發(fā)布時(shí)間：2018-03-06 10:48

  本文選題：壓縮感知　切入點(diǎn)：層析SAR成像　出處：《北京建筑大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：合成孔徑雷達(dá)(SAR)三維成像技術(shù)不僅具有傳統(tǒng)SAR系統(tǒng)所具備的全天時(shí)、全天候等優(yōu)勢(shì),而且解決了三維成像中將高度向投影到二維平面時(shí)產(chǎn)生的疊掩問(wèn)題,其能將目標(biāo)高度向與距離向完全分離,實(shí)現(xiàn)目標(biāo)的三維成像。在地形測(cè)繪、軍事偵察、資源勘測(cè)、災(zāi)害的精準(zhǔn)評(píng)估以及森林資源與生態(tài)監(jiān)測(cè)的動(dòng)態(tài)監(jiān)測(cè)等方面具有廣泛的應(yīng)用前景,是成像雷達(dá)科學(xué)工作研究者的研究熱點(diǎn)。層析SAR三維成像利用多次航過(guò)或者多天線單次航過(guò)獲取的同一地區(qū)SAR二維圖像,在距離垂向上運(yùn)用層析原理進(jìn)行孔徑合成,從而實(shí)現(xiàn)高分辨三維成像。合成孔徑雷達(dá)三維成像無(wú)須針對(duì)飛行器進(jìn)行飛行軌跡的刻意控制,并且無(wú)須進(jìn)行特定的位置控制,就能具備真正意義上的三維成像能力,在成像雷達(dá)中具有很好的應(yīng)用前景。但是,層析SAR三維成像研究不夠成熟,從理論研究到應(yīng)用實(shí)現(xiàn)仍需要有很長(zhǎng)的發(fā)展過(guò)程。最近幾年由于壓縮感知理論的提出,解決了數(shù)據(jù)獲取中必須要滿足奈奎斯特采樣定理而所帶來(lái)的數(shù)據(jù)存儲(chǔ)量大和傳輸困難的問(wèn)題。該理論指出,當(dāng)信號(hào)具有稀疏性時(shí),通過(guò)求解非線性最優(yōu)化問(wèn)題,可以用遠(yuǎn)低于奈奎斯特采樣定理對(duì)信號(hào)進(jìn)行重構(gòu)。層析SAR三維成像理論中,對(duì)目標(biāo)的觀測(cè)數(shù)量遠(yuǎn)低于距離垂向上目標(biāo)(即信號(hào))的點(diǎn)數(shù),但由于距離垂向上的目標(biāo)(信號(hào))點(diǎn)數(shù)又滿足了稀疏性的特點(diǎn),因此基于壓縮感知架構(gòu)的層析SAR三維成像理論應(yīng)運(yùn)而生。本文基于此,針對(duì)壓縮感知的層析SAR三維成像開(kāi)展了深入研究。本文首先研究了層析SAR成像的幾何模型、數(shù)學(xué)模型;針對(duì)層析SAR成像的數(shù)學(xué)模型,著重研究基于壓縮感知的層析SAR三維成像方法。以壓縮感知作為基礎(chǔ)理論,分別研究了正交匹配追蹤、正則化正交匹配追蹤、壓縮感知匹配追蹤、廣義正交匹配追蹤等層析SAR成像算法;在研究和分析算法的基礎(chǔ)上,運(yùn)用仿真數(shù)據(jù)和真實(shí)數(shù)據(jù)對(duì)這些方法進(jìn)行驗(yàn)證。仿真數(shù)據(jù)反映了算法有效性。根據(jù)層析SAR成像的流程,論文還研究了SAR圖像配準(zhǔn)方法,并根據(jù)真實(shí)數(shù)據(jù)對(duì)其進(jìn)行驗(yàn)證,得到良好的配準(zhǔn)效果。針對(duì)真實(shí)數(shù)據(jù)的驗(yàn)證,論文選取了北京地區(qū)鳥(niǎo)巢附近的盤(pán)古七星酒店作為研究對(duì)象,采用TerraSAR-X數(shù)據(jù)進(jìn)行試驗(yàn),真實(shí)數(shù)據(jù)的試驗(yàn)結(jié)果表明論文方法的合理性。本文的創(chuàng)新點(diǎn)在于:(1)提出基于相關(guān)函數(shù)的圖像精配準(zhǔn)方法。該方法首先對(duì)圖像粗配準(zhǔn),然后進(jìn)行分塊插值處理,提高了圖像的配準(zhǔn)精度。(2)采用正交匹配追蹤、正則化正交匹配追蹤、壓縮感知匹配、廣義正交匹配等算法進(jìn)行壓縮感知的仿真,對(duì)其重構(gòu)結(jié)果進(jìn)行對(duì)比分析,評(píng)價(jià)了上述四種算法的優(yōu)劣。
[Abstract]:Synthetic Aperture Radar (SAR) 3D imaging technology not only has the advantages of all-day, all-weather and so on as the traditional SAR system, but also solves the problem of overlay when the height is projected to the two-dimensional plane in 3D imaging. It can completely separate the height and distance of the target and realize the three-dimensional imaging of the target. In topographic mapping, military reconnaissance, resource survey, The accurate assessment of disasters and the dynamic monitoring of forest resources and ecology have wide application prospects. Tomographic SAR 3D imaging is a hot research topic in imaging radar science. Using SAR 2D images of the same area obtained by multiple voyages or single voyage with multiple antennas, the tomography principle is used to synthesize aperture at vertical distance. In order to achieve high resolution 3D imaging, synthetic Aperture Radar (SAR) 3D imaging does not require deliberate control of the flight trajectory of the aircraft, nor does it require specific position control, in order to have a true three-dimensional imaging capability. It has a good application prospect in imaging radar. However, the study of tomography SAR 3D imaging is not mature enough, and it still needs a long development process from the theoretical research to the application. In recent years, the compression sensing theory has been proposed. The problem of large data storage and difficult transmission caused by Nyquist sampling theorem in data acquisition is solved. The theory points out that when the signal is sparse, the nonlinear optimization problem is solved. The signal can be reconstructed with a far lower sampling theorem than Nyquist. In the theory of SAR tomography, the number of observations on a target is much lower than the number of points in the vertical target (the signal). However, because the number of targets (signals) in vertical distance satisfies the characteristics of sparsity, the theory of three-dimensional tomography (SAR) imaging based on compression sensing architecture emerges as the times require. In this paper, the geometric model and mathematical model of tomography SAR imaging are studied firstly, and the mathematical model of tomographic SAR imaging is also studied. Based on the theory of compressed sensing, orthogonal matching tracking, regularized orthogonal matching tracking and compressed perceptual matching tracking are studied respectively. Based on the research and analysis of the algorithms, these methods are verified by simulation data and real data. The simulation data reflect the validity of the algorithm. According to the process of tomographic SAR imaging, This paper also studies the SAR image registration method, and verifies it according to the real data, and obtains good registration effect. In view of the real data verification, the paper selects the Pangu Seven Star Hotel near the Bird's Nest in Beijing as the research object. The experimental results of TerraSAR-X data show that the method is reasonable. The innovation of this paper lies in: (1) an image registration method based on correlation function is proposed. Then the block interpolation processing is carried out to improve the registration accuracy of the image. The algorithm of orthogonal matching tracking, regularized orthogonal matching tracking, compressed perceptual matching, generalized orthogonal matching and so on is used to simulate the compression perception. The reconstruction results are compared and analyzed, and the advantages and disadvantages of the above four algorithms are evaluated.
【學(xué)位授予單位】：北京建筑大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN957.52

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 耿杰;范劍超;初佳蘭;王洪玉;;基于深度協(xié)同稀疏編碼網(wǎng)絡(luò)的海洋浮筏SAR圖像目標(biāo)識(shí)別[J];自動(dòng)化學(xué)報(bào);2016年04期

2 畢輝;張冰塵;洪文;;基于RIPless理論的層析SAR成像航跡分布優(yōu)化方法[J];航空學(xué)報(bào);2016年02期

3 廖明生;魏戀歡;汪紫蕓;Timo Balz;張路;;壓縮感知在城區(qū)高分辨率SAR層析成像中的應(yīng)用[J];雷達(dá)學(xué)報(bào);2015年02期

4 李文梅;陳爾學(xué);李增元;;多基線干涉層析SAR提取森林樹(shù)高方法研究[J];林業(yè)科學(xué)研究;2014年06期

5 李文梅;李增元;陳爾學(xué);馮琦;;層析SAR反演森林垂直結(jié)構(gòu)參數(shù)現(xiàn)狀及發(fā)展趨勢(shì)[J];遙感學(xué)報(bào);2014年04期

6 廖明生;魏戀歡;BALZ Timo;張路;;TomoSAR技術(shù)在城市形變監(jiān)測(cè)中的應(yīng)用[J];上海國(guó)土資源;2013年04期

7 徐穎;周焰;;SAR圖像配準(zhǔn)方法綜述[J];地理空間信息;2013年03期

8 閔銳;楊倩倩;皮亦鳴;曹宗杰;;基于正則化正交匹配追蹤的SAR層析成像[J];電子測(cè)量與儀器學(xué)報(bào);2012年12期

9 尹曉慧;張寶菊;王為;雷晴;;基于改進(jìn)層式DCT的壓縮感知圖像處理[J];計(jì)算機(jī)工程;2012年09期

10 李蘊(yùn)華;;一種改進(jìn)的圖像分塊壓縮感知模型[J];計(jì)算機(jī)工程與應(yīng)用;2011年25期

相關(guān)博士學(xué)位論文 前5條

1 張紅敏;SAR圖像高精度定位技術(shù)研究[D];解放軍信息工程大學(xué);2013年

2 孫希龍;SAR層析與差分層析成像技術(shù)研究[D];國(guó)防科學(xué)技術(shù)大學(xué);2012年

3 王金峰;SAR層析三維成像技術(shù)研究[D];電子科技大學(xué);2010年

4 劉寶泉;干涉合成孔徑雷達(dá)測(cè)量關(guān)鍵技術(shù)研究[D];西安電子科技大學(xué);2008年

5 柳祥樂(lè);多基線層析成像合成孔徑雷達(dá)研究[D];中國(guó)科學(xué)院研究生院（電子學(xué)研究所）;2007年

相關(guān)碩士學(xué)位論文 前4條

1 張立造;壓縮感知理論與技術(shù)研究[D];電子科技大學(xué);2016年

2 徐靜;基于壓縮感知的SAR圖像目標(biāo)識(shí)別方法研究[D];南京航空航天大學(xué);2013年

3 蘆婧;小波變換圖像去噪及其在SAR圖像中的應(yīng)用[D];西安科技大學(xué);2011年

4 陳欽;多基線層析SAR成像方法研究[D];電子科技大學(xué);2011年

，

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