本文選題：小麥 + 微波遙感�。� 參考：《寧夏大學(xué)》2017年碩士論文

【摘要】：小麥不僅是三大谷物之一,更是我國(guó)的主要糧食作物之一。因此,只有能夠?qū)π←湻N植面積進(jìn)行精確的估算并且可以監(jiān)測(cè)生長(zhǎng)過(guò)程中的病蟲害,才能更好的提高農(nóng)作物產(chǎn)量。目前來(lái)看,通過(guò)使用微波遙感技術(shù)來(lái)勘測(cè)農(nóng)作物已經(jīng)獲取了很大的成績(jī)。光學(xué)遙感在這個(gè)領(lǐng)域雖然運(yùn)用的較早,數(shù)據(jù)也更方便獲得,可是它容易受天氣的干擾,導(dǎo)致了光學(xué)遙感在監(jiān)測(cè)植被時(shí)獲取到的數(shù)據(jù)不精確。而微波遙感技術(shù)不但可以全天候、全天時(shí)的進(jìn)行監(jiān)控測(cè)量,還能夠穿過(guò)植被,這些優(yōu)點(diǎn)不僅補(bǔ)足了光學(xué)遙感的缺點(diǎn),還直接推進(jìn)了微波遙感在農(nóng)業(yè)的發(fā)展。本文以農(nóng)作物——小麥為研究對(duì)象,研究極化干涉SAR對(duì)隨機(jī)粗糙面上小麥的電磁散射機(jī)理并構(gòu)建小麥的電磁散射回波響應(yīng)系統(tǒng)軟件。首先,在使用Pol-InSAR對(duì)信號(hào)進(jìn)行處理的過(guò)程中,先對(duì)區(qū)域地點(diǎn)進(jìn)行勘測(cè)獲取圖像復(fù)數(shù)據(jù)信息,將兩副SAR影像的數(shù)據(jù)信息按照?qǐng)D像配準(zhǔn)、濾波、干涉處理、相位解纏以及數(shù)字高程反演等過(guò)程進(jìn)行研究,最后得到所勘測(cè)區(qū)域的三維坐標(biāo)。將雷達(dá)數(shù)據(jù)快速可視化,就能夠獲得對(duì)應(yīng)的數(shù)字高程信息。由于相位解纏的好壞決定了數(shù)字高程的準(zhǔn)確性,于是本文將幾種相位解纏方法進(jìn)行對(duì)比,為用戶及時(shí)提供信息以便于最終達(dá)到監(jiān)測(cè)小麥長(zhǎng)勢(shì)的目的。隨后,研究隨機(jī)粗糙面的入射角與后向散射系數(shù)的關(guān)系并完成了仿真。其中,對(duì)小麥進(jìn)行了抽象描述并構(gòu)建物理模型,可以清楚的看到小麥的入射角和后向散射系數(shù)變化的關(guān)系。經(jīng)過(guò)對(duì)小麥模型的構(gòu)建,研究并得到小麥的極化特性和相關(guān)特性,從而建立小麥入射角和后向散射系數(shù)之間的關(guān)系,為小麥生物物理參數(shù)的微波遙感定量反演奠定基礎(chǔ)。本文的主要工作內(nèi)容如下:1.介紹了 Pol-InSAR處理信號(hào)的具體過(guò)程及步驟。分別讀取主輔SAR圖像數(shù)據(jù),對(duì)圖像進(jìn)行影像配準(zhǔn)、干涉圖生成、噪聲濾波、相位解纏等處理,最終可以得到三維數(shù)字高程模型重建。2.研究了隨機(jī)粗糙面的建模方法,對(duì)其中的部分方法進(jìn)行簡(jiǎn)單闡述,其中,主要對(duì)經(jīng)典的Kirchhoff近似理論和改進(jìn)積分方程法(AIEM)進(jìn)行詳細(xì)說(shuō)明,并在文中重點(diǎn)提出統(tǒng)計(jì)拓展改進(jìn)積分方程法(SEAIEM)算法。3.將小麥抽象成物理模型,小麥葉、莖、稈分別抽象成盤狀、針狀及有限長(zhǎng)圓柱,并且使用廣義瑞利金斯計(jì)算求得物理模型與后向散射系數(shù)之間的關(guān)系,為下一步小麥的整體建模構(gòu)建理論基礎(chǔ)。4.將隨機(jī)粗糙面和小麥的物理模型進(jìn)行相干疊加后,可以重構(gòu)小麥的整體模型,通過(guò)選擇小麥及粗糙面的參數(shù),能夠比較準(zhǔn)確地得到小麥微波后向散射系數(shù)隨入射角變化而變化的關(guān)系,為后期小麥的生物量反演做理論基礎(chǔ)。5.對(duì)以上研究?jī)?nèi)容進(jìn)行MATLAB GUI界面設(shè)計(jì),構(gòu)建小麥的電磁散射回波響應(yīng)系統(tǒng)軟件。
[Abstract]:Wheat is not only one of the three cereals, but also one of the main food crops in China. Therefore, only by accurately estimating the planting area of wheat and monitoring the diseases and pests in the growth process, can the crop yield be improved better. At present, the use of microwave remote sensing technology to survey crops has made great achievements. Although optical remote sensing has been used in this field earlier and the data are more convenient to obtain, it is easy to be disturbed by weather, resulting in inaccurate data obtained by optical remote sensing in monitoring vegetation. Microwave remote sensing technology can not only monitor and measure all weather, all day, but also pass through vegetation. These advantages not only complement the shortcomings of optical remote sensing, but also directly promote the development of microwave remote sensing in agriculture. In this paper, the mechanism of electromagnetic scattering of wheat on random rough surface by polarimetric interferometric SAR (SAR) is studied, and the system software of electromagnetic scattering echo response of wheat is constructed. First of all, in the process of using Pol-InSAR to process the signal, the complex data information of the two sets of SAR images is obtained by surveying the area first, and the data information of the two sets of SAR images is registered, filtered, and interferentially processed according to the image registration, filtering and interference processing. The phase unwrapping and digital elevation inversion are studied, and the 3D coordinates of the surveyed area are obtained. If the radar data is visualized quickly, the corresponding digital elevation information can be obtained. Because the accuracy of digital elevation is determined by the quality of phase unwrapping, several phase unwrapping methods are compared in this paper in order to provide users with timely information so as to achieve the purpose of monitoring wheat growth. Then, the relation between the incidence angle of random rough surface and the backscattering coefficient is studied and the simulation is completed. The relation between the incidence angle and the backscatter coefficient of wheat can be clearly seen by the abstract description of wheat and the construction of physical model. Based on the establishment of wheat model, the polarization and correlation characteristics of wheat were studied, and the relationship between incidence angle and backscattering coefficient was established, which laid a foundation for quantitative retrieval of wheat biophysical parameters by microwave remote sensing. The main work of this paper is as follows: 1. The process and steps of Pol-InSAR signal processing are introduced. After reading the main and auxiliary SAR image data, image registration, interferogram generation, noise filtering, phase unwrapping and so on, 3D digital elevation model reconstruction. 2. In this paper, the modeling method of random rough surface is studied, and some of the methods are briefly described. Among them, the classical Kirchhoff approximation theory and the improved integral equation method (AIEM) are described in detail. In this paper, a statistical extended improved integral equation method (SEAIEM) algorithm. Wheat is abstracted into a physical model, and wheat leaves, stems and culms are abstracted into disk, needle and finite columns, respectively, and the relationship between the physical model and the backscattering coefficient is obtained by using the generalized Rayleggins calculation. Build the theoretical basis for the next wheat overall modeling. 4. After coherent superposition of random rough surface and wheat physical model, the whole wheat model can be reconstructed, and the parameters of wheat and rough surface can be selected. The relationship between the microwave backscattering coefficient and the incidence angle of wheat can be obtained accurately, which provides a theoretical basis for the retrieval of wheat biomass in the later stage. The above research contents are designed by MATLAB GUI interface, and the electromagnetic scattering echo response system software of wheat is constructed.
【學(xué)位授予單位】：寧夏大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：S512.1;TP722.6

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