【目的】随着智慧城市建设中信息技术的深度应用,GNSS轨迹数据呈爆炸式增长,但其轨迹生成过程易受信号干扰与传感器故障影响而产生噪声。本文旨在设计新型噪声识别与修复算法,以提升原始GNSS轨迹数据的处理精度与质量。【方法】针对轨...【目的】随着智慧城市建设中信息技术的深度应用,GNSS轨迹数据呈爆炸式增长,但其轨迹生成过程易受信号干扰与传感器故障影响而产生噪声。本文旨在设计新型噪声识别与修复算法,以提升原始GNSS轨迹数据的处理精度与质量。【方法】针对轨迹噪声识别问题,本文提出基于密度矩阵的自适应DBSCAN算法,其具有超参数无关特性,可敏感捕获低幅值噪声点,同时避免连续转向点的误判。针对噪声修复问题,提出基于轨迹分段的函数构造式修复算法:首先采用道格拉斯-普克(Douglas-Peucker,DP)算法压缩轨迹数据实现分段;其次定位含噪声轨迹段,基于段内有效点构造拟合函数;最终依据相邻点时空属性修复噪声数据。相较于主流插值算法(如拉格朗日、牛顿、埃尔米特、线性、三次样条及最近邻插值),本方法通过规避全局特征依赖,显著保留了噪声点蕴含的局部信息特征。【结果】基于长春市1500名志愿者2024年8月19日—9月1日的原始GNSS轨迹数据,设计2组对比实验。第1组将新型识别算法与原始DBSCAN及其主流衍生算法(KANN-DBSCAN、BDT-ADBSCAN)进行对比。实验表明:新算法在轮廓系数(SC)、Calinski-Harabasz指数(CHI)、Da‐vies-Bouldin指数(DBI)3项指标均取得最优值,优化幅度分别为40.17%~381.80%、20.03%~235.18%、23.42%~79.53%。第2组实验对比新型修复算法与6类经典插值方法(拉格朗日、牛顿、埃尔米特、线性、三次样条、最近邻),结果显示:新算法在轨迹相似性度量指标(Dynamic Time Warping,DTW)上全面优于对比方法,整体优化幅度达43.18%~80.43%。【结论】本文提出的噪声识别与修复算法显著提升了原始GNSS轨迹的质量精度,可高效支撑大规模轨迹数据预处理任务,为时空轨迹挖掘研究提供高质量数据基础。展开更多
碳捕集、利用和封存(Carbon Capture,Utilization and Storage)已经成为减少大气中二氧化碳的一种有效方法,但大量的二氧化碳注入地下可能会引起地表发生变形.为了探究二氧化碳注入后注采区的地表变化情况,本文基于45景Sentinel-1A升轨...碳捕集、利用和封存(Carbon Capture,Utilization and Storage)已经成为减少大气中二氧化碳的一种有效方法,但大量的二氧化碳注入地下可能会引起地表发生变形.为了探究二氧化碳注入后注采区的地表变化情况,本文基于45景Sentinel-1A升轨影像,运用SBAS-InSAR技术对国内某CO_(2)陆地埋存实验区域进行为期两年半形变监测工作,并构建了一种适用于小区域顾及GNSS的大气延迟改正模型.根据结果显示,本文提出的大气改正模型可以有效削减干涉图中的对流层延迟误差.根据InSAR结果显示,在注气过程中地表沿卫星视线方向靠近卫星,即地表发生隆起现象.通过提取注气井附近的形变时间序列,转换到垂直方向与GNSS数据对比,发现在注气之后,地表先隆起,几个月后开始逐渐回落.综合分析来看,结合GNSS与InSAR技术可以观测到该地区地表微小形变信息,GNSS监测站不仅可以用于校正InSAR干涉图中的大气延迟误差,还可以用于验证InSAR监测结果.展开更多
现有GNSS水汽层析研究主要聚焦于如何提升卫星观测数据利用率,但在卫星信号数据优选方面研究较少,导致穿过同一组网格集的层析观测方程线性近似且方程系数矩阵列向量元素多数为零,水汽层析模型病态严重。针对该现状,本文提出一种GNSS卫...现有GNSS水汽层析研究主要聚焦于如何提升卫星观测数据利用率,但在卫星信号数据优选方面研究较少,导致穿过同一组网格集的层析观测方程线性近似且方程系数矩阵列向量元素多数为零,水汽层析模型病态严重。针对该现状,本文提出一种GNSS卫星信号自适应优选的水汽层析方法,解决层析模型设计矩阵零元素较多和层析模型病态的难题。该方法基于网格覆盖率最大原则确定层析区域水平网格划分,并发展联合卫星高度角与方位角阈值的卫星信号自适应优选方法,克服水汽层析模型观测方程线性近似的难题。本文选取香港地区2013年5月2日—2013年5月7日共6 d 12个GNSS测站及1个无线电探空站数据为例进行试验。与现有方法相比,本文方法能在降低卫星信号利用率的同时保证网格覆盖率,克服相似卫星信号造成层析模型设计矩阵病态的现状。以无线电探空数据为真值,发现本文方法反演水汽密度廓线的平均RMS、MAE和Bias分别为1.03、0.80和0.13 g/m^(3),优于传统方法的1.25、0.97和0.10 g/m^(3),其RMS改善率为20.78%;此外,本文方法在模型解算效率方面也优于传统方法,其模型计算效率平均提升9.51%。展开更多
In Global Navigation Satellite System(GNSS)meteo rology,the atmospheric weighted mean temperatu re(T_(m))is a critical intermediate parameter for converting zenith wet delay(ZWD)to precipitable water vapor(PWV),essent...In Global Navigation Satellite System(GNSS)meteo rology,the atmospheric weighted mean temperatu re(T_(m))is a critical intermediate parameter for converting zenith wet delay(ZWD)to precipitable water vapor(PWV),essential for accurate atmospheric water content estimation.However,global models often overlook regional climatic variability,leading to reduced accuracy in localized applications.This study introduces an improved T_(m)model developed using radiosonde observations across Iran and GNSS radio occultation(RO)profiles from CHAMP,GRACE,MetOp-A/B/C,COSMIC,TerraSAR-X,and TanDEM-X missions collected between 2007 and 2022.A novel integral formulation was proposed to estimate T_(m)more accurately by incorporating vertical water vapor distribution and temperature linearity.Based on this formulation,three regional T_(m)models were constructed using annual,semiannual,and diurnal periodicities,along with surface temperature(T_(s)),each varying in structure and complexity.Validation against independent radiosonde observations from 2022 showed that Models Two and Three outperformed the Bevis model,reducing RMSE by 30.7%.When evaluated against GNSS RO profiles,Model One—excluding T_(s)due to its inaccessibility in RO data—yielded the highest accuracy,with a 42.6%improvement in RMSE over the Bevis model.To evaluate the practical effectiveness of the proposed T_(m)model,PWV was derived from GNSS data at the tehn and tabz stations during the second half of 2022and compared with PWV values obtained from co-located radiosonde observations in Tehran and Tabriz.Using T_(m)from Model One improved PWV estimation compared to the Bevis model,reducing RMSE and MAE by up to 54%and 53.8%in Tabriz and 50.6%and 52.9%in Tehran,respectively.These results demonstrate that regionalized T_(m)modeling,particularly approaches that avoid dependence on T_(s),can significantly enhance GNSS-based PWV estimation in areas with limited surface data.展开更多
To characterize the spatial patterns of vertical crustal movement of Chinese mainland,GNSS imaging technology was applied to map the tectonic deformation of the region.In this study,the vertical crustal velocities inf...To characterize the spatial patterns of vertical crustal movement of Chinese mainland,GNSS imaging technology was applied to map the tectonic deformation of the region.In this study,the vertical crustal velocities inferred from GNSS data for Chinese mainland over two decades were rigorously estimated.First,by analyzing the vertical displacement time series from continuous GNSS stations and environmental load data,we found that the annual and semi-annual vertical displacements are highly correlated.This indicates that the vertical seasonal variations on the ground surface are mainly caused by environmental loading.After removing the seasonal variations caused by environmental loads from the GNSS time series,we applied an improved PCA technique to filter out common mode errors.Next,we estimated the optimal noise models for the filtered time series and derived the vertical velocity field of Chinese mainland.Finally,we employed an empirical Spatial Structure Function(SSF)to image the tectonic deformation of Chinese mainland.This method effectively mitigates issues with abrupt circular arc-shaped boundaries in GNSS imaging caused by sparse station networks.The imaging results show that vertical crustal deformation in Chinese mainland generally ranges from-3 to 3 mm/yr,with significant spatial variability.The central and northern parts of Qinghai-Xizang Plateau are identified as primary subsidence zones,indicating that plate boundaries and tectonic compression continue to shape the crustal movement in these regions.The major uplift zones are located in northern and central China,likely linked to regional tectonic activity and plate compression.Subsidence deformation in parts of eastern China appears to be influenced by human activities.展开更多
文摘【目的】随着智慧城市建设中信息技术的深度应用,GNSS轨迹数据呈爆炸式增长,但其轨迹生成过程易受信号干扰与传感器故障影响而产生噪声。本文旨在设计新型噪声识别与修复算法,以提升原始GNSS轨迹数据的处理精度与质量。【方法】针对轨迹噪声识别问题,本文提出基于密度矩阵的自适应DBSCAN算法,其具有超参数无关特性,可敏感捕获低幅值噪声点,同时避免连续转向点的误判。针对噪声修复问题,提出基于轨迹分段的函数构造式修复算法:首先采用道格拉斯-普克(Douglas-Peucker,DP)算法压缩轨迹数据实现分段;其次定位含噪声轨迹段,基于段内有效点构造拟合函数;最终依据相邻点时空属性修复噪声数据。相较于主流插值算法(如拉格朗日、牛顿、埃尔米特、线性、三次样条及最近邻插值),本方法通过规避全局特征依赖,显著保留了噪声点蕴含的局部信息特征。【结果】基于长春市1500名志愿者2024年8月19日—9月1日的原始GNSS轨迹数据,设计2组对比实验。第1组将新型识别算法与原始DBSCAN及其主流衍生算法(KANN-DBSCAN、BDT-ADBSCAN)进行对比。实验表明:新算法在轮廓系数(SC)、Calinski-Harabasz指数(CHI)、Da‐vies-Bouldin指数(DBI)3项指标均取得最优值,优化幅度分别为40.17%~381.80%、20.03%~235.18%、23.42%~79.53%。第2组实验对比新型修复算法与6类经典插值方法(拉格朗日、牛顿、埃尔米特、线性、三次样条、最近邻),结果显示:新算法在轨迹相似性度量指标(Dynamic Time Warping,DTW)上全面优于对比方法,整体优化幅度达43.18%~80.43%。【结论】本文提出的噪声识别与修复算法显著提升了原始GNSS轨迹的质量精度,可高效支撑大规模轨迹数据预处理任务,为时空轨迹挖掘研究提供高质量数据基础。
文摘碳捕集、利用和封存(Carbon Capture,Utilization and Storage)已经成为减少大气中二氧化碳的一种有效方法,但大量的二氧化碳注入地下可能会引起地表发生变形.为了探究二氧化碳注入后注采区的地表变化情况,本文基于45景Sentinel-1A升轨影像,运用SBAS-InSAR技术对国内某CO_(2)陆地埋存实验区域进行为期两年半形变监测工作,并构建了一种适用于小区域顾及GNSS的大气延迟改正模型.根据结果显示,本文提出的大气改正模型可以有效削减干涉图中的对流层延迟误差.根据InSAR结果显示,在注气过程中地表沿卫星视线方向靠近卫星,即地表发生隆起现象.通过提取注气井附近的形变时间序列,转换到垂直方向与GNSS数据对比,发现在注气之后,地表先隆起,几个月后开始逐渐回落.综合分析来看,结合GNSS与InSAR技术可以观测到该地区地表微小形变信息,GNSS监测站不仅可以用于校正InSAR干涉图中的大气延迟误差,还可以用于验证InSAR监测结果.
文摘现有GNSS水汽层析研究主要聚焦于如何提升卫星观测数据利用率,但在卫星信号数据优选方面研究较少,导致穿过同一组网格集的层析观测方程线性近似且方程系数矩阵列向量元素多数为零,水汽层析模型病态严重。针对该现状,本文提出一种GNSS卫星信号自适应优选的水汽层析方法,解决层析模型设计矩阵零元素较多和层析模型病态的难题。该方法基于网格覆盖率最大原则确定层析区域水平网格划分,并发展联合卫星高度角与方位角阈值的卫星信号自适应优选方法,克服水汽层析模型观测方程线性近似的难题。本文选取香港地区2013年5月2日—2013年5月7日共6 d 12个GNSS测站及1个无线电探空站数据为例进行试验。与现有方法相比,本文方法能在降低卫星信号利用率的同时保证网格覆盖率,克服相似卫星信号造成层析模型设计矩阵病态的现状。以无线电探空数据为真值,发现本文方法反演水汽密度廓线的平均RMS、MAE和Bias分别为1.03、0.80和0.13 g/m^(3),优于传统方法的1.25、0.97和0.10 g/m^(3),其RMS改善率为20.78%;此外,本文方法在模型解算效率方面也优于传统方法,其模型计算效率平均提升9.51%。
文摘In Global Navigation Satellite System(GNSS)meteo rology,the atmospheric weighted mean temperatu re(T_(m))is a critical intermediate parameter for converting zenith wet delay(ZWD)to precipitable water vapor(PWV),essential for accurate atmospheric water content estimation.However,global models often overlook regional climatic variability,leading to reduced accuracy in localized applications.This study introduces an improved T_(m)model developed using radiosonde observations across Iran and GNSS radio occultation(RO)profiles from CHAMP,GRACE,MetOp-A/B/C,COSMIC,TerraSAR-X,and TanDEM-X missions collected between 2007 and 2022.A novel integral formulation was proposed to estimate T_(m)more accurately by incorporating vertical water vapor distribution and temperature linearity.Based on this formulation,three regional T_(m)models were constructed using annual,semiannual,and diurnal periodicities,along with surface temperature(T_(s)),each varying in structure and complexity.Validation against independent radiosonde observations from 2022 showed that Models Two and Three outperformed the Bevis model,reducing RMSE by 30.7%.When evaluated against GNSS RO profiles,Model One—excluding T_(s)due to its inaccessibility in RO data—yielded the highest accuracy,with a 42.6%improvement in RMSE over the Bevis model.To evaluate the practical effectiveness of the proposed T_(m)model,PWV was derived from GNSS data at the tehn and tabz stations during the second half of 2022and compared with PWV values obtained from co-located radiosonde observations in Tehran and Tabriz.Using T_(m)from Model One improved PWV estimation compared to the Bevis model,reducing RMSE and MAE by up to 54%and 53.8%in Tabriz and 50.6%and 52.9%in Tehran,respectively.These results demonstrate that regionalized T_(m)modeling,particularly approaches that avoid dependence on T_(s),can significantly enhance GNSS-based PWV estimation in areas with limited surface data.
基金National Natural Science Foundation of China(42274012,42004001)the Science and Technology Innovation Project of Anhui Surveying and Mapping Bureau(2025-KJ-08)+1 种基金the Open Fund of Wuhan Gravitation and Solid Earth Tides,National Observation and Research Station(WHYWZ202107)the Fundamental Research Funds for the Central Universities(JZ2022HGTB0268)。
文摘To characterize the spatial patterns of vertical crustal movement of Chinese mainland,GNSS imaging technology was applied to map the tectonic deformation of the region.In this study,the vertical crustal velocities inferred from GNSS data for Chinese mainland over two decades were rigorously estimated.First,by analyzing the vertical displacement time series from continuous GNSS stations and environmental load data,we found that the annual and semi-annual vertical displacements are highly correlated.This indicates that the vertical seasonal variations on the ground surface are mainly caused by environmental loading.After removing the seasonal variations caused by environmental loads from the GNSS time series,we applied an improved PCA technique to filter out common mode errors.Next,we estimated the optimal noise models for the filtered time series and derived the vertical velocity field of Chinese mainland.Finally,we employed an empirical Spatial Structure Function(SSF)to image the tectonic deformation of Chinese mainland.This method effectively mitigates issues with abrupt circular arc-shaped boundaries in GNSS imaging caused by sparse station networks.The imaging results show that vertical crustal deformation in Chinese mainland generally ranges from-3 to 3 mm/yr,with significant spatial variability.The central and northern parts of Qinghai-Xizang Plateau are identified as primary subsidence zones,indicating that plate boundaries and tectonic compression continue to shape the crustal movement in these regions.The major uplift zones are located in northern and central China,likely linked to regional tectonic activity and plate compression.Subsidence deformation in parts of eastern China appears to be influenced by human activities.
