基于连续性的分段与多位置时钟偏移估计的LEO多普勒匹配
LEO Doppler Matching from Power Spectrum Data with Continuity-Based Segmentation and Multi-Position Clock Offset Estimation
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中文总结 AI 辅助
本研究提出基于连续性分段与多位置时钟偏移估计的LEO卫星匹配框架，将定位误差从32.99公里降至1.84公里，显著提升关联精度与空间一致性。
中文摘要 AI 辅助
从无源软件定义无线电（SDR）频谱数据中提取的低地球轨道（LEO）卫星多普勒测量值需要与预测的卫星轨迹进行时间对齐，以实现可靠的卫星关联。在我们之前的框架中，多普勒斜率信息在分段生成和时钟偏移估计中均被使用，而时钟偏移是在单个粗略接收机位置处估计的。本研究提出了一种基于连续性多普勒分段和多位置时钟偏移估计的卫星匹配框架，以减少这些依赖性。首先仅利用时间和频率连续性生成多普勒分段，从而将分段生成与用于时钟偏移估计的斜率标准分离。随后，通过基于斜率兼容性和组合多普勒成本的两阶段过程，使用五个粗略接收机位置（包括一个城市级标称位置和四个周围位置）来估计时钟偏移。对齐后的分段随后使用基于相同多普勒斜率和去偏RMSE指标的匹配分数与候选卫星进行关联，并通过接收机定位评估所得关联结果。使用六小时无源Starlink/OneWeb监测数据的实验表明，在单位置时钟偏移估计下，与基于斜率的分段相比，仅基于连续性的分段并未改善接收机定位。然而，将所提出的多位置时钟偏移估计应用于相同的基于连续性的多普勒分段，将定位误差从32.99公里降低至1.84公里，在所评估的方法中实现了最低误差。对于所评估数据集的结果表明，当将多位置时钟偏移估计应用于基于连续性的多普勒分段时，卫星关联的空间一致性得到改善。
英文摘要
Low Earth orbit (LEO) satellite Doppler measurements extracted from passive software-defined radio (SDR) spectrum data require temporal alignment with predicted satellite trajectories for reliable satellite association. In our previous framework, Doppler slope information was used during both segment generation and clock offset estimation, while the clock offset was estimated at a single coarse receiver position. This study proposes a satellite matching framework based on continuity-based Doppler segmentation and multi-position clock offset estimation to reduce these dependencies. Doppler segments are first generated using only temporal and frequency continuity, thereby separating segment generation from the slope criterion used for clock offset estimation. The clock offset is then estimated using five coarse receiver positions, consisting of one city-level nominal position and four surrounding positions, through a two-stage procedure based on slope compatibility and a combined Doppler cost. The aligned segments are subsequently associated with candidate satellites using a matching score based on the same Doppler slope and bias-removed RMSE metrics, and the resulting associations are evaluated through receiver localization. Experiments using six hours of passive Starlink/OneWeb monitoring data show that continuity-based segmentation alone did not improve receiver localization compared with slope-based segmentation under single-position clock offset estimation. However, applying the proposed multi-position clock offset estimation to the same continuity-based Doppler segments reduced the localization error from 32.99 km to 1.84 km, achieving the lowest error among the evaluated methods. The results for the evaluated dataset show improved spatial consistency of satellite associations when multi-position clock offset estimation is applied to continuity-based Doppler segments.
发表机构
- School of Integrated Technology Yonsei University（延世大学综合技术学院）
- Future Technology Center Danam Systems Inc.（Danam Systems公司未来技术中心）
机构由 AI 辅助整理，请以论文原文为准。
