arXiv subjects

Xing Tong

Publications and source records attributed to Xing Tong.

6 recordsLinked to original sources

arXiv2026

A Beamforming Microwave Interferometric Radiometer for High-resolution Passive Imaging: Concept, Modeling, and Preliminary Demonstration

High-resolution passive microwave imaging is important for numerical weather prediction, disaster monitoring, and oceanographic studies, but kilometer-level spatial resolution remains difficult to achieve because of aperture limitations and the high complexity of large interferometric arrays. This paper proposes a beamforming microwave interferometric radiometer (BF-MIR) for high-resolution passive microwave imaging. BF-MIR employs beamforming-capable antennas as interferometric elements in a large sparse array. The enlarged spatial-frequency sampling interval reduces the required number of elements and the cross-correlation burden, while a large aperture-to-sampling-interval ratio factor (ASRF) array design enables narrow-beam spatial filtering to suppress brightness temperature (TB) aliasing caused by spatial-frequency under sampling. In addition, beamforming enables dynamic beam steering across multiple pointing directions, thereby compensating for the limited instantaneous coverage of narrow beams. A beamforming interferometric imaging model is established, and the relationships among spatial resolution, radiometric sensitivity, and effective field of view are analyzed. An image-domain Shift-Accumulate method is further introduced to analyze aliasing, based on which an aliasing suppression strategy is developed. In addition, a three-element proof-of-concept prototype provides preliminary experimental validation of dynamic beam interferometric measurement and dynamic beam observation modes. These results indicate that BF-MIR is a promising architecture for further spaceborne high-resolution passive microwave imaging.

eess.SP↗

arXiv2025

Leveraging Sidewalk Robots for Walkability-Related Analyses

Walkability is a key component of sustainable urban development. In walkability studies, collecting detailed pedestrian infrastructure data remains challenging due to the high costs and limited scalability of traditional methods. Sidewalk delivery robots, increasingly deployed in urban environments, offer a promising solution to these limitations. This paper explores how these robots can serve as mobile data collection platforms, capturing sidewalk-level features related to walkability in a scalable, automated, and real-time manner. A sensor-equipped robot was deployed on a sidewalk network at KTH in Stockholm, completing 101 trips covering 900 segment records. From the collected data, different typologies of features are derived, including robot trip characteristics (e.g., speed, duration), sidewalk conditions (e.g., width, surface unevenness), and sidewalk utilization (e.g., pedestrian density). Their walkability-related implications were investigated with a series of analyses. The results demonstrate that pedestrian movement patterns are strongly influenced by sidewalk characteristics, with higher density, reduced width, and surface irregularity associated with slower and more variable trajectories. Notably, robot speed closely mirrors pedestrian behavior, highlighting its potential as a proxy for assessing pedestrian dynamics. The proposed framework enables continuous monitoring of sidewalk conditions and pedestrian behavior, contributing to the development of more walkable, inclusive, and responsive urban environments.

cs.RO↗

arXiv2025

Robust Route Planning for Sidewalk Delivery Robots

Sidewalk delivery robots are a promising solution for last-mile freight distribution. Yet, they operate in dynamic environments characterized by pedestrian flows and potential obstacles, which make travel times highly uncertain and can significantly affect their efficiency. This study addresses the robust route planning problem for sidewalk robots by explicitly accounting for travel time uncertainty generated through simulated interactions between robots, pedestrians, and obstacles. Robust optimization is integrated with simulation to reproduce the effect of obstacles and pedestrian flows and generate realistic travel times. Three different approaches to derive uncertainty sets are investigated, including budgeted, ellipsoidal, and support vector clustering (SVC)-based methods, together with a distributionally robust shortest path (DRSP) method based on ambiguity sets that model uncertainty in travel-time distributions. A realistic case study reproducing pedestrian patterns in Stockholm's city center is used to evaluate the efficiency of robust routing across various robot designs and environmental conditions. Results show that, when compared to a conventional shortest path (SP) method, robust routing significantly enhances operational reliability under variable sidewalk conditions. The ellipsoidal and DRSP approaches outperform the other methods in terms of average and worst-case delay. Sensitivity analyses reveal that robust approaches are higher for sidewalk delivery robots that are wider, slower, and more conservative in their navigation behaviors, especially in adverse weather and high pedestrian congestion scenarios.

cs.RO↗

arXiv2024

Three-dimensional atomic interface between metal and oxide in Zr-ZrO2 nanoparticles

Metal-oxide interfaces with poor coherency have unique properties comparing to the bulk materials and offer broad applications in the fields of heterogeneous catalysis, battery, and electronics. However, current understanding of the three-dimensional (3D) atomic metal-oxide interfaces remains limited because of their inherent structural complexity and limitations of conventional two-dimensional imaging techniques. Here, we determine the 3D atomic structure of metal-oxide interfaces in zirconium-zirconia nanoparticles using atomic-resolution electron tomography. We quantitatively analyze the atomic concentration and the degree of oxidation, and find the coherency and translational symmetry of the interfaces are broken. Moreover, we observe porous structures such as Zr vacancies and nano-pores and investigate their distribution. Our findings provide a clear 3D atomic picture of metal-oxide interface with direct experimental evidence. We anticipate this work could encourage future studies on fundamental problems of oxides such as interfacial structures in semiconductor and atomic motion during oxidation process.

cond-mat.mtrl-sci↗

arXiv2023

Forecasting and Analysis of CSI 300 Daily Index and S&P 500 Index Based on ARMA and GARCH Models

In this paper, the ARMA(0,6)-GARCH(1,1) and ARMA(2,6)-eGARCH(1,1) models are constructed by applying ARMA and GARCH models to daily data of the CSI 300 and S&P 500 indices from 2018 to 2021, and the forecasts for the next 7 steps and the corresponding VaR and ES are calculated. After testing the sensitivity of the models, the two index stocks are compared and the corresponding conclusions are presented.

stat.AP↗

arXiv2020

"Butterfly Effect" in Shear-Banding Mediated Plasticity of Metallic Glasses

Metallic glasses response to the mechanical stress in a complex and inhomogeneous manner with plastic strain highly localized into nanoscale shear bands. Contrary to the well-defined deformation mechanism in crystalline solids, understanding the mechanical response mechanism and its intrinsic correlation with the macroscopical plasticity in metallic glasses remains long-standing issues. Through a combination of experimental and theoretical analysis, we showed that the shear banding process in metallic glasses exhibits complex chaotic dynamics, which manifests as the existence of a torus destroyed phase diagram, a positive Lyapunov exponent and a fractional Lyapunov dimension. We also demonstrated that the experimentally observed large plasticity fluctuation of metallic glasses tested at the same conditions can be interpreted from the chaotic shear-band dynamics, which could leads to an uncertainty on the appearance of the critical condition for runaway shear banding. Physically, the chaotic shear-band dynamics arises from the interplay between structural disordering and temperature rise within the shear band. By tuning the deformation parameters, the chaotic dynamics can be transformed to a periodic orbit state corresponding to a smaller plasticity fluctuation in metallic glasses. Our results suggest that the plastic flow of metallic glasses is a complex dynamic process, which is highly sensitive to initial conditions and reminiscent of the "butterfly effect" as observed in many complex dynamic systems.

cond-mat.mtrl-sci↗