利用张衡一号卫星搭载的电场探测仪(Electric Field Detector,EFD)获得的VLF频段2019年电场功率谱数据,研究赤道附近区域近东西向电场的背景分布、季节变化以及与电离层背景的关系。结果表明:白天电场背景在赤道及其附近随季节呈不同波...利用张衡一号卫星搭载的电场探测仪(Electric Field Detector,EFD)获得的VLF频段2019年电场功率谱数据,研究赤道附近区域近东西向电场的背景分布、季节变化以及与电离层背景的关系。结果表明:白天电场背景在赤道及其附近随季节呈不同波形结构,以3波、4波为主;夜间电场背景规律性稍差,仍呈随季节变化的经向波形结构分布特征;白天电场背景与电离层背景的季节变化呈高度正相关性,春秋季为峰值;夜间电场背景的季节变化特征是夏冬季峰值,与夜间电离层背景整体上呈负相关性。VLF电场功率谱观测数据与电离层观测数据在较大和较小空间尺度上的统计特征上都具有一致性。EFD载荷为电离层相关科学问题的研究及应用提供了一个可以使用的电场观测数据集。展开更多
This report briefly introduces the current status of the CSES(China Seismo-Electromagnetic Satellite)mission which includes the first satellite CSES 01 in-orbit(launched in February 2018),and the second satellite CSES...This report briefly introduces the current status of the CSES(China Seismo-Electromagnetic Satellite)mission which includes the first satellite CSES 01 in-orbit(launched in February 2018),and the second satellite CSES 02(will be launched in 2023)under development.The CSES 01 has been steadily operating in orbit for over four years,providing abundant global geophysical field data,including the background geomagnetic field,the electromagnetic field and wave,the plasma(in-situ and profile data),and the energetic particles in the ionosphere.The CSES 01 platform and the scientific instruments generally perform well.The data validation and calibration are vital for CSES 01,for it aims to monitor earthquakes by extracting the very weak seismic precursors from a relatively disturbing space electromagnetic environment.For this purpose,we are paying specific efforts to validate data quality comprehensively.From the CSES 01 observations,we have obtained many scientific results on the ionosphere electromagnetic environment,the seismo-ionospheric disturbance phenomena,the space weather process,and the Lithosphere-Atmosphere-Ionosphere coupling mechanism.展开更多
随着前兆观测数据的激增,如何对大量的观测数据中存在的异常数据进行快速检测,是当前面临的比较迫切的问题。本文利用一种基于快速聚类的异常数据检测与评价方法,解决大量观测数据中异常数据的自动检测问题。首先,利用垂直距离分段方法...随着前兆观测数据的激增,如何对大量的观测数据中存在的异常数据进行快速检测,是当前面临的比较迫切的问题。本文利用一种基于快速聚类的异常数据检测与评价方法,解决大量观测数据中异常数据的自动检测问题。首先,利用垂直距离分段方法对水管倾斜仪观测数据进行分割,构造分段数据对象;其次,利用均值、方差、峰度与偏度等特征对分段数据对象进行特征表达;然后,基于反正切函数改进影响蚁群算法聚类效率的路径持久性参数,利用快速搜索算法(Clustering by Fast Search,CFS)和改进的蚁群最优化算法(Ant Colony Optimization,ACO)分别对分段数据对象进行聚类,实现对观测数据中异常数据检测的目的;最后,利用F-measure、R-value指标与Chi-square检验评估CFS和ACO聚类方法在异常数据检测上的有效性,以上检测方法都通过了三种指标的有效性检验。实验结果表明ACO和CFS聚类算法可以有效、快速地检测到观测数据中的局部异常数据,诸如高频变化、尖峰等异常数据,为形变类观测数据中异常数据的识别提供一种有效的检测与评价方法。展开更多
The China Seismo-Electromagnetic Satellite(CSES)deploys three payloads to detect the electromagnetic environment in the ionosphere.The tri-axial fluxgate magnetometers(FGM),as part of the high precision magnetometer(H...The China Seismo-Electromagnetic Satellite(CSES)deploys three payloads to detect the electromagnetic environment in the ionosphere.The tri-axial fluxgate magnetometers(FGM),as part of the high precision magnetometer(HPM),measures the Earth magnetic vector field in a frequency range from direct current(DC)to 15 Hz.The tri-axial search coil magnetometer(SCM)detects the alternating current(AC)related magnetic field in a frequency range from several Hz to 20 k Hz,and the electric field detector(EFD)measures the spatial electric field in a broad frequency band from DC to 3.5 MHz.This work mainly crosscalibrates the consistency of these three payloads in their overlapped detection frequency range and firstly evaluates CSES’s timing system and the sampling time differences between EFD and SCM.A sampling time synchronization method for EFD and SCM waveform data is put forward.The consistency between FGM and SCM in the ultra-low-frequency(ULF)range is validated by using the magnetic torque(MT)signal as a reference.A natural quasiperiodic electromagnetic wave event verifies SCM and EFD’s consistency in extremely low-frequency and very low-frequency(ELF/VLF)bands.This cross-calibration work is helpful to upgrade the data quality of CSES and brings valuable insights to similar electromagnetic detection solutions by low earth orbit satellites.展开更多
The China-Seismo-Electromagnetic Satellite(CSES),which was launched in February 2018,carries the search coil magnetometer(SCM)and the electric field detector(EFD)to realize the high-resolution electromagnetic field an...The China-Seismo-Electromagnetic Satellite(CSES),which was launched in February 2018,carries the search coil magnetometer(SCM)and the electric field detector(EFD)to realize the high-resolution electromagnetic field and wave detection in the upper ionosphere.Due to the complexity and variability of the ionospheric environment,the stability of such a high sampling rate and high-precision electromagnetic field detection systems is always an essential link in data processing and the scientific application of CSES.This work evaluates the stability of the very-low-frequency(VLF)band detection by validating the systemic sampling-time differences between SCM and EFD in the VLF burst-mode observations.The optimal waveform data preprocessing method is put forward according to the noise levels of the VLF burst-mode observation and the inherent design characteristics of EFD.The VLF waveform data of EFD is rebuilt by filling the data gaps among the sampling sub-periods,making it with a similar sample length to SCM.Then by precisely intercepting the maximum and minimum values of the burst-mode waveforms,the variation of the sampling-time difference between EFD and SCM is statistically evaluated.Results show that during the three years'operation,the sampling-time difference between EFD and SCM predominately keeps below 0.5 s,indicating good stability of EFD and SCM on orbit.Then we developed an automatic synchronization tool based on the similarity function and STA/LTA(short time average over long time average)characteristic function.This tool can effectively realize the precise synchronization between SCM and EFD in the VLF burst-mode observation.This work is helpful to upgrade the data quality of CSES and provides technical support for electromagnetic wave propagation studies.展开更多
文摘利用张衡一号卫星搭载的电场探测仪(Electric Field Detector,EFD)获得的VLF频段2019年电场功率谱数据,研究赤道附近区域近东西向电场的背景分布、季节变化以及与电离层背景的关系。结果表明:白天电场背景在赤道及其附近随季节呈不同波形结构,以3波、4波为主;夜间电场背景规律性稍差,仍呈随季节变化的经向波形结构分布特征;白天电场背景与电离层背景的季节变化呈高度正相关性,春秋季为峰值;夜间电场背景的季节变化特征是夏冬季峰值,与夜间电离层背景整体上呈负相关性。VLF电场功率谱观测数据与电离层观测数据在较大和较小空间尺度上的统计特征上都具有一致性。EFD载荷为电离层相关科学问题的研究及应用提供了一个可以使用的电场观测数据集。
基金Supported by the National Natural Science Foundation of China(4187417,42104159)National Key R&D Program of China(2018YFC1503501)+1 种基金the APSCO Earthquake Research Project PhaseⅡthe Dragon 5 cooperation 2020-2024(ID.59236)。
文摘This report briefly introduces the current status of the CSES(China Seismo-Electromagnetic Satellite)mission which includes the first satellite CSES 01 in-orbit(launched in February 2018),and the second satellite CSES 02(will be launched in 2023)under development.The CSES 01 has been steadily operating in orbit for over four years,providing abundant global geophysical field data,including the background geomagnetic field,the electromagnetic field and wave,the plasma(in-situ and profile data),and the energetic particles in the ionosphere.The CSES 01 platform and the scientific instruments generally perform well.The data validation and calibration are vital for CSES 01,for it aims to monitor earthquakes by extracting the very weak seismic precursors from a relatively disturbing space electromagnetic environment.For this purpose,we are paying specific efforts to validate data quality comprehensively.From the CSES 01 observations,we have obtained many scientific results on the ionosphere electromagnetic environment,the seismo-ionospheric disturbance phenomena,the space weather process,and the Lithosphere-Atmosphere-Ionosphere coupling mechanism.
文摘随着前兆观测数据的激增,如何对大量的观测数据中存在的异常数据进行快速检测,是当前面临的比较迫切的问题。本文利用一种基于快速聚类的异常数据检测与评价方法,解决大量观测数据中异常数据的自动检测问题。首先,利用垂直距离分段方法对水管倾斜仪观测数据进行分割,构造分段数据对象;其次,利用均值、方差、峰度与偏度等特征对分段数据对象进行特征表达;然后,基于反正切函数改进影响蚁群算法聚类效率的路径持久性参数,利用快速搜索算法(Clustering by Fast Search,CFS)和改进的蚁群最优化算法(Ant Colony Optimization,ACO)分别对分段数据对象进行聚类,实现对观测数据中异常数据检测的目的;最后,利用F-measure、R-value指标与Chi-square检验评估CFS和ACO聚类方法在异常数据检测上的有效性,以上检测方法都通过了三种指标的有效性检验。实验结果表明ACO和CFS聚类算法可以有效、快速地检测到观测数据中的局部异常数据,诸如高频变化、尖峰等异常数据,为形变类观测数据中异常数据的识别提供一种有效的检测与评价方法。
基金supported by the National Natural Science Foundation of China(Grant Nos.41874174 and 41574139)the National Key R&D Program of China(Grant No.2018YFC1503501)+1 种基金the APSCO Earthquake Research Project PhaseⅡand ISSI-BJ projectSouthern Yunnan Observatory for Cross-block Dynamic Process,Yuxi Yunnan,China。
文摘The China Seismo-Electromagnetic Satellite(CSES)deploys three payloads to detect the electromagnetic environment in the ionosphere.The tri-axial fluxgate magnetometers(FGM),as part of the high precision magnetometer(HPM),measures the Earth magnetic vector field in a frequency range from direct current(DC)to 15 Hz.The tri-axial search coil magnetometer(SCM)detects the alternating current(AC)related magnetic field in a frequency range from several Hz to 20 k Hz,and the electric field detector(EFD)measures the spatial electric field in a broad frequency band from DC to 3.5 MHz.This work mainly crosscalibrates the consistency of these three payloads in their overlapped detection frequency range and firstly evaluates CSES’s timing system and the sampling time differences between EFD and SCM.A sampling time synchronization method for EFD and SCM waveform data is put forward.The consistency between FGM and SCM in the ultra-low-frequency(ULF)range is validated by using the magnetic torque(MT)signal as a reference.A natural quasiperiodic electromagnetic wave event verifies SCM and EFD’s consistency in extremely low-frequency and very low-frequency(ELF/VLF)bands.This cross-calibration work is helpful to upgrade the data quality of CSES and brings valuable insights to similar electromagnetic detection solutions by low earth orbit satellites.
基金supported by the National Natural Science Foundation of China(Grant Nos.41874174 and 42104159)National Key R&D Program of China(Grant No.2018YFC1503502)+3 种基金Scientific and Technological Innovation Team of Henan Earthquake Agency-the Survey and Comparison Of Electromagnetic Data on Satellite and Earth Research Groupthe APSCO Earthquake Research Project PhaseⅡInternational Space Science Institute——Beijing Project,Dragon 59236Southern Yunnan Observatory for Cross-block Dynamic Process,Yuxi Yunnan,652799,China。
文摘The China-Seismo-Electromagnetic Satellite(CSES),which was launched in February 2018,carries the search coil magnetometer(SCM)and the electric field detector(EFD)to realize the high-resolution electromagnetic field and wave detection in the upper ionosphere.Due to the complexity and variability of the ionospheric environment,the stability of such a high sampling rate and high-precision electromagnetic field detection systems is always an essential link in data processing and the scientific application of CSES.This work evaluates the stability of the very-low-frequency(VLF)band detection by validating the systemic sampling-time differences between SCM and EFD in the VLF burst-mode observations.The optimal waveform data preprocessing method is put forward according to the noise levels of the VLF burst-mode observation and the inherent design characteristics of EFD.The VLF waveform data of EFD is rebuilt by filling the data gaps among the sampling sub-periods,making it with a similar sample length to SCM.Then by precisely intercepting the maximum and minimum values of the burst-mode waveforms,the variation of the sampling-time difference between EFD and SCM is statistically evaluated.Results show that during the three years'operation,the sampling-time difference between EFD and SCM predominately keeps below 0.5 s,indicating good stability of EFD and SCM on orbit.Then we developed an automatic synchronization tool based on the similarity function and STA/LTA(short time average over long time average)characteristic function.This tool can effectively realize the precise synchronization between SCM and EFD in the VLF burst-mode observation.This work is helpful to upgrade the data quality of CSES and provides technical support for electromagnetic wave propagation studies.
