发表机构
School of Integrated Technology Yonsei University; Department of Electronics Engineering Chungbuk National University（延世大学综合技术学院; 忠北国立大学电子工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用NASA SRTM 30m和NGII 90m DEM，分析eLoran系统空间ASF与路径地形特征的相关性，发现高分辨率DEM相关性更强，为机器学习ASF预测的地形数据选择提供依据。
AI 中文摘要
ASF是eLoran系统定位误差的主要来源，并受信号传播路径沿线地形特征的影响。本研究利用NASA SRTM 30米和NGII 90米DEM，分析了空间ASF与基于路径的地形特征之间的相关性。沿从光州eLoran发射机到仁川和平泽港区测量位置的传播路径，提取了路径平均高程和路径平均坡度。结果表明，两种地形特征均与空间ASF强相关，且较高分辨率的NASA SRTM DEM通常表现出更强的相关性，尤其是路径平均坡度。这些发现证明了DEM空间分辨率在地形基空间ASF分析中的重要性，并为未来基于机器学习的ASF预测选择地形数据提供了依据。
英文摘要
The ASF is a major source of positioning error in eLoran system and is affected by terrain characteristics along the signal propagation path. This study analyzes the correlations between spatial ASF and path-based terrain features using NASA SRTM 30m and NGII 90m DEMs. Path mean elevation and path mean slope were extracted along the propagation paths from the Gwangju eLoran transmitter to measurement locations in the Incheon and Pyeongtaek port areas. The results show that both terrain features are strongly correlated with spatial ASF, with the higher-resolution NASA SRTM DEM generally exhibiting stronger correlations, particularly for path mean slope. These findings demonstrate the importance of DEM spatial resolution in terrain-based spatial ASF analysis and provide a basis for selecting terrain data for future machine-learning-based ASF prediction
Commentssubmitted to ICCE-Asia 2026
