Analysis of the ionosphere/plasmasphere electron content variability during strong geomagnetic storm

The ionosphere/plasmasphere electron content (PEC) variations during strong geomagnetic storms in November 2004 were estimated by combining of mid-latitude Kharkov incoherent scatter radar observations and GPS TEC data derived from global TEC maps. The comparison between two independent measurements was performed by analysis of the height-temporal distribution for specific location corresponding to the mid-latitudes of Europe. The percentage contribution of PEC to GPS TEC indicated the clear dependence from the time with maximal values (more than 70%) during night-time. During day-time the lesser values (30–45%) were observed for quiet geomagnetic conditions and rather high values of the PEC contribution to GPS TEC (up to 90%) were observed during strong negative storm. These changes can be explained by the competing effects of electric fields and winds, which tend to raise the layer to the region with lower loss rate and movement of the ionospheric plasma to the plasmasphere.     

多GNSS全球电离层建模特性及其精度检验

分别以GPS单系统和融合BDS,GPS,GLONASS三系统两种方案,采用载波相位平滑伪距观测值和球谐函数,构建了全球电离层延迟模型并进行了对比和分析.本文以GPS单系统和融合三系统两种方法反演了2014年1月每日电离层变化过程,解算得出了频间偏差的月综合产品,并对结果进行了对比和分析.事实上,三系统融合不仅增加了可观测的卫星数,而且改善了穿刺点的几何分布.分析结果表明,三系统融合反演全球电离层在精度上优于GPS单系统,均有5~10 TECU的提高.计算得到的频间偏差结果显示,GPS优于GIONASS,BDS稳定性则较次之.     

电离层周日变化对解算GPS硬件延迟稳定性的影响

针对电离层周日变化特征分析了其可能对SCORE方法估算的硬件延迟稳定性的影响. 利用BJFS以及XIAM台站的GPS观测数据, 解算了位于太阳活动高年(2001年)和太阳活动低年(2009年)的卫星硬件延迟并分析了估算的硬件延迟的稳定性. 研究发现, 电离层周日变化对估算的硬件延迟稳定性具有一定影响, 但是利用不同台站所得到的卫星硬件延迟稳定性在昼夜不同时间上的解算结果存在一定差异. 电离层周日变化对利用 BJFS台站数据解算的硬件延迟稳定性日夜差异较为明显, 在太阳活动高年利用XIAM 台站数据解算的硬件延迟日夜稳定性差异不很明显, 由于XIAM台站处于电离层赤道异常峰附近, 夜间电离层变化很大, 因此对比中纬度地区, 电离层周日变化对赤道异常峰附近地区硬件延迟稳定性解算结果的影响相对较小, 但在太阳活动低年, 其影响仍较为显著.      

高压输电网设计中的二阶非线性方程的次谐波分枝

本文用Melnikov方法研究高压输电网设计中提出的非线性二阶受迫振动方程的次谐波分枝,分析了系统可能出现次谐解的条件和参数区域,以此为工程应用提供参考。     

Comparative analysis of four different single-frequency PPP models on positioning performance and atmosphere delay retrieval

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.     

西藏高原 广州地区f0E,f0Es,fbEs的某些变化特征

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     

IRI-90及其与中国电离层资料f_0F_2的比较

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。     

Anomalous enhancement of electric field derived from ionosonde data before the great Wenchuan earthquake

The seismo-ionospheric coupling is a hot topic of modern scientific research. One of the most reasonable mechanisms is the hypothesis of quasistatic electric field. With a preliminary analytical method, electric field in F2-region before Wenchuan earthquake was derived from the five lower latitude ground-based ionosondes: Lhasa (29.63°N, 91.17°E), Chongqing (29.50°N, 106.40°E), Kunming (25.00°N, 102.70°E), Guangzhou (23.15°N, 113.35°E) and Haikou (23.15°N, 110.35°E). The results show that there was an anomalous enhancement of electric field in F2-region close to the epicenter with maximal amplitude ∼2 mV/m (about 10 times of the background) at 15:00 LT on 9 May, which is in line with the amplitudes of anomalous electric field related to some previous earthquakes observed by satellites.     

A MLP neural network as an investigator of TEC time series to detect seismo-ionospheric anomalies

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.     

Kalman filter based estimation of differential hardware biases with triangular interpolation technique for IRNSS

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.