Navigation, Guidance, Control and Dynamics Commons^™

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Aircraft Fault Detection Via Weight And Bias Analysis Of A Custom First Neural Network Layer, George Harrison Chen

Theses and Dissertations

Fault detection in aircraft is traditionally handled through redundant hardware and comparison algorithms to detect failures. Alternatives like model-based residual generation and data-driven approaches such as supervised fault classification and unsupervised anomaly detection have been explored, but they suffer from practical limitations; model-based methods require accurate system models, and data-driven methods have large constraints on the data limiting scalability and adaptability. This work presents a purely data-driven neural network architecture featuring a custom first layer designed for real-time fault detection where the weights and biases of this layer are used to detect faults. The network requires zero supervision and complements …

Adaptive Artificial Potential Field Guidance And Control For Autonomous Docking With Uncooperative And Unknown Spacecraft, Steven Holmberg

Theses and Dissertations

The increasing demand for on-orbit servicing (OOS), active debris removal (ADR), and space domain awareness (SDA) missions has increased the need for autonomous spacecraft rendezvous and proximity operations (RPO) with uncooperative and unknown targets. Traditional guidance and control methods are typically designed for cooperative systems with known geometry and state information. This work builds on previous research to develop and evaluate an artificial potential field (APF)-based control framework capable of autonomous operation with minimal prior target knowledge and applicability to both relatively static and tumbling spacecraft.

The proposed APF formulation incorporates established safety constructs from cooperative docking systems, including an …

Leveraging Large Language Models (Llms) For Automated Generation Of Sysml V2 State Machines In Guidance, Navigation, And Control (Gnc) Systems, Andrea Louise Ames

Theses and Dissertations

Modern defense systems continue to grow in complexity, placing increasing pressure on engineering workflows to be faster and more adaptable. While Model-Based Systems Engineering (MBSE) with the emerging SysML v2 standard provides a framework for capturing system behavior, its practical use is often limited by the expertise and time required for manual modeling. This research investigates whether large language models (LLMs) can help overcome that barrier by automatically generating SysML v2 state machines from Guidance, Navigation, and Control (GNC) textual inputs. Three LLM Flowise-based models were developed and evaluated: the Structured Transformation Model (STM), which uses a structured extraction and …

Developing End-To-End Imitation Learning For Asteroid Proximity Operations, Patrick David Quinn

Theses and Dissertations

Asteroid exploration remains a popular topic in the scientific community, however hurdles still exist for controlling spacecraft within the asteroid environment. Communication delays often require the usage of limited onboard computing hardware for navigation. Additionally, long mission timelines must be accommodated with highly efficient fuel use. Considering these issues, it is apparent that any guidance, navigation, and control (GNC) system in these spacecraft should emphasize both computational and fuel efficiency in its design. Furthermore, the integration of a robust state estimation system is necessary for the successful deployment of such systems. The development of a controller aiming to address these …

Towards Visual Inertial Navigation With Fixed Tetrahedral Targets, Joao Leonardo Silva Cotta

Theses and Dissertations

This dissertation presents a robust method for 6DoF position estimation under impaired visual conditions utilizing a minimum 4-point Perspective-n-Point (P4P) solver designed for tetrahedral targets. Using SO(3) × R 3 instead of SE(3), the method uses a Lie group-based formulation to discriminate between rotation and translation, thereby enabling computationally efficient, resource-conscious op- optimization while preserving correct geometric behavior. Designed using the contemporary C++17 library ShomerTarget, the solver is analytically formulated and assessed under pragmatic robotic conditions. Particularly in low-light and high-dynamic environments, experiments on embedded systems, UAVs, and NASA’s Astrobee show that the proposed solver attains enhanced accuracy compared to …

Implementation Of Unscented Kalman Filter-Based State Estimation For Multiple Spacecraft Using Global Positioning System Measurements, Bala Prenith Reddy Gopu

Theses and Dissertations

This study presents an implementation of state estimation for a drag-based rendezvous mission involving multiple chaser spacecraft and a single target, using Unscented Kalman Filtering (UKF) with Global Positioning System (GPS) measurements. The implemented method combines GPS navigation solutions with UKF to provide real- time state estimates of all spacecraft involved. Nonlinear least squares method is employed to process pseudorange and pseudorange rate measurements to determine receiver states, UKF utilizes these states as measurements to estimate absolute space- craft positions and velocities. This implementation also addresses practical challenges including raw GPS measurement processing, and varying GPS satellite geometries.

Graph Neural Network-Based Uav Coverage Planning For Robust And Efficient 3d Environments, Gal Tsfaty

Theses and Dissertations

This thesis addresses the challenge of generating optimized UAV waypoints for complete coverage of complex 3D environments, utilizing graph-based computational techniques. The proposed framework replaces computationally intensive steps—triangulation and three-coloring—within the Vantage Waypoint Set Generation Algorithm (VWSGA) pipeline with Graph Neural Networks (GNNs). By learning structural patterns, the GNN achieves scalable and robust triangulation and node classification, enabling enhanced coverage planning in irregular geometries. A novel penalty mechanism ensures alignment with graph structure during adjacency prediction. Experimental results demonstrate the effectiveness of GNNs in balancing accuracy, computational efficiency, and adaptability, advancing UAV coverage optimization.

Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan

Theses and Dissertations

Autonomous vehicles are increasingly being deployed for use in high-stakes and uncertain environments where safe and efficient navigation is critical. In these scenarios, traditional path planning approaches, which rely primarily on deterministic models and fixed assumptions, fall short due to the inherent uncertainty of dynamic threats, sensor inaccuracies, and incomplete information. This research addresses these challenges by developing a novel path-planning methodology that combines the Chance-Constrained Rapidly Exploring Random Tree* (CC-RRT*) algorithm with a probabilistic risk assessment heuristic. This method models uncertainty in sensor detection zones, obstacles in the environment, and the Autonomous Vehicle itself, which allows for uncertainty during …

Visual Segmentation For Autonomous Aircraft Landing On Austere Runways, Alissa M. Owens

Theses and Dissertations

Autonomous aircraft must land without human intervention, but existing methods rely on GPS or marked runways, which may be unavailable in austere environments. This paper presents a vision-based approach using semantic segmentation to detect runways and estimate aircraft pose by comparing camera and satellite imagery. We detail the model’s training and demonstrate its effectiveness with simulated and real UAV data.

Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones

Theses and Dissertations

The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.

An Analytical Approach In Solving A Two-On-One Pursuit Evasion Differential Game With Fast Evader And No-Point Capture, Nathan T. Morrow

Theses and Dissertations

This paper is concerned with a co-planar pursuit-evasion scenario where two Pursuers (P) are after an Evader (E). The players are holonomic/can turn on a dime and their speeds, V_P and V_E, are constant, but the evader is faster than the pursuers, that is, the speed ratio parameter μ =  V_E/V_P > 1. The Pursuers are endowed with a circular capture disc whose radius l > 0. A differential game (DG) with three states and one parameter is addressed through geometric and analytical methods where a partial solution is outlined and visualized. The game is split …

Metaheuristic Techniques To Optimize Trajectory Planning Of Uav Swarms: Enhancing Data Acquisition In Wireless Sensor Networks, Nada Ali Mohamed Ahmed Ahmed

Theses and Dissertations

Unmanned aerial vehicles (UAVs) have become increasingly integrated into various applications due to their cost-efficiency, rapid deployment, flexible maneuvers, and enhanced performance. This has led to the development of a new field called UAV-assisted Wireless Sensor Networks (U-WSNs), which focus on data routing, network performance optimization, and planning UAV trajectories between sensor nodes in wireless sensor networks. In this thesis, a new framework has been proposed to manage a swarm of UAVs cooperatively serving large-scale wireless sensor networks. The framework consists of three optimization problems: distributing sensor nodes among UAVs, finding optimal trajectories in the presence of obstacles, and performing …

Learning-Based Feature Identification For Rendezvous And Capture Of Non-Cooperative Space Objects, Trupti Mahendrakar

Theses and Dissertations

In recent years, On-Orbit Servicing (OOS) and Active Debris Removal (ADR) have attracted increasing interest due to growing concerns about space debris. This debris poses a significant risk to spacecraft, as collisions can catastrophically end missions and potentially trigger a cascading chain reaction of more debris. Space debris ranges from tiny paint chips to large non-functional spacecraft and even launch vehicle components. One way to mitigate the formation of additional space debris is to reduce the total number of large non-cooperative resident space objects present in operational orbits. This can be achieved through two approaches: de-orbiting these objects as part …

Improving Robustness Of Learning-Based Approaches In Autonomous Systems And Engineering Education, Godwyll Aikins

Theses and Dissertations

This dissertation advances the development of robust learning-based approaches across two complementary domains: engineering education and autonomous systems. Through four studies, this research addresses critical challenges in preparing data-proficient engineers and developing reliable autonomous systems that can operate under uncertainty and incomplete information. The engineering education study examines how mechanical and aerospace engineering undergraduates conceptualize and develop data proficiency skills essential for modern engineering practice. Through interviews with 27 students, the research employs the How People Learn framework to analyze student perspectives on information literacy, data interpretation, and computational thinking. The findings inform pedagogical strategies for developing data proficiency in …

System Identification For Motion Control Of Unmanned Aerial Vehicles Platform, Raj Ramesh Agarwal

Theses and Dissertations

Comprehensive research on Unmanned Aerial Vehicles (UAV) system identification for motion control parameters is presented in this thesis, with a focus on the necessity of precise control and improved performance. Using Pseudorandom Binary Sequence (PRBS) and Normally Distributed Random Numbers, it presents a unique technique for excitation of UAV dynamic systems. It also shows how effective random signals are in time-domain identification for precise control in a range of flying circumstances. The piece of research includes a thorough analysis and implementation of various approaches and its further improvements, highlighting the benefits and drawbacks of each. These approaches include the free …

External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow

Theses and Dissertations

In the past two decades, Unmanned Aerial Systems have progressed from expensive military hardware or one-off custom builds, to include off-the-shelf drones that can be purchased for a rather affordable price and flown by nearly anyone. As the technology and performance have improved, the door is opened to applications that require operation in environments where the consequences for failure are high, such as operating in the navigable airspace or in urban environments, or with human passengers. This requires a great deal of trust in the reliability and integrity of the control systems of the aircraft. A method of monitoring the …

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

Belief Space Planning For Alternative Navigation In Gnss-Denied Environments, Timothy I. Machin

Theses and Dissertations

Robust alternative navigation for autonomous agents becomes critical without reliable GNSS. Autonomous agents utilize measurement updates to constrain uncertainty. Belief space planning builds graph structures of beliefs within environments based on probable paths, agent and measurement models, and information of the environment. The Rapidly-exploring Random Alt-Nav Belief Graph (RRBANG) algorithm leverages stochastic filtering to implement a range of alt-nav measurement capabilities for robust navigation in GNSS-denied environments.

Robust Feature Matching For Visual-Based Aerial Navigation Using Registered Imagery, Luis Montenegro

Theses and Dissertations

This work leverages the SIFT detector along with known robust feature matching techniques for vision-aided sUAS navigation solutions. The proposed algorithm focuses on a sufficient number of features extracted, their quality and their distribution.

Magnetic Anomaly Mapping For Navigation, Luke T. Bergeron

Theses and Dissertations

Magnetic navigation (MagNav) has the potential to provide a global form of navigation that uses magnetic measurements of the Earth’s anomaly magnetic field and compares those measurements to a magnetic anomaly map in order to determine the user’s position. Widespread use of MagNav will require a database of fully-sampled, low-altitude magnetic anomaly maps. Existing magnetic anomaly map databases usually come from under- or poorly-sampled surveys. In this work, we provide an easy to follow MagNav anomaly map generation framework and set of survey collection metrics/requirements in an effort to help facilitate and standardize the creation of such a database. We …

Atmospheric Polarization And Solar Position As Kalman Updates To A Navigation Solution, Thomas J. Wheeler

Theses and Dissertations

Simulation and physical testing of a sensor that measures relative position of the Sun and polarization of light in the atmosphere as a navigational aid in a Kalman filter.

Three-Axis Magnetometer Calibration With Norm Preservation, Seth Lichlyter

Theses and Dissertations

This thesis proposes a set of methods for the purpose of improving the calibration of three-axis magnetometers. Specifically, these methods aim to improve the accuracy of the bias estimation methods currently in use. The first proposed method utilizes a constrained optimization problem based on norm preserving. The second proposed method finds the same bias estimate as the first method, but in a computationally more efficient manner. The last proposed method tackles the case where the value of the local geomagnetic field is only imprecisely known. Computer simulations demonstrate the viability of the proposed methods.

Magnetic Anomaly Absolute Positioning For Hypersonic Aircraft, Alexander J. Mcneil

Theses and Dissertations

GPS has proven to be an extremely valuable asset for navigation, and timing. GPS has become the standard navigation system for all applications, but GPS has limitations. GPS is susceptible to jamming, spoofing, and in the case of hypersonic aircraft, is likely unavailable. When an aircraft is traveling at hypersonic speeds, there is a plasma sheath that surrounds the aircraft. This plasma sheath blocks electromagnetic waves, and is therefore responsible for a GPS blackout. GPS unavailability for hypersonic aircraft has prompted the research into the viability of alternate navigation systems for these aircraft. This paper seeks to explore the viability …

Covariance Analysis For Multi-Source Navigation Architecture, Tristan T. Williams

Theses and Dissertations

Currently, analysis on navigation systems can be slow and computationally expensive using Monte Carlo approaches. Covariance analysis is a tool that can return trade space analysis results promptly and can be computationally reasonable. This research aims to create a covariance analysis tool in a new navigation framework architecture, PntOS. The creation of this covariance tool is explained in coordination with the tool being used in a few different navigation scenarios with the results. These scenarios include a Doppler LiDAR velocity sensor and magnetic anomaly navigation.

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.

Magnetic Navigation Using Online Calibration Filter Analysis, Jonnathan D. Bonifaz

Theses and Dissertations

Magnetic navigation using the Earth’s magnetic anomaly field has proven to be a promising alternative that can provide coverage for a navigation system. This research demonstrates a magnetic navigation system using an extended Kalman filter (EKF) to aid an aircraft’s inertial navigation system (INS). Traditional magnetic anomaly navigation uses a “static calibration method,” which takes post-processed data to calibrate, obtaining the Tolles-Lawson coefficients needed for magnetic anomaly navigation filter compensation. These coefficients are constant and may cause drifts in the navigation filter if not re-calibrated. The online calibration method continuously updates the Tolles-Lawson coefficients as a filter state, reducing the …

Development Of A Three Degree-Of-Freedom Control Simulation For A Group 3 Large Unmanned Aircraft System, Majka Anna Wilczynski

Theses and Dissertations

Aircraft modeling and simulation has become increasingly important in the aviation world. Simulations allow for safer and more economical training prior to flight testing. In this project, a three degree-of-freedom control simulation coded in a MATLAB environment is used to assess and simulate the dynamic stability of group three unmanned aircraft system. By calculating, evaluating, and simulating the static and dynamic stability derivatives of the aircraft, this project will allow for the estimation of the handling qualities of an unmanned aircraft system. This can help mitigate risks that come along with altering the mass and aerodynamic properties of an aircraft, …

Gps-Denied Localization Of Daughter-Ships In A Mother-Daughter Ship Collaborative Environment, Ethan W. Jacquin

Theses and Dissertations

This research investigates the possibility of using the communication link between a mothership and daughter-ship UAV and an Extended Kalman Filter algorithm as a replacement of GPS, assuming a ranging link exists between the mothership and daughter-ship and that the mothership is GPS-enabled. A simulation study examines the viability of the approach and the effect of parameters such as distance, altitude, roll angle, speed, ranging sensor noise, and inertial measurement unit uncertainty were considered. The magnitude of the errors between predicted and measured position were examined and a range of acceptable flight parameters was formed.

Automated Find Fix And Track With A Medium Altitude Long Endurance Remotely Piloted Aircraft, Aubrey L. Olson

Theses and Dissertations

A limitation in RPA ISR operations is loss of target track if the command link is severed. For an RPA to effectively execute the ISR mission without a command link, it needs the capability to F2T targets autonomously. Automated Find Fix and Track (AFFTRAC) was developed to help solve this problem by demonstrating a proof of concept tactical autopilot. Monocular stereo vision was used to process sequential images acquired during orbit to produce a partial structural point cloud of the original structure. This partial structural point cloud was then exploited to create a holding area density for the aircraft to …