增强网络空间坐标系性能的时延滤波方法OA
Delay filtering method for enhancing the performance of cyberspace coordinate systems
网络空间坐标系的准确性依赖于高质量的时延数据,但实际网络环境中的随机污染现象严重制约了传统滤波方法的性能.针对现有方法在噪声抑制、统计特征保留与阶梯性变化感知之间的权衡不足,提出了一种基于 SG 滤波的分段时延滤波方法(SDF).该方法通过动态分段策略,结合变化率检测划分时延数据段.对长段落,采用 SG 滤波器拟合趋势;对短段落,则采用中值滤波抑制噪声,从而实现异常值抑制与时延曲线平滑,同时保留阶梯式突变特征.在真实网络数据集上的验证实验表明,SDF方法可将 95%分位数相对误差 NFPRE降低约 18.59%,显著降低时延变化率.同时,该方法显著提升了网络空间坐标系统的定位精度与稳定性.
The accuracy of cyberspace coordinate systems depends on high-quality delay data,yet random noise in real-world network environments severely limits the effectiveness of traditional filtering methods.To address the insufficient balance among noise suppression,statistical feature preservation,and step-change detection in existing approaches,this paper proposes a segmented delay filtering(SDF)method based on the Savitzky-Golay(SG)filter.The method dynamically segments delay data using a change rate detection strategy.For long segments,the SG filter is applied to fit the trend,while median filtering is used for short segments to suppress noise.This hybrid approach effectively suppresses outliers and smooths delay curves while preserving step-like abrupt changes.Validation experiments on real network datasets demonstrate that the SDF method reduces the 95%percentile relative error(NFPRE)by approximately 18.59%and significantly decreases delay variation rates,thereby enhancing the positioning accuracy and stability of cyberspace coordinate systems.
李雄庆;赵冬青;李林阳;樊文哲;袁俊俨
信息工程大学地理空间信息学院,郑州 450001信息工程大学地理空间信息学院,郑州 450001信息工程大学地理空间信息学院,郑州 450001||武汉大学测绘学院,武汉 430079信息工程大学地理空间信息学院,郑州 450001信息工程大学地理空间信息学院,郑州 450001
信息技术与安全科学
时延滤波时延随机污染SG滤波算法网络空间坐标系
delay filteringrandom delay contaminationSG filtering algorithmcyberspace coordinate system
《电子科技大学学报》 2026 (4)
571-579,9
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