Systems and Communications Commons^™

Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter

Discovery Day - Daytona Beach

Lightweight UAV-to-UAV Detection and Tracking for Advanced Air Mobility Applications addresses the significant challenge of reliable UAV-to-UAV detection on resource-constrained platforms, particularly within Advanced Air Mobility (AAM) environments where dense, low-altitude airspace requires robust detect-and-avoid capabilities. This work presents the development and experimental evaluation of a lightweight detection and tracking framework for autonomous detect-and-avoid applications. The approach is designed to support real-time onboard operation in multi-vehicle environments characteristic of emerging AAM systems. The proposed framework integrates optical and LiDAR sensing with a low-complexity machine learning decision-support layer that reduces false detections without replacing the underlying control-oriented detection pipeline. This design …

Project Minerva, Lena Wang, Gannon English, Ethan Yemm, Gabrielle Guirguis, Jose Murphy

Discovery Day - Daytona Beach

Project Minerva is a multidisciplinary engineering initiative at Embry-Riddle Aeronautical University (ERAU) dedicated to the design, integration, and deployment of high-altitude balloon (HAB) systems for stratospheric research and aerospace hardware validation. The project challenges student researchers to engineer flight-ready payloads capable of maintaining structural and electronic integrity in extreme temperatures and low-pressure environments in the stratosphere. Typically utilizing 600g latex balloons filled with helium, Project Minerva missions aim to achieve altitudes exceeding 22,000 meters to facilitate vertical atmospheric profiling of variables such as CO₂ concentration, humidity, temperature, and pressure. Beyond its technical objectives, the project serves as a professional training …

Radaround: A Field-Expedient Direction Finder For Contested Iot Sensing & Em Situational Awareness, Owen Maute, Blake Roberts

Discovery Day - Daytona Beach

This paper presents RadAround, a passive 2-D direction-finding system designed for adversarial IoT sensing in contested environments. Using mechanically steered narrowbeam antennas and field-deployable SCADA software, it generates high-resolution electromagnetic (EM) heatmaps using low-cost COTS or 3D-printed components. The microcontroller-deployable SCADA coordinates antenna positioning and SDR sampling in real time for resilient, on-site operation. Its modular design enables rapid adaptation for applications such as EMC testing in disaster-response deployments, battlefield spectrum monitoring, electronic intrusion detection, and tactical EM situational awareness (EMSA). Experiments show RadAround detecting computing machinery through walls, assessing utilization, and pinpointing EM interference (EMI) leakage sources from Faraday …

Remora Ads-B In Receiver, Noah Evans, Sara Patel, Nicholas Gatto, Daniel Ingleton

Discovery Day - Daytona Beach

The Remora is a compact Automatic Dependent Surveillance Broadcast (ADS-B) receiver, designed to enhance situational awareness for pilots operating experimental and homebuilt aircraft. Unlike conventional panel or windscreen-mounted systems, the Remora is installed externally, making it a low-profile solution to the ADS-B In challenge. The device integrates easily with the aircraft’s existing power supply. It transmits data wirelessly to electronic flight bags (EFBs) within the cockpit, using existing iOS and Android software for display and user interaction.   The primary function of the Remora is to provide public-access, real-time traffic awareness and weather forecasting, enabling pilots to make informed mission decisions. …

Stability Through Chaos: Atmospheric Impact And Control Strategies For Laser Communication, Om Acharya, Mykailla Harper, Mark Vanberschot, Aldir Moreira

Discovery Day - Daytona Beach

Study of Atmospheric Effects and Mitigation Strategies in Free-Space Optical Communication Systems examines the fundamental limitations imposed by atmospheric disturbances on point-to-point laser communication links and evaluates methods to improve link reliability and performance. Free-space optical communication offers high data rates and reduced spectral congestion compared to radiofrequency systems, but its effectiveness is constrained by atmospheric effects including turbulence-induced scintillation, beam wander, absorption, and scattering. These phenomena introduce fluctuations in signal intensity and pointing errors, leading to degraded link stability and increased bit error rates. The work analyzes these atmospheric effects and investigates mitigation strategies that enhance optical link robustness …

Mob-Air: Sensing Package Development For Maritime Search And Rescue Uav, Rachel Jacobsen, Liam Abraham, Ethan Thomas, Madeline Thomson, Nikolaos Triantafilloy

Discovery Day - Daytona Beach

Man-overboard (MOB) search and rescue (SAR) operations present a persistent maritime challenge, where rapid and reliable detection of a person in the water is critical to mission success. MOB-Air is developing a modular sensing package for an unmanned aerial system (UAS) to enhance SAR missions through autonomous human detection in maritime environments. This capability directly supports Navy maritime operations by improving overboard recovery, reducing search timelines, and enabling persistent aerial monitoring in contested or resource-constrained environments. The system evaluates thermal and visual imaging sensors using a custom horizontal-rail testing frame with a mobile payload. A ROS 2–based software architecture supports …

Real-Time Fused Sensor System For Early Onboard Detection Of Weather Phenomena, Sanjana Singh

Discovery Day - Daytona Beach

Weather-related hazards continue to be a major cause of operational interruptions and safety issues in the aviation sector. Atmospheric phenomena, including turbulence, microbursts, convective storms, and rapidly changing boundary-layer conditions, can arise quickly and often occur on spatial scales that are not adequately addressed by regional forecasting systems. These phenomena particularly endanger aircraft flying at low altitudes, such as general aviation planes, unmanned aerial vehicles (UAVs), and those during takeoff and landing Although meteorological forecasting systems and ground-based radar networks offer important regional insights, they may fail to detect localized atmospheric variations encountered along specific flight routes. Consequently, pilots and …

Laser-Based Optical Communications For Spacecraft Information Transfer, Ibrahim Arnous

Discovery Day - Daytona Beach

This course-based, in-progress project explores optical communications as a spacecraft subsystem and examines how light-based systems can be used to transmit information in space. As modern missions demand faster and more efficient data transfer, optical communications have emerged as an important area of interest alongside traditional communication methods. The purpose of this project is to study the role of optical communication in spacecraft design, with attention to its principles, advantages, limitations, and broader relevance to future missions. Using a comparative and research-based approach, the project investigates how these systems function, what engineering challenges they introduce, and why they are becoming …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions

Doctoral Dissertations and Master's Theses

Effective communication is a critical component of successful collaboration in group projects and team settings. However, systematically tracking and analyzing team communications can be challenging, especially in complex, multi-member teams such as those found in the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of information flow, encoding communication patterns, and analyzing Ecological Network Analysis parameters, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the …

Data-Driven Physical-Layer Optimization For Rf And Optical Communications: Transmitarray Metasurfaces, Contextual-Bandit Mud, And Coherent Optical Links, Chengtao M. Xu

Doctoral Dissertations and Master's Theses

This dissertation studies three physical-layer optimization problems that share a common difficulty: the forward model, whether an electromagnetic solver or a statistical channel model, is either too expensive to evaluate at design scale or too unstable to hold across a single processing block. The first two problems are treated in their own right, as problems in antenna design and in multi-user detection over time-variant channels; the third carries the methodology onto a coherent optical link, where size, weight, and power constraints make a small-satellite deployment the natural target.

The antenna work targets a tri-layer pixelated unit cell fabricated on Avient …

Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand

Doctoral Dissertations and Master's Theses

As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …

Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting, Madison Gleydura

Doctoral Dissertations and Master's Theses

Flash flood nowcasting in Central and Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at long range and signal blockage by mountains. GNSS-meteorology offers an established alternative for measuring precipitable water vapor and is currently integrated into several numerical weather models. Recent research demonstrates that commercial-grade GNSS receivers can produce tropospheric products comparable to those from geodetic-grade equipment. The gaps in mountain coverage can be addressed by developing a low-cost, self-contained embedded system that …

Performance Evaluation Of Routing Protocols And Ml-Based Enhancements For Uav-Assisted Post-Disaster Communication Networks, Prachi Choudhary

Doctoral Dissertations and Master's Theses

During natural disasters, the existing communication systems collapse, and the disaster-affected areas become disconnected without any means of exchanging information. The collapse of existing communication networks poses challenges for First-Responders (FRs) in locating survivors during Search and Rescue (SAR) operations and for survivors to communicate for emergency aid. To alleviate post-disaster consequences and save lives, Uncrewed Air Vehicles (UAVs), commonly known as drones, can be employed to establish adaptable and reliable emergency communication networks. UAVs offer portability and rapid deployment, making them effective in crises. This thesis presents two main contributions: 1) Evaluation and Comparison of Routing Protocol Performance: The …

Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson

Sustainability Conference

There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …

Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens

Doctoral Dissertations and Master's Theses

Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook

Doctoral Dissertations and Master's Theses

With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …

Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions, Robert Koeneke

Doctoral Dissertations and Master's Theses

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team's coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV …

A Design Flow For Additively Manufactured 3d Metasurface Antennas​, Justin Parkhurst

Doctoral Dissertations and Master's Theses

Metasurface (MTS) antennas are complex arrays consisting of hundreds or thousands of individual elements that each exert their own influence on the performance of the antenna. Due to this, the process of designing and developing a MTS antenna can be intensive in terms of both the time to understand the how these antennas operate and time running calculations that achieve optimal performance. Through the use of automation for geometry creation in ANSYS HFSS, the work involved in making a MTS antenna can be greatly simplified. The overall objective of this thesis is to reduce the burden of constructing a MTS …

Hardware Security For Wireless Communications Systems Using Antenna-Based Radio Frequency Fingerprint Engineering, Noemi Miguelez Gomez

Doctoral Dissertations and Master's Theses

The design and application of novel physical-layer security techniques have been increasing in the last decades as means to enhance the security that more traditional techniques provide to wireless communications systems. Well-known hardware security techniques, such as radio frequency fingerprinting, use unintended manufacturing process variations and unique hardware structures in the semiconductors for applications such as identification and classification of the source of different transmitted signals, and detection of hardware modifications. The uniqueness of the features that two different modules present, even maintaining the same design, can be used for modules characterization at a lower cost and complexity than other …

Effect Of Freestream Noise On Hypersonic Crossflow-Induced Boundary-Layer Transition, Andrew Bustard, Thomas J. Juliano, Harrison B. Yates, Mark Noftz, Joseph Jewell

Publications

Between the windward and leeward rays, boundary-layer transition on cones at angle of attack in hypersonic flow is dominated by the crossflow instability [1, 2], wherein stationary and/or traveling crossflow vortices develop and can breakdown into turbulence [3]. Stationary crossflow modes are caused by surface roughness or any other steady forcing and produce disturbances that are fixed in place on the surface [3–6]. Stationary vortices create a generalized inflection point in the velocity profile that is inviscidly unstable [7]. This distorted mean flow develops secondary instabilities, whose growth and breakdown is one path to turbulence [8–10]. Traveling crossflow modes are …

Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang

Doctoral Dissertations and Master's Theses

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …

Improvement On Pdp Evaluation Performance Based On Neural Networks And Sgdk-Means Algorithm, Fan Deng, Houbing Song, Zhenhua Yu, Liyong Zhang, Xi Song, Min Zhang, Zhenyu Zhang, Yu Mei

Publications

With the purpose of improving the PDP (policy decision point) evaluation performance, a novel and efficient evaluation engine, namely XDNNEngine, based on neural networks and an SGDK-means (stochastic gradient descent K-means) algorithm is proposed. We divide a policy set into different clusters, distinguish different rules based on their own features and label them for the training of neural networks by using the K-means algorithm and an asynchronous SGDK-means algorithm. Then, we utilize neural networks to search for the applicable rule. A quantitative neural network is introduced to reduce a server’s computational cost. By simulating the arrival of requests, XDNNEngine is …

Zero-Bias Deep Neural Network For Quickest Rf Signal Surveillance, Yongxin Liu, Jian Wang, Dahai Liu, Houbing Song, Yingjie Chen, Shuteng Niu

Publications

The Internet of Things (IoT) is reshaping modern society by allowing a decent number of RF devices to connect and share information through RF channels. However, such an open nature also brings obstacles to surveillance. For alleviation, a surveillance oracle, or a cognitive communication entity needs to identify and confirm the appearance of known or unknown signal sources in real-time. In this paper, we provide a deep learning framework for RF signal surveillance. Specifically, we jointly integrate the Deep Neural Networks (DNNs) and Quickest Detection (QD) to form a sequential signal surveillance scheme. We first analyze the latent space characteristic …

Federated Variational Learning For Anomaly Detection In Multivariate Time Series, Kai Zhang, Houbing Song, Yushan Jiang, Lee Seversky, Chengtao M. Xu, Dahai Liu

Publications

Anomaly detection has been a challenging task given high-dimensional multivariate time series data generated by networked sensors and actuators in Cyber-Physical Systems (CPS). Besides the highly nonlinear, complex, and dynamic nature of such time series, the lack of labeled data impedes data exploitation in a supervised manner and thus prevents an accurate detection of abnormal phenomenons. On the other hand, the collected data at the edge of the network is often privacy sensitive and large in quantity, which may hinder the centralized training at the main server. To tackle these issues, we propose an unsupervised time series anomaly detection framework …

Learning To Detect: A Data-Driven Approach For Network Intrusion Detection, Zachary Tauscher, Yushan Jiang, Kai Zhang, Jian Wang, Houbing Song

Publications

With massive data being generated daily and the ever-increasing interconnectivity of the world’s Internet infrastructures, a machine learning based intrusion detection system (IDS) has become a vital component to protect our economic and national security. In this paper, we perform a comprehensive study on NSL-KDD, a network traffic dataset, by visualizing patterns and employing different learning-based models to detect cyber attacks. Unlike previous shallow learning and deep learning models that use the single learning model approach for intrusion detection, we adopt a hierarchy strategy, in which the intrusion and normal behavior are classified firstly, and then the specific types of …

Multimedia Networks And Communications, Houbing Song

Publications

Sight and sound is a type of correspondence that joins distinctive substance structures like content, sound, pictures, liveliness, or video into a solitary show, rather than customary broad communications, like written word or sound chronicles. Famous instances of interactive media incorporate video web recordings, sound slideshows and animated videos. Multimedia can be recorded for playback on PCs, workstations, cell phones, and other electronic gadgets, either on request or progressively (streaming). In the early long stretches of sight and sound, the expression "rich media" was inseparable from intuitive mixed media. Over the long run. Improved degrees of intuitiveness are made conceivable …