本文選題：電離層模型 + GPS��； 參考：《西南交通大學》2014年碩士論文

【摘要】：電離層是日地空間環(huán)境的一個重要組成部分,它的劇烈變動會對人類的生產(chǎn)生活產(chǎn)生巨大的影響。對電離層本身的動態(tài)變化以及災害前后電離層的異常變動等現(xiàn)象的探測研究已然成為了當前研究的熱點。據(jù)相關研究發(fā)現(xiàn),劇烈天氣(臺風、寒潮等)、日食、地震、火山爆發(fā)等都會對電離層造成不同程度的影響,從而引發(fā)電離層異常。利用地基GPS臺網(wǎng)觀測數(shù)據(jù),通過計算電離層電子密度以及總電子含量(TEC),可以發(fā)現(xiàn)電離層在不同時空尺度的分布與變化特性。同時,通過探測TEC以及電子密度時間序列可以發(fā)現(xiàn)電離層異常現(xiàn)象。但是,電離層自身存在動態(tài)變化。太陽活動等引起地球空間環(huán)境的擾動,使得電離層發(fā)生不同程度的變化,呈現(xiàn)出周日、逐日變化,季節(jié)變化等。這使得探測難度加大。如何更可靠地探測捕捉電離層異常現(xiàn)象,就成為亟需解決的關鍵性問題。針對于這些問題,本文就電離層的周期性變化規(guī)律、電離層TEC模型以及三維層析模型的構建、TEC時間序列的異常探測等方面進行了討論。本文的研究內容主要包括： 1)概括了電離層異常國內外研究現(xiàn)狀,介紹了電離層分層結構及其特性。詳細討論了多種參考框架、電離層模型具體構造和特點； 2)利用CODE提供的太陽活動高峰年2013年和低峰年2006年全球電離層TEC格網(wǎng)模型GIM分析武漢站上空天頂方向總電子含量的周日、逐日、季節(jié)變化情況； 3)詳細闡述了利用GPS雙頻觀測值計算電離層TEC的算法原理,對GPS數(shù)據(jù)預處理、硬件延遲解算、建立格網(wǎng)模型進行詳細的描述； 4)介紹了滑動四分位距法、滑動時窗法、卡爾曼濾波法和ARIMA時間序列法。利用上述方法對一段正常的TEC數(shù)據(jù)直接進行預測,對比分析不同方法下的預測背景值的精度：對同一段TEC數(shù)據(jù),去除長周期和趨勢變化后,再通過上述方法進行預測,比較得到的預測背景值精度。對比處理和未處理的TEC數(shù)據(jù)采用四種方法進行預測得到的背景值精度,實驗結果表明：去除長周期和趨勢性變化的TEC數(shù)據(jù)的預測精度要高于未處理的TEC數(shù)據(jù)；處理后的TEC數(shù)據(jù)采用滑動四分位距法和卡爾曼濾波法的預測精度要高于其余兩種算法的預測精度； 5)利用IGS跟蹤站、四川觀測網(wǎng)絡以及陸態(tài)網(wǎng)的數(shù)據(jù)對汶川地震、東日本大地震和蘆山地震震前后的電離層構建局域的精細格網(wǎng)模型以及三維層析模型,利用兩種去周期和趨勢性的滑動四分位距法和卡爾曼濾波法分析地震前后震中附近地區(qū)電離層VTEC的異常變化情況,排除太陽活動和地磁擾動等影響因素后,發(fā)現(xiàn)三次大地震的震中附近震前幾天均有TEC異�，F(xiàn)象發(fā)生,并且異常區(qū)呈現(xiàn)出共軛的結構。
[Abstract]:The ionosphere is an important part of the solar-terrestrial space environment. The research on the dynamic changes of the ionosphere itself and the anomalous changes of the ionosphere before and after disasters has become a hot topic. According to relevant studies, severe weather (typhoons, cold waves, solar eclipses, earthquakes, volcanic eruptions, etc.) will cause varying degrees of influence on the ionosphere, thus causing ionospheric anomalies. The distribution and variation characteristics of ionosphere at different space-time scales can be found by calculating the ionospheric electron density and total electron content by using the ground-based GPS network data. At the same time, ionospheric anomalies can be found by detecting TEC and electron density time series. However, there are dynamic changes in the ionosphere itself. The solar activity causes the disturbance of the Earth's space environment, which makes the ionosphere change in different degrees, showing diurnal, diurnal and seasonal variations. This makes detection more difficult. How to detect and capture ionospheric anomalies more reliably has become a key problem that needs to be solved. Aiming at these problems, the regularity of periodic variation of ionosphere, the construction of ionospheric TEC model and the construction of 3D tomography model are discussed in this paper. The main contents of this paper are as follows: 1) the research status of ionospheric anomalies at home and abroad is summarized, and the structure and characteristics of ionospheric stratification are introduced. In this paper, the structure and characteristics of the ionospheric model are discussed in detail. 2) the global ionospheric TEC grid model GIM provided by CODE in 2013 and 2006 is used to analyze the total electron content in the zenith direction over Wuhan station. 3) the algorithm principle of calculating ionospheric TEC using GPS dual-frequency observations is described in detail. The data preprocessing of GPS, the solution of hardware delay and the establishment of grid model are described in detail. 4) the sliding quartile method, sliding window method, Kalman filter method and ARIMA time series method are introduced. The method is used to predict a normal TEC data directly, and the accuracy of the predicted background value under different methods is compared and analyzed. For the same section of TEC data, after removing the long period and trend changes, the method is used to predict, The accuracy of the predicted background value is compared. Compared with the unprocessed TEC data, four methods are used to predict the background value accuracy. The experimental results show that the prediction accuracy of the long-period and trend TEC data is higher than that of the unprocessed TEC data. The prediction accuracy of the processed TEC data by the sliding quartile distance method and the Kalman filter method is higher than that of the other two algorithms. 5) using the data of IGS tracking station, Sichuan observation network and land network to construct local fine grid model and three-dimensional tomography model for the ionosphere before and after Wenchuan earthquake, East Japan earthquake and Lushan earthquake. Two kinds of aperiodic and trending sliding quartile distance method and Kalman filter method are used to analyze the anomalous variation of ionospheric VTEC in the area near the epicenter before and after the earthquake. The influence factors such as solar activity and geomagnetic disturbance are excluded. It is found that the TEC anomaly occurred several days before the epicenter of the three major earthquakes, and the anomalous region presents conjugate structure.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：P352;P228.4

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