and techniques rely on a "line of sight", or a direct path between the source and the receivers to provide accurate results.

Indoor environments pose a challenge to locating transmitters due to the many surfaces that allow radio waves to interact (reflect, refract, and generally distort) with them. Because …

Formation Control Using Vehicle Operational Envelopes And Behavior-Based Dual-Mode Model Predictive Control, Brian Merrell

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This thesis presents a control framework for formation control. Given an initial desired trajectory, a framework is presented to generate trajectories for each vehicle within the formation. When combined with an operational envelope, a designated area for each vehicle to maneuver, for each vehicle the multi-vehicle formation control problem can be redefined into a single vehicle problem. A single vehicle framework is presented to track the respective trajectory when possible, or stay near it when it passes through previously unknown obstacles. Arc-based motions are used to rapidly produce desirable robot controls while a trajectory tracking motion is used to ensure …

Design Of A Sweeping Impedance Probe For The Sport Mission, Caleb W. Young

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In our modern world satellite systems are an evermore common part of day to day life. Reliable communication from the ground to these satellites is becoming more and more necessary. Plasma scintillations in the ionosphere can make these communications difficult or even impossible. By gaining a better understanding of these scintillations, times of bad satellite connection can be predicted in the same way terrestrial weather gets predicted and reported today. The objective of the SPORT mission is to gain a better understanding of these plasma scintillations. In order to measure plasma density, and gain a better understanding of plasma scintillations, …

Greentpu: Predictive Design Paradigm For Improving Timing Error Resilience Of A Near-Threshold Tensor Processing Unit, Pramesh Pandey, Prabal Basu, Koushik Chakraborty, Sanghamitra Roy

Electrical and Computer Engineering Faculty Publications

The emergence of hardware accelerators has brought about several orders of magnitude improvement in the speed of the deep neural-network (DNN) inference. Among such DNN accelerators, the Google tensor processing unit (TPU) has transpired to be the best-in-class, offering more than 15\times speedup over the contemporary GPUs. However, the rapid growth in several DNN workloads conspires to escalate the energy consumptions of the TPU-based data-centers. In order to restrict the energy consumption of TPUs, we propose GreenTPU - a low-power near-threshold (NTC) TPU design paradigm. To ensure a high inference accuracy at a low-voltage operation, GreenTPU identifies the patterns in …

The Gridded Retarding Ion Drift Sensor For The Petitsat Cubesat Mission, Ryan L. Davidson, B. Oborn, E. F. Robertson, S. Noel, G. D. Earle, J. Green, J. Kramer

Electrical and Computer Engineering Faculty Publications

The Gridded Retarding Ion Drift Sensor (GRIDS) is a small sensor that will fly on the 6 U petitSat CubeSat. It is designed to measure the three-dimensional plasma drift velocity vector in the Earth’s ionosphere. The GRIDS also supplies information about the ion temperature, ion density, and the ratio of light to heavy ions present in the ionospheric plasma. It utilizes well-proven techniques that have been successfully validated by similar instruments on larger satellite missions while meeting CubeSat-compatible requirements for low mass, size, and power consumption. GRIDS performs the functions of a Retarding Potential Analyzer (RPA) and an Ion Drift …

Estimation Of Autoregressive Parameters From Noisy Observations Using Iterated Covariance Updates, Todd K. Moon, Jacob H. Gunther

Electrical and Computer Engineering Faculty Publications

Estimating the parameters of the autoregressive (AR) random process is a problem that has been well-studied. In many applications, only noisy measurements of AR process are available. The effect of the additive noise is that the system can be modeled as an AR model with colored noise, even when the measurement noise is white, where the correlation matrix depends on the AR parameters. Because of the correlation, it is expedient to compute using multiple stacked observations. Performing a weighted least-squares estimation of the AR parameters using an inverse covariance weighting can provide significantly better parameter estimates, with improvement increasing with …

Three-Dimensional Hydrodynamic Focusing For Integrated Optofluidic Detection Enhancement, Eric Scott Hamilton

Utah Space Grant Consortium

Integrated optofluidics are ideal for high sensitivity detection due to the size of device features being near the small scale of sample particles (10 microns). Novel integrated optofluidic designs enable single molecule detection through hydrodynamic focusing, making the approach ideal for low concentration biosensing. Detection was enhanced and device operation characterized. Further enhancement is promised with optimization of existing designs.

Masking And Detecting Radiation-Induced Errors In Sram-Based Fpgas Through Partial Circuit Replication, Andrew M. Keller

Utah Space Grant Consortium

Radiation found in terrestrial and space environments can induce errors into SRAM-based FPGAs. Replication of circuitry can be used mask and detect these errors to improve reliability or availability. This work advances the understanding and implementation of partial circuit replication in SRAM-based FPGAs. Partial circuit replication is the replication of a subset of the components in a circuit. A reliability model is presented that evaluates the reliability benefit of partial circuit replication. The model suggests that the reliability benefit is inversely related to the portion of the circuit replicated. A partial triple module redundancy case study is also presented that …

Command, Control, And Telemetry For Utah State University's Scintillation Prediction Observation Research Task (Sport) Mission, Jordan Haws

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The Scintillation Prediction Observation Research Task (SPORT) is a joint United States of America (USA) and Brazil small satellite mission to address the further understanding of the preconditions leading to equatorial plasma bubbles. Utah State University (USU) is supplying four instruments towards this SPORT mission. These four instruments will allow measurements of the electric field and plasma density in the ionosphere which will help understand what gives rise to plasma bubbles in the ionosphere.

This thesis will discuss the command, control, and telemetry communications needed to operate the SPORT USU instruments. It will cover an overview of the instruments involved, …

A Study Of Potential Security And Safety Vulnerabilities In Cyber-Physical Systems, Ali Al-Hashimi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The work in this dissertation focuses on two examples of Cyber-Physical Systems (CPS), integrations of communication and monitoring capabilities to control a physical system, that operate in adversarial environments. That is to say, it is possible for individuals with malicious intent to gain access to various components of the CPS, disrupt normal operation, and induce harmful impacts. Such a deliberate action will be referred to as an attack. Therefore, some possible attacks against two CPSs will be studied in this dissertation and, when possible, solutions to handle such attacks will also be suggested.

The first CPS of interest is vehicular …

Hardware Accelerator For Star Centroiding, Nazmus Sakib

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Since the dawn of civilization mankind has gazed upon the night sky and looked for directions. In this modern age, the stars have proved to be a reliable reference point for navigation in space. From small-satellites for gathering weather data to inter-planetary missions like Cassini Orbiter, figuring out the location of a spacecraft has been done successfully by taking images of star filed visible from the spacecraft, processing and analyzing the image to find the stars and then finding out from a star catalog which part of the sky the patterns of the visible stars best matches. But a lot …

System-Level Analysis Of Autonomous Uav Landing Sensitivities In Gps-Denied Environments, Terran R. Gerratt

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This paper presents an analysis of the navigation accuracy of an fixed-wing Unmanned Aerial Vehicle (UAV) landing on a aircraft carrier. The UAV is equipped with typical sensors used in landing scenarios. Data from the Office of Naval Research is used to accurately capture the behavior of the aircraft carrier. Through simulation, the position and orientation of both the UAV and carrier are estimated. The quality of the UAV’s sensors are varied to determine the sensitivity of these estimates to sensor accuracy. The system’s sensitivity to GPS signals and visual markers on the carrier is also analyzed. These results allow …

Comparison Of Locational Beamforming Algorithms For Audio Targeting, Thomas Lewis Bradshaw

Undergraduate Honors Capstone Projects

In many applications it is desirable to focus on the direction a signal is coming from to isolate the signal from interfering noise coming from other directions. This is often done by focusing the receiver on a given direction. One method to accomplish this focusing is to use an array of receivers and a signal processing algorithm called beamforming. This algorithm attenuates signals coming from all other directions besides the direction of interest, which can be viewed pictorially as a beam. However, it would also benefit many applications to be able to focus on a location rather than just a …

Robust Secure Wireless Powered Miso Cognitive Mobile Edge Computing, Boyang Liu, Jiajia Song, Jin Wang, Haijan Sun, Qun Wang

Electrical and Computer Engineering Student Research

Wireless power transfer (WPT) and cognitive radio (CR) are two promising techniques in designing mobile-edge computing (MEC) systems. In this paper, we study a robust secure wireless powered multiple-input single-output (MISO) cognitive MEC system, which integrates several techniques: physical-layer security, WPT, CR, underlay spectrum sharing and MEC. Three optimization problems are formulated to minimize the total transmission power (TTP) of the primary transmitter (PT) and the secondary base station (SBS) under perfect channel state information (CSI) model, bounded CSI error model and the probabilistic CSI error model, respectively. The formulated problems are nonconvex and hard to solve. Three two-phase iterative …

Reducing Road Wear While Ensuring Comfort And Charging Constraints For Dynamically Charged Passenger Vehicles Through Noise-Shaped Path Variations, Clint Jay Ferrin, Randall Christensen

Electrical and Computer Engineering Faculty Publications

Dynamically charged vehicles suffer from power loss during wireless power transfer due to receiver and transmitter coil misalignment while driving. Autonomous, dynamically charged vehicles can maximize wireless power transfer by minimizing the misalignment, but the repeated high-precision driving increases road wear. To avoid unnecessary road wear and rutting, a noise shaping filter is proposed that adds variability to a vehicle's trajectory that complies with passenger acceleration and position constraints. However, introducing variability into an optimal charging path also risks depleting battery life prior to destination arrival. Therefore, a path planner is proposed that guarantees average charge within a specified probability …

Effort: Enhancing Energy Efficiency And Error Resilience Of A Near-Threshold Tensor Processing Unit, Noel Daniel Gundi, Tahmoures Shabanian, Prabal Basu, Pramesh Pandey, Sanghamitra Roy, Koushik Chakraborty, Zhen Zhang

Electrical and Computer Engineering Faculty Publications

Modern deep neural network (DNN) applications demand a remarkable processing throughput usually unmet by traditional Von Neumann architectures. Consequently, hardware accelerators, comprising a sea of multiplier and accumulate (MAC) units, have recently gained prominence in accelerating DNN inference engine. For example, Tensor Processing Units (TPU) account for a lion's share of Google's datacenter inference operations. The proliferation of real-time DNN predictions is accompanied with a tremendous energy budget. In quest of trimming the energy footprint of DNN accelerators, we propose EFFORT-an energy optimized, yet high performance TPU architecture, operating at the Near-Threshold Computing (NTC) region. EFFORT promotes a better-than-worst-case design …