Naval Postgraduate School
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What drives the Sino-Russian partnership? Regime insecurity, aggressive overreach, and authoritarian great power alignment
No full textThis paper examines the drivers behind the Sino-Russian partnership—the most consequential alignment since the Cold War. Challenging existing accounts, the paper argues that Moscow and Beijing converged not because of external threats, or regime insecurity, but when these two dangers com bined. Tracing the trajectory of the Sino-Russian rapprochement, the analysis shows that the weakening Putin regime sought China’s support to offset the high geopolitical cost of conflicts that it launched to preserve itself.Fearing that a collapse of Putinism could undermine the Chinese regime, Beijing, in turn, maintained a lifeline for Russia’s beleaguered dictatorship. The paper pos its that the Sino-Russian convergence is therefore best understood as a three level game, where the two dictatorships leverage their international actions (level 1) and mutual relations (level 3) to secure their power domestically (level 2). This framework offers crucial insights for containing Russian aggression and preventing escalating tensions between China and Western powers.Department of the Nav
ARTIFICIAL INTELLIGENCE MODELS FOR ELECTRONIC INTERFERENCE DETECTION AND CLASSIFICATION ON GLOBAL NAVIGATION SATELLITE SYSTEMS
No full textGlobal navigation satellite systems, such as GPS, transmit position, navigation, and timing data over the electromagnetic spectrum. These transmissions are susceptible to interference via malicious actors performing jamming or spoofing on them. Due to the remote nature of space, direct human oversight is not always possible; therefore, automated detection and classification methods are needed. Automated detection and classification of interference can give end-users better awareness about the integrity of the data they receive and allow them to take appropriate countermeasures if needed. This thesis investigated the use of artificial intelligence, specifically deep learning architectures, to provide automated detection and classification of electronic interference for use on resource-constrained flight hardware. The main challenge with these models is that they typically require substantial computer resources. These resources are not available on small satellite flight computers, so an efficient model architecture is needed. Ultimately, a dense autoencoder architecture was found to have the best balance between performance and storage requirement. This thesis demonstrated that lightweight models can automatically detect and classify electronic interference and provides methods for integrating these models into flight hardware. The methods developed in this research are aimed at satellite developers who wish to provide reliable data to their end-users.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisEnsign, United States Nav
STRATEGIC ACQUISITION FRAMEWORK FOR MANNED-UNMANNED TEAMING IN NAVAL AVIATION
No full textUnmanned aerial systems (UAS) are at the cutting edge of the United States military's development efforts. The U.S. Navy aims to integrate UAS into Carrier Air Wings (CVW), leveraging Manned-Unmanned Teaming (MUMT) to extend and increase its operational capabilities. Programs of record for past systems, such as the MQ-8, MQ-4C, and MQ-25, have faced significant challenges, including scope creep, cost overruns, and unsustainable integration. MUMT must overcome technical, operational, and logistical challenges while coordinating with existing CVW operations. To assess these challenges, a modified capabilities-based assessment (CBA) was used to determine the current capability gaps, followed by a Doctrine, Organization, Training, materiel, Leadership, Personnel, and Facilities (DOTmLPF) analysis to identify non-materiel solutions to those existing gaps. The study revealed a definitive need for UAS to be integrated into CVWs that incorporate MUMT. However, single-role, attritable UAS must be expanded to mature technology and demonstrate that MUMT can perform in contested environments. The Navy needs to pivot to a more open and capability-centric module of sustainment for these systems. Additional non-materiel solutions were found using the DOTmLPF framework, showing shortcomings in many areas where MUMT requires support. Collaboration with allies to rapidly adopt these systems will help close the capability gaps in the CVWs and propel naval aviation into the future.Distribution Statement A. Approved for public release: Distribution is unlimited.Ensign, United States NavyEnsign, United States Nav
COMPARISON OF DECISION POLICIES FOR OPTIMAL REPAIR-REPLACE IN INFRASTRUCTURE SYSTEMS
No full textCritical infrastructure systems are under threat: natural disasters, degradation, and enemy action form a recipe for disruption. Many systems rely on maladapted or incomplete models to forecast and respond to disruptions; these are especially vulnerable to the increasing severity of disruptions as well as over-reliance on artificial intelligence and machine learning (ML). Every Department of Defense installation has infrastructure systems that it deems critical, and the goal for this research is to support more adaptive, resource-aware policies for maintaining mission-critical infrastructure in times of peace and crisis. We formulate a network flow problem with uncertain edge failures and model repair-replace decisions as a Markov Decision Process (MDP). We then compare optimal decision policies derived from linear programming with approximated policies generated via Q-learning and a heuristic approach. We leverage stochastic simulation to determine the expected costs of following each policy and compare their performance. The primary output of this thesis is our demonstrated use of a method to directly compare ML and heuristic policy approximations to a known optimal solution. This technique helps elucidate when different decision models can be deployed in more complex systems where the optimal solution is computationally infeasible.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, United States ArmyStrategic Environmental Research and Development Program (SERDP), Washing, DC 20301-350
ASSESSING THE RESILIENCE OF DIFFERENT ALTERNATIVE FUELS FOR UNMANNED AERIAL VEHICLES
No full textOperational alternative energy is a recurring discussion within the Department of Defense (DoD). Energy access has been limited due to the demand only being met with fossil fuels like petroleum oil. This thesis answers the question, How can alternative fuels increase resiliency of UAVs (unmanned aerial vehicles) in a mission? In this thesis, resiliency is defined by a system’s ability to withstand, adapt, and endure various scenarios, ensuring continued operational effectiveness and mission performance. First, research was conducted on both the ScanEagle and Fire Scout UAVs for performance parameters using their conventional fuel type (JP-5). Then, six simulations in ExtendSim, a discrete-event simulation program, were built to assess the resilience of both UAVs using three fuel types: JP-5, hydrogen, and ammonia. Through partition tree analysis, some critical findings emerged. First, fuel type was the main factor of interest and yielded the highest endurance while decreasing the fuel consumption rate. Second, while hydrogen fuel yielded the lowest fuel consumption rate and highest endurance, longer mission durations and higher power requirements required the fuel selection to be ammonia or JP-5. This thesis provides additional insights for the Department of Energy to consider the resilience of alternative fuels while developing and establishing fuel-related requirements.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant, United States Nav
Faces of NPS: Computer Science Class of '91
No full textFaces of NPS features interviews spotlighting the students, faculty, staff and alumni of our Nation's premier defense education and research institution
ESTIMATING SHIP SOURCE LEVELS USING AIS AND HARP DATA
No full textAccurate estimates of ambient noise are essential for predicting sonar performance and conducting effective Anti-Submarine Warfare (ASW) operations. One major source of ambient noise in the marine environment is the commercial shipping industry. This industry has expanded significantly since the mid-20th century due to increased globalization and consumer demand. This study examined the feasibility of estimating ship source levels in marine environments using Automatic Identification System (AIS) shipping data, passive acoustic recordings from a High Frequency Acoustic Recording Package (HARP), and acoustic propagation modeling. By analyzing the acoustic signatures of different ships, correlations between various ship characteristics and their source levels were examined. These correlations will aid in developing a foundational database for use in ambient noise models which are essential for ASW and broader naval operations.Distribution Statement A. Approved for public release: Distribution is unlimited.Lieutenant Commander, United States Nav
BUILDING PARTNER CAPACITY IN THE MIDDLE EAST: ARE THEY SHOULDERING MORE OF THE BURDEN?
No full textThis thesis evaluates the effectiveness and strategic relevance of U.S. security cooperation initiatives in the Middle East from 2011 to 2024. Despite decades of investment in building partner capacity, many regional allies and partners remain dependent on U.S. assistance, raising questions about the efficacy and sustainability of these programs. By analyzing security cooperation efforts tied to major regional crises—including the conflicts in Yemen, Israeli–Palestinian tensions, and Iranian aggression—this study examines whether such initiatives have meaningfully advanced U.S. defense and foreign policy goals or merely delayed direct American involvement. It draws from official plans, reports, and literature to assess the correlation between security cooperation efforts and outcomes, while weighing the benefits of influence, access, and deterrence against the risks of regional instability, human suffering, and reputational damage. The study also explores the implications of continued investment amid a strategic pivot toward countering China and Russia. Ultimately, this thesis asks whether the current security cooperation model should remain a central component of U.S. Middle East policy or transition into a supplemental role. It concludes that a more deliberate, ethically grounded, and outcomes-driven approach is needed to ensure these initiatives genuinely enhance regional self-reliance while aligning with broader global strategic objectives.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisMajor, United States Marine Corp