本文選題：表層穿透雷達(dá) + 精細(xì)成像��； 參考：《國(guó)防科學(xué)技術(shù)大學(xué)》2014年碩士論文

【摘要】：表層穿透雷達(dá)以其穿透介質(zhì)實(shí)施觀測(cè)的優(yōu)良性能,正日益為人們所重視,在安檢防暴、掃雷探測(cè)、無(wú)損評(píng)估(Nondestructive Evaluation,NDE)等諸多軍事和民用場(chǎng)合得到了廣泛應(yīng)用。表層穿透雷達(dá)成像技術(shù)作為直觀呈現(xiàn)探測(cè)結(jié)果、降低數(shù)據(jù)解譯難度的重要手段,發(fā)展卻相對(duì)滯后,離實(shí)用化的要求還有一定差距。本文提出了表層穿透雷達(dá)精細(xì)成像的概念,核心是高分辨成像、改善適應(yīng)性以及增強(qiáng)穩(wěn)健性,以期提高表層穿透雷達(dá)的成像性能,推動(dòng)其實(shí)用化發(fā)展。本文研究表層穿透雷達(dá)精細(xì)成像技術(shù),主要包括:表層穿透雷達(dá)成像基本原理、快速自聚焦方法和高分辨成像方法。首先,介紹表層穿透雷達(dá)成像機(jī)理。表層穿透雷達(dá)成像屬于近場(chǎng)成像問(wèn)題,因此基于平面波近似的成像算法并不適用,必須在充分考慮散射場(chǎng)的波動(dòng)性的基礎(chǔ)上研究成像算法。第二章利用波動(dòng)方程,對(duì)波恩近似下的散射場(chǎng)表示形式進(jìn)行分析,研究近場(chǎng)條件下的三維距離偏移算法和全息成像算法,并對(duì)算法性能和空間采樣準(zhǔn)則進(jìn)行討論。其次,研究表層穿透雷達(dá)快速自聚焦成像方法。在工程應(yīng)用中,成像場(chǎng)景的參數(shù)常常難以準(zhǔn)確獲取,成像結(jié)果容易受參數(shù)誤差影響而發(fā)生模糊、分辨率下降等問(wèn)題。為增強(qiáng)成像算法對(duì)環(huán)境條件的適應(yīng)性,減輕對(duì)人工干預(yù)的依賴(lài),第三章研究了自動(dòng)調(diào)整和修正成像參數(shù)以實(shí)現(xiàn)準(zhǔn)確聚焦成像的方法。本文首先介紹基于幅度和的自聚焦算法,通過(guò)合理地選擇聚焦度量來(lái)減少運(yùn)算量,在最優(yōu)化聚焦度量過(guò)程中搜索最優(yōu)成像參數(shù)。然后,從信號(hào)的卷積退化模型來(lái)重新認(rèn)識(shí)散焦問(wèn)題,提出一種基于反卷積去除參數(shù)誤差的影響來(lái)實(shí)現(xiàn)自聚焦的算法。最后,研究表層穿透雷達(dá)高分辨率成像技術(shù)。表層穿透雷達(dá)方位向分辨率通常受到合成孔徑范圍、工作頻率等的制約,可以通過(guò)拓寬頻譜支撐區(qū)的方法來(lái)提高成像分辨率。第四章研究了兩種拓展頻譜支撐區(qū)來(lái)提高成像分辨率的方法。一種是基于自回歸模型的譜外推方法,利用線(xiàn)性預(yù)測(cè)模型來(lái)計(jì)算支撐區(qū)外的頻譜成分,從而獲取額外的帶寬。另一種是反卷積校頻譜均衡的高分辨成像方法,通過(guò)消除天線(xiàn)方向圖對(duì)高頻分量的抑制作用,均衡高低頻成分,達(dá)到擴(kuò)展支撐區(qū)寬度的目的。本文通過(guò)構(gòu)建的實(shí)驗(yàn)系統(tǒng)收集實(shí)測(cè)數(shù)據(jù)驗(yàn)證了所研究的各種算法,實(shí)驗(yàn)結(jié)果顯示這些算法對(duì)于提高成像質(zhì)量起到了重要作用。本文所研究的表層穿透雷達(dá)精細(xì)成像技術(shù),為提高表層穿透雷達(dá)成像性能、增強(qiáng)系統(tǒng)的適應(yīng)性和穩(wěn)健性打下了基礎(chǔ),推動(dòng)了表層穿透雷達(dá)的實(shí)用化進(jìn)程。
[Abstract]:Surface penetrating radar has been widely used in many military and civil fields, such as riot control, mine clearance detection, nondestructive evaluation, and so on, because of its excellent performance of observation in penetrating medium.Surface penetrating radar imaging technology as an important means to visualize the detection results and reduce the difficulty of data interpretation, the development of surface penetrating radar imaging technology is relatively lagging behind, and there is still a certain gap from the practical requirements.In this paper, the concept of fine imaging of surface penetrating radar is proposed, the core of which is high resolution imaging, improving adaptability and enhancing robustness, in order to improve the imaging performance of surface penetrating radar and promote its practical development.In this paper, the fine imaging technology of surface penetrating radar is studied, including the basic principle of surface penetrating radar imaging, fast self-focusing method and high-resolution imaging method.Firstly, the imaging mechanism of surface penetrating radar is introduced.Surface penetrating radar imaging is a near-field imaging problem, so the imaging algorithm based on plane wave approximation is not applicable. Therefore, it is necessary to study the imaging algorithm on the basis of fully considering the fluctuation of scattering field.In the second chapter, the representation of scattering field in the Bonn approximation is analyzed by using the wave equation, and the 3-D distance migration algorithm and holographic imaging algorithm under near-field condition are studied, and the performance of the algorithm and the spatial sampling criterion are discussed.Secondly, the fast self-focusing imaging method of surface penetrating radar is studied.In the engineering application, the parameters of the imaging scene are often difficult to obtain accurately, the imaging results are easily affected by the parameter error and the resolution is decreased.In order to enhance the adaptability of the imaging algorithm to the environmental conditions and reduce the dependence on human intervention, chapter 3 studies the method of automatically adjusting and modifying the imaging parameters to achieve accurate focus imaging.In this paper, we first introduce a self-focusing algorithm based on amplitude sum. By selecting the focusing metric reasonably, we can reduce the computational complexity and search for the optimal imaging parameters in the process of optimization focusing measurement.Then, the defocusing problem is re-recognized from the signal convolution degradation model, and a self-focusing algorithm based on the effect of deconvolution removal parameter error is proposed.Finally, the high resolution imaging technology of surface penetrating radar is studied.The azimuth resolution of surface penetrating radar is usually restricted by the range of synthetic aperture and the working frequency.In chapter 4, two methods to improve imaging resolution are studied.One is the spectral extrapolation method based on the autoregressive model, which uses the linear prediction model to calculate the spectrum components outside the support area, thus obtaining the extra bandwidth.The other is the high resolution imaging method of deconvolution correction spectrum equalization. By eliminating the suppression effect of antenna pattern on the high frequency component, the high and low frequency components can be equalized to achieve the purpose of extending the width of the support region.The experimental results show that these algorithms play an important role in improving the imaging quality.The fine imaging technology of surface penetrating radar studied in this paper has laid a foundation for improving the imaging performance of surface penetrating radar, enhancing the adaptability and robustness of the system, and promoting the practical process of surface penetrating radar.
【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN957.52

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