PLA Rocket Force University of Engineering

DDL-NSGA-II: A Distributed Navigation Interference Source Deployment Method Based on Improved NSGA-II

Distributed navigation interference is a critical technique for degrading the performance of multi-element adaptive nulling antennas, where optimal spatial deployment of interference sources is pivotal to maximizing overall interference effectiveness. However, interference signal...

Sequence-Conditioned Physics-Informed Neural Network for Lithium-Ion Battery State of Health Estimation Using Charging Segments at High State of Charge

Accurate and reliable state of health (SOH) estimation is essential for lithium-ion battery safety and lifetime management. Physics-informed neural networks (PINNs) integrate battery degradation knowledge with deep learning to improve the physical consistency of SOH estimation. H...

Remaining useful life prediction for multivariate stochastic degradation systems under functionally dependent failure modes

Multivariate stochastic degradation systems are widely encountered in complex industrial equipment, where performance deterioration exhibits coupling characteristics among multiple indicators. However, functionally dependent failure may still occur even when no single indicator e...

UAV RGB-NIR Tracking via Quality-Gated Dynamic Template Update in OSTrack

Existing single-modality object-tracking methods for unmanned aerial vehicles (UAVs) suffer from template mismatch under illumination variation, target occlusion, and fast motion, leading to tracking failure. We therefore propose an algorithm based on the one-stream Transformer t...

Infra-Net: a robust parallel decision-making network for discriminating natural hazards and anthropogenic infrasound events via multi-view feature learning

The accurate classification of infrasound signals is a cornerstone of global geophysical monitoring, essential for both natural hazard early warning systems (e.g., volcanic eruptions, debris flows, and earthquakes) and the verification of the Comprehensive Nuclear-Test-Ban Treaty...

Bond behavior and multi-scale enhancement mechanisms of UHPC–NC composite interfaces

Interfacial bond performance between ultra-high-performance concrete (UHPC) overlays and normal concrete (NC) substrates is critical to concrete repair and strengthening. This study investigates the bond behavior and enhancement mechanisms of UHPC–NC interfaces considering UHPC p...

A Leakage-Aware Evaluation of a Multi-Scale Attention Temporal Convolutional Network for Binary Network Intrusion Detection

Reliable evaluation is as important as model design in benchmark-based network intrusion detection. This study evaluates a Multi-Scale Attention Temporal Convolutional Network (MS-ATCN) for binary intrusion detection under a leakage-aware and reproducibility-oriented protocol on...

Error State Kalman Filter for Integrated Attitude Estimation Based on Data Fusion of MIMU Inertial Array and Magnetometer

Attitude estimation has increasingly relied on MEMS inertial measurement units (IMUs) owing to the low cost and miniature size, but the inherent high random noise and error accumulation limit long-term measurement accuracy. This article proposes an integrated attitude estimation...

A rocket debris impact threat assessment method incorporating value distribution of ground avoidance zones

With increasing launch frequency in China, rocket debris impact threats have become significant.Traditional trajectory methods often neglect nonlinear stochastic factors and spatial heterogeneity of population activities, leading to risk assessment deviations.This study aims to d...

Measurement report: Quantifying the trade-off between station number and spatial layout in sparse GNSS networks for calibrating all-weather FY-4A precipitable water vapor

Abstract. Integrating satellite-derived precipitable water vapor (PWV) provides data with high spatiotemporal resolution, which is crucial for monitoring and forecasting extreme weather. However, current fusion and calibration methods typically relies on dense GNSS networks, hind...

FFCS-Net: controlled multi-prior interaction via decoupled residual gating for lightweight defect detection

Embedding domain priors can compensate for the limited capacity of lightweight defect detectors, yet existing methods implicitly treat prior stacking as beneficial, overlooking the nonlinear interactions—synergy, perturbation, or conflict—that may arise when heterogeneous inducti...

Pt‐Mediated Co‐Adsorption of Hydroxyl and Nitrogen‐Heterocyclic Species Over Cu/CuO Heterostructure Enhances Coupled Azotriazole Electrosynthesis and Dual‐Electrode Hydrogen Production

ABSTRACT Electrocatalytic N─N oxidative coupling (OC) offers an eco‐friendly approach to produce value‐added azo materials, but suffers from sluggish kinetics and limited Faradaic efficiency (FE). The key fundamental issue is unfavorable competitive adsorption of hydroxyl groups...

Pt‐Mediated Co‐Adsorption of Hydroxyl and Nitrogen‐Heterocyclic Species Over Cu/CuO Heterostructure Enhances Coupled Azotriazole Electrosynthesis and Dual‐Electrode Hydrogen Production

ABSTRACT Electrocatalytic N─N oxidative coupling (OC) offers an eco‐friendly approach to produce value‐added azo materials, but suffers from sluggish kinetics and limited Faradaic efficiency (FE). The key fundamental issue is unfavorable competitive adsorption of hydroxyl groups...

Physics-informed neural predictor-corrector guidance for time-coordinated reentry of hypersonic glide vehicles

Abstract This paper addresses the time-coordinated reentry guidance problem for multiple hypersonic glide vehicles and proposes a physics-informed neural predictor-corrector guidance method. In the proposed framework, the path and terminal constraints are mapped to the bank-angle...

MGMD: A novel cross-working remaining useful life prediction method for rolling bearings under small-sample conditions

To address heavy data reliance and poor cross-working condition generalization of rolling bearing remaining useful life (RUL) prediction models under small-sample scenarios, this paper proposes a novel method integrating meta-learning, parallel temporal modeling and the domain ad...

Adaptive Spatial–Frequency Information Fusion for SAR Ship Detection

Synthetic-aperture radar (SAR) ship detection is a fundamental task in maritime remote sensing, supporting wide-area surveillance, traffic monitoring, and emergency response under all-weather imaging conditions. Existing deep detectors mainly rely on spatial cues such as intensit...

Deformable Sparse-Gradient Regularization for Extreme Image Denoising

Extreme noise severely degrades image quality in photon-limited imaging systems and challenges existing denoising methods. Classical total variation (TV) models rely on fixed local gradients and often introduce cross-edge smoothing, while deep learning methods may become unstable...

A New Variable Step-size LMS Algorithm and Its Analysis

The LMS (least mean square) algorithm is an adaptive filtering algorithm widely used in the fields of signal processing and system identification. To avoid the compromise between the convergence speed and the steady-state error for fixed step-size LMS algorithm, a variable step-s...