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EVALUATION OF THE LOGARITHMIC SPIRAL SEARCH PATTERN FOR ANTISUBMARINE WARFARE
Full text linkThis thesis investigates the ability of a searching submarine to locate a recently lost target submarine using the logarithmic spiral search pattern. The study was done by developing a stochastic, time-step simulation to data farm quantitative information. The measures of effectiveness are time to regain contact, distance away from contact on regain, and overall probability of detection. The independent variables are assumed target speed, the searcher’s starting distance away from the target, and the target’s frequency of maneuver. A key finding of this study is that this search pattern is the most effective within the first two hours, after which the likelihood of locating the target drops significantly. Additionally, there is a proportional relationship between target maneuver frequency and probability of detection and a negative correlation between the searcher’s starting distance away and the probability of detection. Finally, it was found that basing the searcher’s maneuvers by assuming a speed at the extremes of likely target speeds degrades performance. Overall, this study quantitatively supports the efficacy of the logarithmic spiral search pattern and provides a framework for future research to develop antisubmarine warfare tactics.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav
SELF-SUPERVISED PRE-TRAINING FOR PASSIVE SONAR
No full textThis study explores the effectiveness of self-supervised learning techniques in automated ship detection using passive sonar data. Passive sonar offers rich acoustic signatures that are valuable for ship detection, yet much of this data remains unlabeled and underutilized. We leverage the Underwater Passive Acoustic Dataset (UPAD) toolbox, developed and supported by the Naval Postgraduate School (NPS), to drive this research. Using UPAD and more than 20,000 hours of passive sonar data, we pre-train five transformer models with unique self-supervised approaches to learn data representations without explicit labels, establishing a robust foundation for downstream passive sonar tasks. After this initial pre-training on a noisily labeled subset, we fine-tune the models on a hand-labeled dataset to enhance the model’s ship detection capabilities. Our results demonstrate that self-supervised pre-training enriches the model’s understanding of spectrogram structures, producing separated embedding clusters in the absence of labels. Additionally, models pre-trained in this manner show improvement in classification tasks when fine-tuned with traditional supervised learning, outperforming models trained purely through supervised learning alone. This work underscores the potential of self-supervised learning in advancing automated ship detection from passive sonar audio.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav
CAPILLARY WAVE MODULATION BY SUBSURFACE FLOW
No full textSurface roughness serves as a critical diagnostic tool for inferring subsurface ocean dynamics, particularly under moderate conditions where capillary wave modulation can reveal subsurface flow. This study investigates the interaction between surface capillary waves and fine-scale surface flows as a result of subsurface dynamics. Using a spectral method, we solve phase-resolved governing equations to simulate the evolution of the capillary wave spectrum under varying surface flows and wind forcing directions. Surface roughness modulation depends primarily on flow strength, with wind direction having little influence except in highly directional wave fields. A minimum flow speed of 0.05–0.1 meters per second will induce detectable roughness changes, with wave-trapping effects intensifying as flow speed increases. Spectral analysis shows that these modulations manifest within key radar bands, though the signal-to-noise ratio remains low. The study establishes a threshold of detection for capillary wave modulation by subsurface flows, providing insights into the interpretation of synthetic aperture radar (SAR) and optical imagery. These findings contribute to advancing remote sensing methodologies for detecting small-scale oceanic processes and highlight the potential for improved subsurface flow retrieval from satellite observations.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, Royal Australian Nav
ANALYZING INDUSTRIAL-CONTROL-SYSTEMS ATTACKS WITH INTEGRATED SECURITY-MONITORING TOOLS AND ADVERSARY EMULATION
No full textCyberattacks on Internet-connected industrial control systems create risks to critical infrastructures. Mitigating these risks requires recognizing attack patterns, methods, and behavior of attackers. This research investigated ways to gather intelligence on adversaries using honeypots (deceptive systems for specifically collecting information) using intrusion-detection and security-information and event-management technologies. We deployed a cloud-based set of honeypots situated in several countries to collect data and analyze real-world attacks on simulated power grids and industrial (BACnet and Modbus) devices. Data collected by our honeypots was analyzed using Splunk, a commercial security-event-monitoring product, and Zeek, an open-source intrusion-detection system, to detect and characterize cyberattacks. We used the MITRE Caldera adversary-emulation toolset and the MITRE ATT&CK framework to simulate realistic attacks. We created Splunk queries and Zeek scripts, informed by the simulated attacks, to extract insights from collected data to generate Splunk alerts. We observed many exploits of network protocols and legitimate services, remote code execution, brute-force credential cracking, and denial of service. Our results confirmed that honeypots with integrated security monitoring can offer defenders a richer set of real-time alerts and actionable information about malicious activities than using single tools alone.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisCapitão de Corveta, Brazilian Nav
READ @your library Thomas M. Jamison (poster)
Full text linkA project of the Dudley Knox Library at the Naval Postgraduate School
2025-2026 Naval Postgraduate School International Programs Catalog
No full textCatalog of the International Graduate Programs Office containing course offerings for the 2025-2026 academic year
NEW YORK CITY: INTELLIGENCE FUSION OR INTELLIGENCE FISSION?
Full text linkThis thesis examines the evolution of counterterrorism strategies in New York City, highlighting the challenges of decentralized intelligence sharing between the New York City Police Department (NYPD) and the Fire Department of the City of New York (FDNY). Significant intelligence sharing failures have underscored the dangers of operational silos. Beginning with an examination of the Intelligence Community, this thesis evaluates how the absence of a fusion center affects the city’s ability to anticipate and respond to terrorist threats. Then, employing a comparative policy analysis with the United Kingdom’s centralized strategy, this thesis reveals critical gaps in New York City’s interagency coordination and information sharing.Drawing from New York City’s post-9/11 counterterrorism advancements and the UK’s integrated model, this thesis advocates a hybrid approach that bridges local adaptability with centralized coordination. Recommendations include instituting an EMS liaison officer to enhance field-level coordination, expanding access to the Domain Awareness System for broader situational awareness, and transforming the underutilized Joint Operations Center into a Networked Operations Center to facilitate seamless interagency communication and collaboration. This research contributes to policy discussions on measuring prevention and enhancing urban resilience against terrorism and serves as a foundation for future investigations into interagency intelligence frameworks.Distribution Statement A. Approved for public release: Distribution is unlimited.Civilian, FDN
BRIDGING THE GAP: APPLYING AI TO NSW’S RECRUITING AND RETENTION CHALLENGES
Full text linkThis thesis investigates the application of artificial intelligence (AI) and analytics in addressing Naval Special Warfare’s (NSW) recruiting and retention challenges. Informed by a comprehensive analysis of historical processes and NSW-specific challenges, coupled with insights from technology leaders and thoughtful considerations for legal and technological barriers, the study identifies low-cost, tech-based solutions with potential to enhance efficiency and effectiveness. The research validates two use cases for prompt implementation: an AI-powered customer relationship management (CRM) tool to streamline candidate engagement and conversion, and a large language model (LLM) to synthesize Naval Special Warfare Leader Assessment Program (NLAP) data into actionable leadership insights. These solutions aim to address critical gaps in force generation and retention by optimizing workflows, improving decision-making, and enhancing first-unit experiences. Other use cases, such as predictive detailing and integrated data systems, were deprioritized due to technological and regulatory barriers. A phased roadmap is recommended, starting with vendor-supported pilot programs to test and refine these AI solutions. By positioning NSW as a testbed for innovation, this research provides a scalable model for broader adoption across U.S. Special Operations Forces and the Department of Defense, driving innovation and efficiency at scale.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States NavyLieutenant, United States NavyCommander, United States Nav
AN ANALYSIS OF CHANGES IN THE PARENTAL LEAVE PROGRAM IN THE MARINE CORPS: A QUANTITATIVE STUDY
No full textThe 2023 expansion of the Marine Corps Military Parental Leave Program (MPLP) increased the parental leave allowance from 21 to 84 days for non-birth parents. This study uses yearly panel data from the Total Force Data Warehouse covering January 2018 to August 2024 to investigate the effects of this policy on parental leave utilization, the number of parental leave days taken, and changes in discretionary leave usage among active-duty Marines. Using linear probability and fixed effects regression models to estimate the policy effect, I found that male Marines were 9.1–12.6% more likely and female Marines were 6.8–13.7% more likely to use parental leave post-policy. However, males used only 63–68% of their full entitlement, while females used 76–80%. Discretionary leave decreased by 13.6–17.3% for males and 14.1–18.5% for females, suggesting previous reliance on discretionary leave to supplement parental leave.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisCaptain, United States Marine Corp
Method, System and Apparatus for Spacecraft Attitude Control Using B-Spline Interpolation
Full text linkA method, apparatus and system for controlling an attitude of a spacecraft, the spacecraft including an attitude control system operatively associated with a ground-based space craft control system. According to an exemplary embodi ment, the spacecraft attitude control system uses a B-spline interpolator for commanding the spacecraft. The methods and systems disclosed herein can be implemented in, for example, executable machine code and/or integrated circuit hardware