Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
With the advancement of 5G-Advanced Non-Terrestrial Network (5G-A NTN) mobile communication technologies, direct satellite connectivity for mobile devices has been increasingly adopted. In the highly dynamic environment of low-Earth-orbit (LEO) satellite communications, the synchronization of satellite–ground signals remains a critical challenge. In this study, a Doppler frequency-shift estimation method applicable to highmobility LEO scenarios is proposed, without reliance on the Global Navigation Satellite System (GNSS). Rapid access to satellite systems by mobile devices is enabled without the need for additional time–frequency synchronization infrastructure. The generation mechanism of satellite–ground Doppler frequency shifts is analyzed, and a relationship between satellite velocity and beam-pointing direction is established. Based on this relationship, a Doppler frequency-shift estimation method, referred to as DFS-BP (Doppler frequency-shift estimation using beam pointing), is developed. The effects of Earth’s latitude and satellite orbital inclination are systematically investigated and optimized. Through simulation, the estimation performance under varying minimum satellite elevation angles and terminal geographic locations is evaluated. The algorithm may provide a novel solution for Doppler frequency-shift compensation in Non-Terrestrial Networks (NTNs)....
Vision-and-Language Navigation (VLN) presents a complex challenge in embodied AI, requiring agents to interpret natural language instructions and navigate through visually rich, unfamiliar environments. Recent advances in large vision-language models (LVLMs), such as CLIP and Flamingo, have significantly improved multimodal understanding but introduced new challenges related to computational cost and real-time deployment. In this project, we propose a modular, plug-and-play navigation framework that decouples vision-language understanding from action planning. By integrating a frozen vision-language model, Qwen2.5-VL-7B-Instruct, with lightweight planning logic, we aim to achieve flexible, fast, and adaptable navigation without extensive model fine-tuning. Our framework leverages prompt engineering, structured history management, and a two-frame visual input strategy to enhance decisionmaking continuity across navigation steps. We evaluate our system on the Room-to-Room benchmark within the VLNCE setting using the Matterport3D dataset and Habitat- Lab simulation environment. Although our initial results reveal challenges in generalizing to unseen environments under strict evaluation settings, our modular approach lays a foundation for scalable and efficient navigation systems, highlighting promising directions for future improvement through enhanced environmental priors and expanded multimodal input integration....
This paper addresses the critical issue of unwanted interference in airborne GNSS receivers, crucial for navigational safety. Previous studies often simplified the problem, but this work offers a comprehensive approach, considering factors like Earth’s reflective properties, 3D calculations, and distinct radiation patterns. It introduces Spatial Interference Distribution Expression Heat-map and Operation Efficacy Plot graphs to visualize interference distribution along flight paths. The results highlight the significance of physical configuration and distance from interference sources on receiver performance. The algorithm developed can assess interference effects on GNSS receivers and aid in selecting optimal flight paths for minimal interference. This research enhances understanding and management of unintentional interference in airborne navigation systems....
Vulnerability impacts have increased in an unprecedented way with the effects of global warming, climate change, erosion, sea level rise, tsunami, flood, and drought—natural events that jointly cause geomorphological changes, especially in coastal zones. There are no analytical mathematical formulations under a set of assumptions due to the complexity of the interactive associations of these natural events, and the only way that seems open in the literature is through empirical formulations that depend on expert experiences. Among such empirical formulations are the Coastal Vulnerability Index (CVI), the Environmental Vulnerability Index (EVI), the Socioeconomic Vulnerability Index (SVI), and the Integrated Coastal Vulnerability Index (ICVI), which is composed of the previous indices. Although there is basic experience and experimental information for the establishment of these indices, unfortunately, logical aspects are missing. This paper proposes a Coastal Fuzzy Vulnerability Index (CFVI) based on fuzzy logic, aiming to improve the limitations of the traditional Coastal Vulnerability Index (CVI). Traditional CVI relies on binary logic and calculates vulnerability through discrete classification (such as “low”, “medium”, and “high”) and arithmetic or geometric means. It has problems such as mutation risk division, ignoring data continuity, and unreasonable parameter weights. To this end, the author introduced fuzzy logic, quantified the nonlinear effects of various parameters (such as landforms, coastal slope, sea level changes, etc.) through fuzzy sets and membership degrees, and calculated CFVI using a weighted average method. The study showed that CFVI allows continuous transition risk assessment by fuzzifying the parameter data range, avoiding the “mutation” defect of traditional methods. Taking data from the Gulf of Mexico in the United States as an example, the calculation result range of CFVI (0.38–3.04) is significantly smaller than that of traditional CVI (0.42–51), which is closer to the rationality of actual vulnerability changes. The paper also criticized the defects of traditional CVI, being that it relies on subjective experience and lacks a logical basis, and pointed out that CFVI can be expanded to integrate more variables or combined with other indices (such as the Environmental Vulnerability Index (EVI)) to provide a more scientific basis for coastal management decisions. This study optimized the coastal vulnerability assessment method through fuzzy logic, improved the ability to handle nonlinear relationships between parameters, and provided a new tool for complex and dynamic coastal risk management. Further research possibilities are also mentioned throughout the text and in the Conclusion section....
For the vast majority of spatial navigation research, experimental tasks are implemented in real-world environments. In recent decades, there has been an increasing trend toward virtual environments, which offer several benefits compared to their realworld counterparts while also having certain limitations. With these properties in mind, we have developed the Gallery of Memories (GA-ME), a customizable virtual-navigation task that is equipped for the assessment of both spatial navigation and memory within a highly controlled three-dimensional environment. The GA-ME provides a 3D position and head direction (pitch and yaw) sampling rate that is significantly higher compared to alternatives, enabling users to reconstruct a participant’s movement in the environment with remarkable spatiotemporal precision while its design, including nested spaces, makes it optimal for the study of place and grid cells in humans. These properties imbue the GA-ME with the potential to be widely utilized in both research and clinical settings for the in-depth study of spatial navigation and memory, with the possibility of conducting human intra- and extra-cranial electrophysiology, imaging, and eye-tracking measurements relevant to these faculties....
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