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在总结用GPS研究电离层电子总量TEC的数据处理方法基础上,分析了利用伪距观测量和载波相位观测量计算电离层TEC的特点及误差来源.在处理过程中考虑了卫星的硬件延迟偏差,分析了应用IRI模型进行接收机硬件延迟偏差修正的可能性,发现利用少量GPS数据和IRI模型修正接收机硬件延迟偏差有一定的困难.最后,利用一些GPS观测数据有针对性地研究了电离层对若干次扰动事件的响应.包括一次大的太阳耀斑期间的电离层TEC变化、一次较典型的电离层行扰以及日食期间的电离层TEC的相对变化等电离层物理问题.结果表明,利用该方法计算TEC的精度可满足电离层扰动现象的研究. 相似文献
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利用日本境内的高空间分辨率的双频GPS台站资料,观测研究了发生于2000年7月中旬太阳强活动期间的一次大尺度电离层行扰. 结果表明:在7月15日11:00UT-1:00UT期间观测区域的电离层中出现了大尺度电离层行扰. 在15:00UT之前,扰动周期为2h左右,在15:00UT以后,扰动周期为1h左右;总电子含量扰动幅度的变化范围约为1-2TECU;通过对15:00-17:00UT之间总电子含量扰动曲线同相位点的分析,发现这期间的电离层行扰的扰动速度约为600-700m/s,扰动波长在2200km左右,扰动传播的方向几乎沿着经线从高纬向低纬传播. 该行扰与此次强太阳活动有直接的关系,因其发生在7月15日的磁暴急始之前数小时,因此与磁暴本身没有因果关系,应与磁暴之前先期到达地球空间的高能质子流有关. 相似文献
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利用日本境内的高空间分辨率的双频GPS台站资料,观测研究了发生于2000年7月中旬太阳强活动期间的一次大尺度电离层行扰. 结果表明:在7月15日11:00UT-1:00UT期间观测区域的电离层中出现了大尺度电离层行扰. 在15:00UT之前,扰动周期为2h左右,在15:00UT以后,扰动周期为1h左右;总电子含量扰动幅度的变化范围约为1-2TECU;通过对15:00-17:00UT之间总电子含量扰动曲线同相位点的分析,发现这期间的电离层行扰的扰动速度约为600-700m/s,扰动波长在2200km左右,扰动传播的方向几乎沿着经线从高纬向低纬传播. 该行扰与此次强太阳活动有直接的关系,因其发生在7月15日的磁暴急始之前数小时,因此与磁暴本身没有因果关系,应与磁暴之前先期到达地球空间的高能质子流有关. 相似文献
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电离层总电子含量(TEC)是空间天气研究和监测预报的重要参量.本文引入了电离层TEC扰动指数DI, 对青岛等6个台站的DI数据进行分析,选取DI>0.35(DI≤-0.30)作为正(负)相电离层TEC扰动的强度标准,并以连续6 h及以上的DI满足该值来判定电离层TEC暴扰动事件.对电离层TEC暴扰动事件的统计分析表明,在地方时日落后至子夜前为发生高峰时段,正(负)相暴扰动事件平均持续时间约为10.9 h(10.5 h),正相暴发生率以冬季为多,夏季为少,而负相暴则以夏季略高.发现位于赤道异常驼峰区的广州站和位于高中纬度的海拉尔站比典型中纬地区的北京站电离层TEC暴扰动更易发生,且低纬地区以正相暴扰动为主.分析表明,约有70%的电离层TEC暴扰动伴随着有地磁扰动,但是电离层TEC暴扰动并不完全由地磁扰动所引起,强烈气象活动等局地环境因素也可能对电离层TEC暴扰动有着重要影响. 相似文献
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电离层总电子含量(TEC)是空间天气研究和监测预报的重要参量.本文引入了电离层TEC扰动指数DI, 对青岛等6个台站的DI数据进行分析,选取DI>0.35(DI≤-0.30)作为正(负)相电离层TEC扰动的强度标准,并以连续6 h及以上的DI满足该值来判定电离层TEC暴扰动事件.对电离层TEC暴扰动事件的统计分析表明,在地方时日落后至子夜前为发生高峰时段,正(负)相暴扰动事件平均持续时间约为10.9 h(10.5 h),正相暴发生率以冬季为多,夏季为少,而负相暴则以夏季略高.发现位于赤道异常驼峰区的广州站和位于高中纬度的海拉尔站比典型中纬地区的北京站电离层TEC暴扰动更易发生,且低纬地区以正相暴扰动为主.分析表明,约有70%的电离层TEC暴扰动伴随着有地磁扰动,但是电离层TEC暴扰动并不完全由地磁扰动所引起,强烈气象活动等局地环境因素也可能对电离层TEC暴扰动有着重要影响. 相似文献
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本文利用设在武汉(114.36°E,30.53°N,磁纬19.4°)的GPS电离层TEC和电波闪烁监测仪的测量数据,分析了2004年11月强磁暴期间TEC的响应以及电波闪烁和TEC起伏的特征.结果表明,在这次强磁暴期间,武汉及其邻近地区电离层TEC的响应以正暴相为主,正暴相分别出现在两次主相期间,最大正偏离达到50 TECU.这次磁暴另一个重要影响是主相期间L波段振幅闪烁的活动性及其强度显著增强.S4指数最大接近1.0.伴随增强的闪烁活动,多次观测到深度耗尽的等离子体泡与TEC起伏,TEC变化率的标准差ROTI指数也显著增强.分析揭示, ROTI指数与S4指数呈正相关,相关系数达到0.97.线性回归计算得到,ROTI和S4的比率为9.64. 相似文献
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R. Orús M. Hernndez-Pajares J. M. Juan J. Sanz M. García-Fernndez 《Journal of Atmospheric and Solar》2002,64(18)
The existence of a worldwide international GPS service (IGS) permanent network of dual-frequency receivers makes the computation of global ionospheric maps (GIMs) of total electron content (TEC) feasible. The GIMs computed by the IGS Associate Analysis Centers on a daily basis and by other kinds of forecast GIMs, which can be computed from, for instance, the international reference ionosphere (IRI) model, and the GPS broadcast models in the navigation message, can be applied to a broad diversity of fields, for instance as, navigation and time transfer.In this context, the performance of different kinds of models are presented in order to determine the accuracy of the different GIM. This is carried out by comparison with the TOPEX data that provides an independent and precise (at the level of few TECU) vertical TEC determination over the oceans and seas. Thus, the obtained accuracies, in terms of global relative error, ranging from 54% corresponding to the GPS broadcast model, to about 41% corresponding to IRI climatological model, and to less than 30% corresponding to GPS data driven models. 相似文献
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SONG Dong-mei XIANG Liang SHAN Xin-jian YIN Jing-yuan WANG Bin CUI Jian-yong 《地震地质》2019,41(6):1511-1528
There are many factors related to the variations of TEC, and the changes of TEC caused by earthquake only occupy a small portion. Therefore, it is vital how to exclude the ionospheric interference of non-seismic factors accurately in the process of seismic ionospheric anomaly extraction. This study constructed a TEC non-seismic dynamic background field considering the influence of solar and geomagnetic activities. Firstly, the TEC components of half-year cycle and annual cycle are extracted by wavelet decomposition. Then, it establishes a regression model between TEC in which periodic factors are removed and solar activity index, geomagnetic activity index with SVR method(support vector regression)in non-seismic period. Finally, based on the constructed model, the solar activity index and geomagnetic activity index is used to reconstruct aperiodic components of TEC in earthquake's period. From the reconstructed aperiodic components of TEC plus the half-year periodic components and annual periodic components of TEC in the same period, the non-seismic dynamic background field is obtained. Comparing the residuals relative to original TEC values in non-seismic dynamic background field and traditional sliding window background, there are apparent monthly periodic change and semi-annual periodic change in the residuals of sliding window background, which can have obvious impacts on the subsequent seismic ionospheric anomaly detection. In order to test the validity of seismic TEC anomaly detection based on the background field construction method, this paper investigated the long time series TEC anomalies near Wenchuan city(30°N, 100°E)from March 1 to September 26 in 2008. It is found that under the condition of non-seismic disturbance such as solar activity and geomagnetic activity, TEC abnormal disturbance is rarely detected by non-seismic dynamic background field method, when compared with the traditional sliding time-window method. And before the earthquake, more TEC anomalies were detected based on the proposed method, also, they were more intense than those extracted by sliding window method. Therefore, the TEC background field construction method based on SVR(support vector regression)has superiorities in both system errors elimination, which are caused by solar, geomagnetism, the non-seismic ionospheric disturbance events and periodic fluctuations of TEC, and in reducing the false alarm rate of seismic TEC anomaly. Moreover, it can also improve the seismic TEC anomaly detection ability. In addition, this paper analyzed the time-spatial distribution of TEC anomaly before three earthquakes on May 12, August 21 and August 30, 2008. They were mainly negative abnormal perturbations and often distributed on the equatorial side of epicenter. 相似文献
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利用上海地区GPS综合应用网提供的高时空分辨率的双频GPS观测资料,研究了该区域内一电离层不均匀体的产生、消亡过程.首先,采用Kalman滤波的方法改善双频伪距之差的观测精度,并利用参数估计的方法计算该时段内相应的硬件延迟.再根据电离层单层模型,利用GPS双频观测量、测站位置和GPS精密星历,求出GPS信号穿刺点的坐标和垂直方向电离层的电子含量;然后内插并获取其等值线图.等值线图随时间的变化表明,受等离子体湍流的影响,2003年9月8日北京时间9时40分左右在38°N、118°E左右产生了一电离层不均匀体,其尺度大约在50km左右,生存时间大约为5min.受地球重力场和高空风场的影响,该不均匀体向东北方向扩散.然后,利用大气扩散模型,按扩散方程计算分析了该不均匀体可能发生的电离层层区.理论计算表明,该不均匀体发生在电离层扩展F区,高度在350km左右. 相似文献