本文選題：極化干涉SAR + 散射相位　； 參考：《中南大學(xué)》2013年碩士論文

【摘要】：極化干涉SAR是一門結(jié)合極化SAR和干涉SAR優(yōu)點(diǎn)的新興技術(shù),既能獲得觀測(cè)目標(biāo)的精細(xì)物理特征和紋理特征,又能夠反映觀測(cè)目標(biāo)的空間分布特性。通過極化散射矩陣分解技術(shù)在分辨單元內(nèi)實(shí)現(xiàn)多種散射機(jī)制相位中心分離,為植被覆蓋下的地表地形測(cè)量和植被高度估計(jì)提供了可能。因此,極化干涉SAR技術(shù)可被用于植被參數(shù)反演,對(duì)地面資源和生態(tài)環(huán)境的監(jiān)測(cè)有著重要的意義。 本文對(duì)極化干涉SAR相關(guān)理論和極化干涉SAR植被高度反演算法進(jìn)行了研究,主要工作和創(chuàng)新點(diǎn)如下： (1)深入分析了兩種典型極化干涉SAR散射相位中心估計(jì)方法。由于極化干涉SAR散射相位中心估計(jì)算法是植被高度反演的關(guān)鍵步驟,于是本文深入研究了基于ESPRIT算法的極化干涉SAR散射相位中心估計(jì)算法和基于Freeman-極化干涉SAR互協(xié)方差矩陣分解的相位中心估計(jì)算法,并通過模擬和真實(shí)極化干涉SAR數(shù)據(jù)驗(yàn)證算法的性能。實(shí)驗(yàn)結(jié)果發(fā)現(xiàn)：基于ESPRIT相位估計(jì)算法能較好地估計(jì)出植被冠層頂部相位中心,但是難以有效估計(jì)出地面散射相位中心；而基于Freeman-極化干涉SAR互協(xié)方差矩陣分解的相位中心估計(jì)算法能夠較好地估計(jì)出地面散射相位。 (2)結(jié)合ESPRIT相位中心估計(jì)算法及Freeman-極化干涉互協(xié)方差矩陣分解的相位中心估計(jì)算法的優(yōu)點(diǎn),提出了一種改進(jìn)的ESPRIT的植被高度反演算法。該算法解決了傳統(tǒng)ESPRIT植被高度算法中估計(jì)的地面散射相位不準(zhǔn)確這一問題。通過選取模擬和真實(shí)極化干涉SAR數(shù)據(jù)進(jìn)行實(shí)驗(yàn),驗(yàn)證了改進(jìn)的算法較之傳統(tǒng)的方法能夠獲得更高的反演精度。 (3)提出了一種結(jié)合Freeman-極化干涉互協(xié)方差矩陣分解及RVOG模型的植被高度反演算法。該算法將Freeman-極化干涉分解估算的地面散射相位作為RVOG模型的初始地表相位,然后利用RVOG模型進(jìn)行植被高度反演。利用模擬和真實(shí)的極化干涉SAR數(shù)據(jù)進(jìn)行實(shí)驗(yàn),驗(yàn)證了該算法的有效性,結(jié)果表明該方法可以獲得更高的植被高度反演精度。圖：55幅,表：6個(gè),參考文獻(xiàn)：52篇。
[Abstract]:Polarimetric interference (SAR) is a new technology which combines the advantages of polarized SAR and interference SAR. It can not only obtain the fine physical and texture features of the observed target, but also reflect the spatial distribution of the observed target. The polarimetric scattering matrix decomposition technique is used to separate the phase centers of various scattering mechanisms in the resolution unit, which makes it possible to measure the surface topography and estimate the height of vegetation under vegetation cover. Therefore, polarimetric interferometry (SAR) can be used to invert vegetation parameters, which is of great significance to the monitoring of surface resources and ecological environment. In this paper, the correlation theory of polarimetric interferometry (SAR) and the vegetation height inversion algorithm of polarimetric interferometry (SAR) are studied. The main work and innovations are as follows: 1) two typical polarimetric interferometric SAR scattering phase center estimation methods are analyzed. Because the phase center estimation algorithm of polarization interference SAR scattering is a key step in vegetation height inversion. In this paper, the phase center estimation algorithm of polarimetric interference SAR scattering based on ESPRIT algorithm and the phase center estimation algorithm based on Freeman-polarization interference SAR cross-covariance matrix decomposition are studied. The performance of the algorithm is verified by simulation and real polarization interference SAR data. The experimental results show that the ESPRIT phase estimation algorithm can estimate the top phase center of the vegetation canopy, but it is difficult to estimate the surface scattering phase center effectively. The phase center estimation algorithm based on Freeman-polarization interferometric SAR cross-covariance matrix decomposition can estimate the surface scattering phase well. Combining the advantages of the ESPRIT phase center estimation algorithm and the phase center estimation algorithm based on Freeman-polarization interference covariance matrix decomposition, an improved vegetation height inversion algorithm for ESPRIT is proposed. The algorithm solves the problem of inaccurate ground scattering phase estimation in the traditional ESPRIT vegetation height algorithm. By selecting simulated and real polarimetric interferometric SAR data, it is verified that the improved algorithm can obtain higher inversion accuracy than the traditional method. A vegetation height inversion algorithm based on Freeman-polarization interference covariance matrix decomposition and RVOG model is proposed. The ground scattering phase estimated by Freeman-polarization interferometric decomposition is taken as the initial surface phase of RVOG model, and then vegetation height inversion is carried out by using RVOG model. The validity of the proposed algorithm is verified by simulation and real polarimetric interferometric SAR data. The results show that the proposed method can obtain higher accuracy of vegetation height inversion. Figs. 55, tables: 6, references: 52.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TN957.52;P23

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