本文選題：GPS坐標(biāo)時間序列 + 噪聲特性��； 參考：《長安大學(xué)》2017年碩士論文

【摘要】：高精度GPS坐標(biāo)時間序列精度已達(dá)到毫米級,這使GPS觀測技術(shù)不僅可以實(shí)時監(jiān)測地表劇烈運(yùn)動造成的瞬時形變,也可監(jiān)測到地表微小的蠕動形變。目前GPS已成為連續(xù)、動態(tài)、實(shí)時觀測地表形變的最佳技術(shù)手段。本文在此背景下以GPS坐標(biāo)時間序列為研究對象,主要探究了GPS坐標(biāo)時間序列的趨勢項、季節(jié)項振幅及相位、噪聲類型等特征參數(shù)、不同GPS坐標(biāo)時間序列分析方法所求特征參數(shù)的差異性、共模誤差對GPS坐標(biāo)時間序列特征參數(shù)的影響、及GPS坐標(biāo)時間序列季節(jié)項成因分析。圍繞上述幾點(diǎn)研究內(nèi)容,本文所做的研究工作和研究成果主要包括以下幾點(diǎn)內(nèi)容:(1)在介紹GPS數(shù)據(jù)處理基本原理、解算策略及方法、數(shù)據(jù)處理流程的基礎(chǔ)上詳細(xì)敘述了GAMIT/GLOBK軟件中涉及到的常用坐標(biāo)系及各坐標(biāo)系之間的換算關(guān)系。(2)文中以中國內(nèi)陸海原斷裂、六盤山斷裂、西秦嶺北緣斷裂所在區(qū)域(文中稱A區(qū)域)、美國加州南部舊金山灣地區(qū)(文中稱B區(qū)域)為研究區(qū)域,研究了區(qū)域內(nèi)約130個GPS測站坐標(biāo)時間序列的特征參數(shù),發(fā)現(xiàn)A區(qū)域內(nèi)37個GPS測站時間序列的特征參數(shù)在斷裂兩側(cè)沒有明顯差異,B區(qū)域內(nèi)有部分GPS測站的趨勢項在斷裂兩側(cè)有差異,說明目前B區(qū)域斷裂兩側(cè)的地殼運(yùn)動仍然活躍。(3)針對所選區(qū)域,研究了不同參考框架下GPS坐標(biāo)時間序列的差異。研究結(jié)果表明不同參考框架下GPS坐標(biāo)時間序列的水平(N、E方向)趨勢項表現(xiàn)不同,而垂向(U方向)趨勢項、各方向序列的季節(jié)性變化幾乎不受參考框架影響。(4)對比了諧波模型、EMD獲取的GPS坐標(biāo)時間序列的特征參數(shù),研究結(jié)果表明對絕大多數(shù)GPS測站而言,兩種方法獲取的測站趨勢項基本一致,個別測站趨勢項的不一致很可能是受序列季節(jié)性波動的影響,但兩種方法獲取的測站季節(jié)項、坐標(biāo)殘差時間序列有些許差異。通過頻譜分析發(fā)現(xiàn)EMD獲取的測站季節(jié)項包含了原始序列中主要的周期項,且季節(jié)項噪聲水平遠(yuǎn)低于原始序列,而諧波模型獲取的周期項僅包含了年、半年周期項。(5)本文探究了地表負(fù)載、區(qū)域GPS網(wǎng)共模誤差對GPS測站時間序列的影響。對比了地表負(fù)載改正前后GPS測站時間序列特征參數(shù)的變化,發(fā)現(xiàn)地表負(fù)載改正前后測站各方向的趨勢項變化甚微,可以忽略不計,但測站周期項振幅、噪聲類型均有不同程度的變化。而區(qū)域網(wǎng)共模誤差對測站各項特征參數(shù)均有影響,濾波后GPS測站時間序列的周期項振幅、相位均表現(xiàn)出局部一致性,而濾波前則比較離散。濾波后殘差時間序列的標(biāo)準(zhǔn)差明顯小于濾波前殘差序列的標(biāo)準(zhǔn)差,另外濾波前后測站水平反向的速度場在運(yùn)動方向上有較明顯的差異。
[Abstract]:The precision of high precision GPS coordinate time series has reached millimeter order, which makes GPS observation technology can not only monitor the instantaneous deformation caused by the violent motion of the earth's surface in real time, but also detect the tiny creep deformation of the surface. At present, GPS has become the best technique for continuous, dynamic and real-time observation of surface deformation. In this paper, the GPS coordinate time series is taken as the research object, and the characteristic parameters of GPS coordinate time series, such as trend term, seasonal term amplitude and phase, noise type and so on, are discussed. The difference of characteristic parameters obtained by different GPS coordinate time series analysis methods, the influence of common mode error on the characteristic parameters of GPS coordinate time series, and the cause of formation of seasonal term of GPS coordinate time series are analyzed. The research work and results of this paper mainly include the following contents: 1) introducing the basic principle of GPS data processing, solving strategies and methods. On the basis of the data processing flow, this paper describes in detail the commonly used coordinate systems and the conversion relations between the coordinate systems involved in the GAMIT/GLOBK software. In this paper, the inland Haiyuan fault and Liupanshan fault in China are used. The area where the fault is located in the northern margin of the West Qinling Mountains (area A in this paper) and the San Francisco Bay area (area B in southern California) in the United States of America are studied. The characteristic parameters of the coordinate time series of about 130 GPS stations in the region are studied. It is found that the characteristic parameters of the time series of 37 GPS stations in area A have no obvious difference on both sides of the fault. It shows that the crustal movement on both sides of the fault in region B is still active. (3) for the selected area, the difference of GPS coordinate time series under different reference frames is studied. The results show that the trend term of GPS coordinate time series is different in horizontal direction and in the direction of vertical U) under different reference frames. The seasonal variation of each direction sequence is almost independent of the reference frame. (4) the characteristic parameters of the GPS coordinate time series obtained by the harmonic model EMD are compared. The results show that for the majority of GPS stations, The trend terms obtained by the two methods are basically the same, and the inconsistency of the trend terms of individual stations is probably affected by the seasonal fluctuation of the sequence, but the time series of coordinate residuals obtained by the two methods are somewhat different. Through spectrum analysis, it is found that the seasonal term obtained by EMD contains the main periodic term in the original sequence, and the noise level of the seasonal term is much lower than that of the original sequence, while the period term obtained by harmonic model contains only a year. In this paper, the influence of surface load and regional GPS network common-mode error on the time series of GPS stations is investigated. The change of time series characteristic parameters of GPS station before and after the surface load correction is compared. It is found that the trend item of each direction of the station has little change before and after the surface load correction, which can be ignored, but the amplitude of the period term of the station is negligible. The type of noise varies in varying degrees. The common-mode error of the regional network has an effect on the characteristic parameters of the station. The amplitude and phase of the periodic term of the GPS time series show local consistency after filtering, but before filtering, they are more discrete. The standard deviation of the time series of residual error after filtering is obviously smaller than that of the series of residual errors before and after filtering. In addition, the velocity field of the measured station before and after filtering is obviously different in the direction of motion.
【學(xué)位授予單位】：長安大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：P228.4

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