Browse Topic: Supply chain management
The demand for high-precision, real-time, and continuous localization in aerospace and low-altitude unmanned systems is steadily increasing. However, under weak GNSS availability, obstruction, and degraded ranging geometry, conventional 3D localization methods often suffer from insufficient observation constraints and severe accuracy degradation. To address observability degradation and localization error divergence in single-auxiliary-node systems, this paper proposes a 3D cooperative localization method based on maneuver reconfiguration of a single auxiliary node. Within a particle filtering framework, the method fuses target motion increments with single-shot range measurements to recursively estimate the target’s 3D position and heading. A geometric degradation metric and a radial-consistency metric are further constructed from the line-of-sight distribution and the alignment between target velocity and line of sight within a sliding window, enabling online detection of degraded observability. Once degradation is detected, the auxiliary node performs either lateral maneuvering or circular maneuvering to actively reshape the target–auxiliary relative geometry and restore observation diversity; meanwhile, the two metrics can also serve as feedback variables for adaptive maneuver adjustment. Comparative analyses are conducted under three modes, namely no reconfiguration, lateral maneuvering, and circular maneuvering, from the perspectives of 3D trajectory evolution, error time series, degradation-metric time series, and statistical error performance. Parameter sensitivity analyses and an additional nonlinear velocity-varying scenario are also included. Experimental results show that the no-reconfiguration mode exhibits clear error divergence under degraded conditions, whereas both maneuver-based strategies effectively reduce localization errors. Lateral maneuvering is more suitable for rapid recovery in the early degradation stage, while circular maneuvering achieves better overall accuracy and stronger post-degradation recovery capability. These results demonstrate the effectiveness and engineering feasibility of degradation-triggered active geometric reconfiguration for cooperative localization in low-configuration unmanned systems.
In recent years, the global demand for high-rate, high-reliability, and wide-coverage wireless communications has continued to grow. Traditional satellite communications are faced with bottlenecks such as spectrum scarcity, insufficient single-satellite capacity, and poor adaptability to highly dynamic channels. Relying on the advantages of wide-area coverage and multi-satellite cooperation, low Earth orbit (LEO) satellite constellations can construct distributed satellite MIMO systems and form virtual large-scale antenna arrays, significantly improving system capacity and reliability. However, such systems are characterized by large spatiotemporal scales, and their channels exhibit strong heterogeneity in dimensions such as delay, frequency, and polarization, which are difficult to accurately evaluate using existing methods. To this end, this paper proposes a large-spatiotemporal-scale channel characteristic analysis method for distributed LEO satellite MIMO systems. A satellite-terrestrial full-link channel model is established, and quantitative characterization of multi-dimensional heterogeneity is realized based on statistical boundary analysis. Combined with the H3 global grid system, large-scale simulations are carried out to statistically analyze the distribution laws of delay differences, frequency offsets, and polarization angle deviations under different user configurations. The unique value of this analysis method lies in that its output results can be used to determine the upper limit of buffer capacity required for the receiver to complete coherent combining of multi-channel signals and the frequency offset correction range required for signal acquisition, provide a quantitative basis for optimizing satellite set selection, and offer a solid theoretical model and data support for performance evaluation and parameter design of multi-satellite cooperative systems.
To address the low computational efficiency problem by numerical calculation and large cumulative error by long-term sequential iterative prediction during the process of predicting the satellite’s transient temperature fields, this paper proposes a Physics-Informed U-Net (PI-Unet) model. Specifically, this PI-Unet model uses multi-branch spatiotemporal features as its inputs and combines hard constraints with a physics-informed loss to ensure the physical consistency of the predicted temperature field. Furthermore, for the error accumulation problem in long-sequence autoregressive prediction models, this paper presents a model training method based on the concept of filtering. Under the guidance of this method, the PI-Unet model can develop a long-term sequence prediction capability while keeping the accuracy of spatial temperature field prediction, achieving high-precision spatiotemporal prediction. By actively injecting prediction errors through a scheduled sampling strategy, along with a multi-step rolling training strategy, the PI-Unet model not only learns the governing physical laws of the spatial distribution of the transient temperature field, but also acquires the filtering capability to mitigate the accumulation of the long-term sequence rolling prediction errors. The experimental results indicate that the PI-Unet model maintains the maximum absolute error of predicting spatial transient temperature field stably below 5.5K and the error of the rolling-predicted transient temperature field in one orbit period less than 6K. In addition, the time for a single-step prediction is reduced to 0.005s, and the time for a total-period prediction is less than 0.5s. Therefore, this research provides a strong and high-efficiency technical support for the real-time monitoring of the satellite’s on-orbit temperature fields.
The persistent rate of accidents and fatalities involving legacy tactical military vehicles underscores a critical need for Enhanced Situational Awareness (ESA) technologies. However, the prohibitive cost and lengthy development cycles associated with full MIL-STD ruggedization often prevent these safety systems from reaching the in-service non-combat vehicles with limited driver visibility. This paper suggests a strategic shift in procurement policy: The adoption of relaxed ruggedization standards for vehicles operating in non-combat, administrative, and training roles. By deriving requirements from high-stress commercial sectors— such as heavy mining, steel production, and NASCAR racing—the military can utilize electronics designed for "extreme industrial" rather than "battlefield" environments. The principal objectives of this relaxation is cost reduction, lowering the barrier to entry and increasing the likelihood of ESA deployment across the legacy fleet. Furthermore, this approach aligns with Modular Open Systems Approach (MOSA) principles by enabling the integration of non-proprietary commercial devices. Utilizing these accessible technologies on legacy platforms creates a real-world testbed to evaluate technological advances rapidly. These insights can then inform and accelerate the development of future MIL-STD systems for combat vehicles, effectively shortening the traditional development life cycle while prioritizing the immediate enhanced protection of service member lives.
ISO 26262ISO/SAE 21434ISTQB/ASPICEMOSAGCIAVICTORY
Ground combat vehicles traditionally remain in service for decades, yet their rigid architectures make them costly to upgrade and slow to adapt to evolving threats. While the Department of War's 2025 Modular Open Systems Approach (MOSA) mandate aims to address this challenge, implementation barriers persist inconsistent vendor interpretations, physical and logical interoperability gaps, and IP complexities hinder progress. This paper proposes a reformed MOSA framework for ground vehicle Portfolio Acquisition Executives that redefines the government's role from system architect to ecosystem governor. The framework comprises four pillars: tiered standards balancing mandatory physical integration with vendor innovation, digital validation pipelines accelerating compliance verification, dynamic IP rights preventing vendor lock-in, and strategic portfolio management aligning investments with ground vehicle capability priorities. Special emphasis addresses integrating AI capabilities. This reformed approach enables rapid fielding of advanced ground vehicle capabilities at commercial innovation speed.
We present atomistic molecular dynamics simulations of linear and branched fluorinated polymer chains, with and without imidazole functionalization, designed as a model for solvent-free proton-conducting membranes for high-temperature fuel cell applications. Simulations conducted over a temperature range of 300 to 550 K, and diffusion-based relaxation times reveal that glass transition temperatures depend on polymer architecture: the branched and functionalized systems exhibit transitions near 400 K compared to 500 K for the linear chain. Fluorine-fluorine radial distribution functions demonstrate that branching disrupts local packing order, while imidazole substitution creates specific intra-chain interactions. Radius-of-gyration distributions reveal that branching significantly increases chain extension and creates multiple conformational families, whereas imidazole groups stabilize compact conformations at low temperatures that transition to more diverse states upon heating. These findings provide molecular-scale insight into how polymer architecture controls thermal transitions and structural organization in model high-temperature polymer electrolyte membranes.
The impending formal adoption of SAE J1939-91C creates an urgent need for rigorous, repeatable validation methods that extend beyond functional conformance. This paper presents a structured validation and benchmarking framework, with a focus on performance characterization across dynamic vehicle configurations. Building on prior work in secure network formation, rekeying, and Golden Tester concepts, we define a minimal, transport-agnostic set of cryptographic and protocol test vectors for deterministic validation of secure message authentication, alongside simulation-based methods for evaluating network formation and rekey behavior. The framework integrates performance metrics such as secure message latency, rekey time and throughput, while also introducing cybersecurity-specific diagnostics and logging requirements for gateway module implementation. Security validation scenarios are mapped to explicit detection and response benchmarks. The resulting methodology provides OEMs, Tier-1 suppliers, and research organizations with a practical, reproducible approach to validating J1939-91C implementations, supporting both development-phase evaluation and ongoing lifecycle assurance.
This paper details the successful scaling demonstration of a comprehensive supply chain screening process for commercial off-the-shelf (COTS) motherboard subassemblies used in tactical servers for naval applications. Our approach leverages Power Fingerprinting (PFP) technology, which uses unintended analog emissions and machine learning to provide independent, non-destructive, and scalable integrity assessment of microelectronics. The primary goal of the effort was to demonstrate the effectiveness and scalability of the PFP screening process without disrupting or delaying the manufacturing workflow. The screening successfully detected hardware and firmware modifications and identified two cases of abnormal behavior: unusual BIOS power reset and elevated CPU sensor readings on two motherboard subassemblies. Following our quality control forensic analysis, we determined the root cause of these anomalies and their potential impact on the host platform.
Defense acquisition often struggles to match the pace of private investment, slowing the transition of mature commercial technologies into military use. This paper examines how aligning government acquisition with venture-oriented business models can increase industry participation, accelerate fielding, and reduce government program office risk. Using autonomous construction as a case study, it highlights how commercial investment has advanced autonomy while traditional procurement limits adoption. The paper outlines approaches such as non-traditional partnerships, phased acquisition, and performance-linked revenue structures to improve flexibility, leverage private capital, and expand the Defense Industrial Base while speeding operational capability delivery. Citation: Mazzara, M., San Nicolas, A., Gadea, J., Himmel, M., Kruger, J., Gill, C., & Simon, A., Soylemezoglu, A., Netchaev, A., Nottage, D., Klein, J. “Mobilizing Innovation: Venture Capital Alignment for Defense with Autonomous Construction Case Study” In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA Michigan Chapter, Novi, MI, August 11–13, 2026.
After an investigation into a fruit and vegetable storage compartment on a ship, this paper proposes a method for creating different temperature zones within a single storage unit. To perform this approach, a top perforated plate air supply system should be implemented, and storage panels should act as partitions to make temperature control more accurate in different zones within the same compartment. This method ensures that fruits and vegetables can be stored for the best flavor at suitable temperatures, enabling fewer separate storage units on the ship. According to the experimental results, this solution can preserve various types of fruits and vegetables under different conditions during long trips, deal with the challenge of chilling or freezing injury due to mixed storage, and save the cold storage capacity on the ship. The proposed method has significant value in engineering applications.
The multi-articulated vehicle uses distributed drive mode. Due to its large degree of freedom of movement and the large number of driving shafts, different torque distribution methods affect the operational stability of the vehicle, how to coordinate and distribute the torque of each driving motor has become an urgent problem to be solved. To improve drive stability of the multi-articulated vehicles, propose a layered torque allocation control strategy. The upper-layer sliding mode controller determines the required additional yaw moments of each car body based on the linear reference model, the controller is characterized by swift response and a strong ability to resist interference. The lower-level allocation module comprehensively considers the torque output limitations of the electric hub motors, the prevailing road adhesion state, and the corrective yaw moment constraints given by the upper layer, and constructs an optimization objective function centered on the uniformity and stability of tire load. The optimal distribution of driving forces for each wheel is completed by solving this function dynamically. To validate the strategy's effectiveness, a vehicle dynamics model is built in the multi-body dynamics software ADAMS/View. Using a joint simulation framework integrating ADAMS/View and MATLAB®/Simulink, the effect of the layered control strategy is evaluated in comparative simulation with uncontrolled situation under U-turn and single lane change conditions. The simulation outcomes demonstrate that, compared to uncontrolled situation, the yaw rate deviation of each car body under the torque layered control are significantly reduced, and the adhesion utilization rate of tire is also effectively controlled, thereby the driving stability is improved.
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