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51.
利用分布在70°E~210°E和20°S~40°N之间的GPS台站的数据,分析了2006年4月5日夜间(中等强度磁暴期间)观测到的电离层等离子体泡的特性.结果表明,本次事件中,等离子体泡大约发生在当地日落后1~1.5 h;空间范围为经度90°E~160°E,纬度12°S~33°N.这是第一次利用地基设备观测到如此大经度范围内的等离子体泡.等离子体泡在南半球出现较早,并且存活时间较长.在其产生的过程中,在约1100 km高度上,映射到磁赤道向上的运动速度约为300m/s,并且等离子体泡在高度上有倾斜.东向电场的存在,对激发等离子体泡起到了一定的作用.   相似文献   
52.
提出了一种基于无线测定卫星业务(RDSS)系统观测数据提取电离层TEC参数的方法,利用此方法计算分析了2006年5月地面中心地区电离层垂向TEC的日变化趋势.研究结果表明,利用RDSS系统观测数据提取的电离层垂向TEC,在北京时间每日凌晨0400时左右达到最小值,在午后1400时左右达到最大值,符合电离层TEC参数受太阳活动影响较大的物理规律.结果说明研究方法是可行且有效的,文章还对可能存在的误差进行了探讨.   相似文献   
53.
日照边缘区域电离层对耀斑的响应特点研究   总被引:1,自引:1,他引:0  
利用MSIS模型和背景太阳辐射谱模型,在一定大耀斑辐射谱假设的前提下,计算了耀斑期间日照边缘区域的电子产生率,分析了这一区域电离层电子密度的变化特点.结果表明,大耀斑期间在日照边缘区域,甚至大于太阳天顶角90°的区域都有明显的电子产生率的增加.从不同太阳天顶角处的电子产生率剖面的形态来看,随着天顶角的增加最大电离率减少,但高度增加.计算还显示了在太阳天顶角小于90°的区域内电子产生率的垂直分布有明显的双峰结构,这种结构对应着电离层的E区和F区,但在天顶角大于90°区域,F区的电子产生率要大得多.考虑到离子和电子的复合过程,这一区域的总电子含量的增加主要产生在高F区.   相似文献   
54.
将太阳活动峰年期间中国4个电离层站垂直探测得到的月平均电子浓度剖面与国际参考电离层IKI-90进行了系统的比较。结果表明国际参考电离层所计算的峰下电子含量(或峰下半厚)总体来说偏大。一天中白天符合较好,晚上较差,对中纬台站较好,对低纬台站较差。   相似文献   
55.
Ionosphere response to severe geomagnetic storms that occurred in 2001–2003 was analyzed using data of global ionosphere maps (GIM), altimeter data from the Jason-1 and TOPEX satellites, and data of GPS receivers on-board CHAMP and SAC-C satellites. This allowed us to study in detail ionosphere redistribution due to geomagnetic storms, dayside ionospheric uplift and overall dayside TEC increase. It is shown that after the interplanetary magnetic field turns southward and intensifies, the crests of the equatorial ionization anomaly (EIA) travel poleward and the TEC value within the EIA area increases significantly (up to ∼50%). GPS data from the SAC-C satellite show that during the main phase of geomagnetic storms TEC values above the altitude of 715 km are 2–3 times higher than during undisturbed conditions. These effects of dayside ionospheric uplift occur owing to the “super-fountain effect” and last few hours while the enhanced interplanetary electric field impinged on the magnetopause.  相似文献   
56.
Single-frequency precise point positioning (SF-PPP) has attracted increasing attention due to its high precision and cost effectiveness. With various strategies to handle the dominant error, i.e., ionosphere delay, the ionosphere-float (IF), ionosphere-free-half (IFH), ionosphere-corrected (IC), and ionosphere-weighted (IW) SF-PPP models are certain to possess different characteristics and performance levels. This study is dedicated to assessing and comparing the four models from model characteristics, positioning performance, and atmosphere delay retrieval. The model comparison shows that IC and IW models are full-rank while IF and IFH models have a rank deficiency of size one that will result in biased estimations, which means the better solvability of IC and IW models. The experiments are carried out based on the 7-day Global Positioning System (GPS) observations collected at 57 global Multi-GNSS Experiment (MGEX) stations and Global Ionosphere Map (GIM) products. The results indicate that the IW model can accelerate SF-PPP convergence and achieve higher positioning accuracy compared to the other three SF-PPP models, especially in kinematic mode. With convergence criteria of 0.25 m in horizontal and 0.5 m in vertical, the east/north/up convergence times of IW model are 0.5/15.0/25.0 min and 0.5/16.0/36.5 min for static and kinematic modes, respectively. The IW model is able to achieve an instantaneous positioning accuracy of 0.28/0.35/0.75 m. In addition, a real kinematic test also demonstrates the best positioning solutions of IW model. Regarding troposphere delay retrieval, the IF, IFH, and IW models obtain a comparable daily accuracy of 3.0 cm on average, while the IC model achieves the worst accuracy of 8.0 cm. For precise ionosphere delay estimation, IW model only needs an average initialization time of 34.3 min, but a longer initialization time of 51.6 min is required for IF model. The daily precision of ionosphere delay estimation for IW model can reach up to 10.8 cm. At the present accuracy of GIM products, it is suggested that the IW model should be adopted for SF-PPP first due to its superior performance in positioning and atmosphere delay retrieval.  相似文献   
57.
本文利用西藏、广州地区1985—1988年夏季的7、8月份的实测资料,对电离层特征参数,f_oE,f_oE_s,f_bE_s,进行了统计分析,得到它们的变化规律与特点。 从图1中看出,西藏高原地区的f_oE值,其变化规律,受太阳黑子的影响较大且为正  相似文献   
58.
IRI-90及其与中国电离层资料f_0F_2的比较   总被引:1,自引:0,他引:1  
本文介绍了国际参考电离层IRI-90版中新增的内容,比较了它与IRI-86的主要差别。与我国电离层临频数据的统计分析表明,新版本对我国地区的适用程度有了改进。  相似文献   
59.
Anomaly detection is extremely important for earthquake parameters estimation. In this paper, an application of Artificial Neural Networks (ANNs) in the earthquake precursor’s domain has been developed. This study is concerned with investigating the Total Electron Content (TEC) time series by using a Multi-Layer Perceptron (MLP) neural network to detect seismo-ionospheric anomalous variations induced by the powerful Tohoku earthquake of March 11, 2011.  相似文献   
60.
Ionosphere delay correction is the main error correction to the computation of single frequency user position using satellite navigation. However ionosphere delay consists of not only delay but also frequency dependent differential hardware biases from satellite and receiver ends. For ionosphere point of view, Indian Regional Navigation Satellite System (IRNSS) service area comes in equatorial anomaly region. It is a unique satellite navigation system which operates at L5 and S frequencies and consists of Geostationary Earth Orbit (GEO) and Geo Synchronous Orbit (GSO) satellite constellation. With IRNSS measurements availability, there is a good opportunity to estimate and analyse differential hardware biases with GEO/GSO combination and with equatorial ionosphere variation. In this paper, Kalman filter based estimation with triangular interpolation technique is used to estimate differential hardware biases for all IRNSS satellites and reference receivers at L5 frequency. The standard deviation of the 15?days of daily estimation of satellite differential hardware biases is in the range of 0.32 to 1.17 TECU for all IRNSS satellites. Similarly, the standard deviation of the 15?days of daily estimation varies up to 2.85 and 6.0 TECU for receiver differential hardware biases during calm and stormy period respectively. The ionosphere delay computed using estimated differential hardware biases is compared with Global Ionosphere Map (GIM) data. A rigorous analysis is carried out to study the error in the estimation in terms of input data noise level, satellite constellation and effect of latitude. Our result reveals that over IRNSS service area, there is an exponential increase in the error in the estimation of receiver differential hardware biases with respect to latitude.  相似文献   
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