本文關(guān)鍵詞： InSAR 缺失數(shù)據(jù)擬合 Kriging 擬合推估 各向異性　出處：《長安大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：InSAR監(jiān)測技術(shù)因為它具有高精度、高分辨率等諸多優(yōu)點,已逐步成為進(jìn)行地面變化監(jiān)測的重要方法手段之一,并在地震監(jiān)測、煤礦監(jiān)測、火山監(jiān)測等地質(zhì)災(zāi)害監(jiān)測研究以及地面沉降監(jiān)測等諸多方面得到了廣泛的應(yīng)用。但是,由于難以避免的受到時間、空間上各種去相干現(xiàn)象的影響,InSAR技術(shù)提取的形變信息中經(jīng)常存有缺失現(xiàn)象,因此需要后期對其進(jìn)行填補(bǔ)處理。對缺失的數(shù)據(jù)進(jìn)行擬合填補(bǔ),通常采用空間數(shù)據(jù)的插值方法來進(jìn)行。論文在對比分析常用的數(shù)據(jù)插值方法基礎(chǔ)上,重點討論了既能顧及結(jié)構(gòu)性成分,又能較好表達(dá)地表局部變化的擬合推估,并就各向異性隨機(jī)信號協(xié)方差函數(shù)的擬合進(jìn)行了研究,提出了基于各向異性的自適應(yīng)擬合推估法,并將其連同其他方法應(yīng)用于地質(zhì)災(zāi)害監(jiān)測缺失數(shù)據(jù)擬合之中。取得主要成果如下:1.討論了影響InSAR監(jiān)測成果的誤差源以及影響InSAR相干性、造成數(shù)據(jù)存有缺失的各去相干源;分析了影響缺失數(shù)據(jù)擬合精度的因素,發(fā)現(xiàn)除擬合方法外,缺失數(shù)據(jù)區(qū)域大小以及缺失數(shù)據(jù)變化起伏程度是影響擬合精度的關(guān)鍵因子。2.探討了多項式曲面擬合法、反距離加權(quán)法、克里金插值法和擬合推估法在缺失數(shù)據(jù)擬合應(yīng)用中的特性�？紤]到隨機(jī)信號通常表現(xiàn)出各向異性的特點,而在常規(guī)擬合推估方法中,常被認(rèn)為各向同性�；诖�,論文重點研究了各向異性協(xié)方差函數(shù)的擬合問題,提出了基于各向異性的自適應(yīng)擬合推估法,并將其應(yīng)用于缺失數(shù)據(jù)的擬合之中,通過實例驗證了基于各向異性的自適應(yīng)擬合推估法的有效性。3.以地面沉降監(jiān)測數(shù)據(jù)以及地震形變監(jiān)測數(shù)據(jù)作為實例,對比并且分析了不同的擬合方法的擬合精度,發(fā)現(xiàn)多項式曲面擬合法精度偏低,不適合于缺失數(shù)據(jù)的擬合;反距離加權(quán)盡管方法簡單,但對于大區(qū)域數(shù)據(jù)擬合,易導(dǎo)致擬合過于平滑的現(xiàn)象;克里金插值與擬合推估方法所具有的擬合精度較高。對于存有明顯區(qū)域特征的形變區(qū)域,采用分區(qū)擬合具有更高的填補(bǔ)精度。
[Abstract]:Because of its advantages of high precision and high resolution, InSAR monitoring technology has gradually become one of the important methods for ground change monitoring, and has been used in seismic monitoring and coal mine monitoring. Geological hazard monitoring, such as volcanic monitoring, and land subsidence monitoring have been widely used. However, due to the inevitable influence of time and space, there are various decoherence phenomena. The deformation information extracted by InSAR technology often has the phenomenon of missing, so it needs to be filled in the later stage, and the missing data is fitted to fill. Based on the comparison and analysis of the common data interpolation methods, this paper focuses on the fitting and estimation of the local changes of the ground surface, which not only takes into account the structural components but also can better express the local changes of the surface. The fitting of anisotropic random signal covariance function is studied, and an adaptive fitting method based on anisotropy is proposed. The main results are as follows: 1. The error sources that affect the InSAR monitoring results and the InSAR coherence are discussed. The various decoherence sources that cause the data to be missing; The factors influencing the fitting accuracy of missing data are analyzed, and it is found that except the fitting method. The size of missing data area and the fluctuation degree of missing data are the key factors to affect the fitting accuracy. 2. The polynomial surface fitting method and inverse distance weighting method are discussed. The characteristics of Kriging interpolation and fitting estimation in the application of missing data fitting, considering that random signals usually exhibit anisotropy, but in the conventional fitting and estimation methods. This paper focuses on the problem of anisotropic covariance function fitting, and puts forward an adaptive fitting and estimation method based on anisotropy, and applies it to the fitting of missing data. The validity of the adaptive fitting method based on anisotropy is verified by an example. 3. Taking the data of ground subsidence monitoring and seismic deformation monitoring as an example. By comparing and analyzing the fitting accuracy of different fitting methods, it is found that the fitting accuracy of polynomial surface fitting method is low, which is not suitable for the fitting of missing data. Although the inverse distance weighting method is simple, it is easy to make the fitting too smooth for large area data fitting. The method of Kriging interpolation and fitting and estimation has higher fitting accuracy and better filling accuracy for deformation regions with obvious regional characteristics.
【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】：2015
【分類號】：P225.1

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