本文關鍵詞：淺海水下地形雷達成像理論研究及應用　出處：《華東師范大學》2017年博士論文　論文類型：學位論文

  更多相關文章： 合成孔徑雷達 水下地形 數(shù)值模擬 雷達成像 破碎波 網(wǎng)格分辨率 長江口

【摘要】：海岸帶水深及其變化對通航安全、漁業(yè)養(yǎng)殖、軍事以及其它近海和離岸作業(yè)安全等都具有重要的意義。隨著全球氣候變化和人類活動的日益增強,海岸帶的水文和生態(tài)環(huán)境正面臨威脅,未來的海岸帶地貌演變趨勢也變得越發(fā)的不確定。因此科學家需要準確的水深數(shù)據(jù)來驗證相關科學理論,而海岸帶管理人員則需要根據(jù)水深情況制定相對應的發(fā)展策略。相比于傳統(tǒng)的船載測深手段,遙感技術擁有大范圍采樣以及短時間成像的優(yōu)勢。而SAR(合成孔徑雷達,Synthetic Aperture Radar)不僅兼顧了遙感技術的優(yōu)勢,還具備全天時和全天候的對地觀測能力,是未來監(jiān)測海岸帶地貌演變的一種潛在有效工具。雷達傳感器的一個重要應用就是可以觀測到水下地形特征的變化,原因是水深變化可以生成海表面流場的輻聚和輻散區(qū)進而改變海表面的粗糙度。這種復雜現(xiàn)象是由水下地形與流場以及海表波浪之間的相互作用所形成的,并可以通過流場模型和雷達成像模型的結(jié)合(水下地形雷達成像模型)來解釋。論文主要基于實測資料,利用遙感技術和數(shù)值模擬的手段研究淺海水下地形的2維雷達成像理論,并基于流場數(shù)值模型和RIM(Radar Imaging Model)模型的集成,建立了長江河口水下地形雷達成像模型。分析并解釋了長江河口 SAR影像上出現(xiàn)的由復雜地形和水動力過程所導致的亮暗條紋特征。為了進一步驗證該水下地形雷達成像模型的性能,研究采用控制變量的方法定量分析了水深、風場以及相關雷達參數(shù)對模擬的海表面粗糙度的影響。此外,還建立了一個理想模型來探究網(wǎng)格分辨率與模擬SAR影像之間的關系。研究的主要成果有:(1)建立了可以對擁有復雜水下地形的水域(如航道附近)進行任意時刻的模擬和雷達成像的2維長江口水下地形雷達成像模型。長江口 SAR圖像中垂直于流場方向出現(xiàn)的亮-暗-亮條紋無法由傳統(tǒng)的1維雷達成像模型進行解釋,1維的流場模型或雷達成像模型都會限制成像模型對復雜水下地形特征的描述。將2維流場模型應用于長江河口,可以模擬河口區(qū)域復雜的水動力環(huán)境以及由水深變化所導致的流場變化,與實測水文資料的良好對比結(jié)果證明了該模型手段的可靠性。由模擬流場計算得到的輻聚和輻散區(qū)與SAR影像上出現(xiàn)的海表面不規(guī)則2維亮暗條紋的位置相吻合,通過輸入風場以及相關雷達參數(shù),2維雷達成像模型模擬得到的SAR圖像與實測ERS-2和Sentinel-1 SAR圖像也較為一致,這表明該模型具備較為可靠的水下地形雷達成像能力,這也為后續(xù)對不同模擬參數(shù)的敏感度分析測試奠定了基礎。(2)模擬和分析了水深、風速、風向以及雷達視向等影響水下地形雷達成像的主要因素和條件。基于建立的雷達成像模型,通過控制變量的方法,改變水深、風速、風向以及雷達視向等部分雷達參數(shù),模擬和比較了其對雷達后向散射信號的影響。結(jié)果表明,海表面粗糙度受整體水深值變化影響較小,而受到水下地形坡度變化的影響較大。根據(jù)綜合分析的結(jié)果,順風(或逆風)的流場、相對低風速和垂直于風向的雷達視向條件更適合淺海水下地形雷達成像。(3)在水下地形雷達成像模型中考慮了破碎波的貢獻。輸入相同的流場數(shù)據(jù),采用不同的雷達成像模型模擬和比較了沿水下地形斜坡斷面方向的雷達后向散射信號,并與實測SAR影像相比較。傳統(tǒng)的二尺度模型低估了雷達后向散射信號,而引入破碎波貢獻的RIM模型結(jié)果則在模擬的幅度和相位上都表現(xiàn)較好,尤其是在較大入射角的情況下。(4)探討和分析了網(wǎng)格分辨率對模擬SAR影像的影響。采用理想數(shù)值模型排除了在實際情景條件下非海底地形因素的影響,模擬和分析不同尺度水下沙波情況下,不同網(wǎng)格分辨率對海表面粗糙度的影響。結(jié)果表明,對于小尺度的水下沙波(波長小于100米),采用10米的高分辨率網(wǎng)格模擬得到的相對雷達后向散射系數(shù)可以達到0.43 dB以上,這說明在適宜水下地形雷達成像的條件下,高分辨率的SAR影像具備探測小尺度水下地形的能力。在相同的水下地形條件下,網(wǎng)格分辨率的提升可以模擬得到更大的相對海表面粗糙度。相比于高分辨網(wǎng)格結(jié)果,使用低分辨率網(wǎng)格計算得到的雷達圖像較為模糊,并且無法充分描述出水下地形的準確幾何形狀及其所在的空間位置。當網(wǎng)格大小達到一定閾值后,模擬得到的雷達后向散射系數(shù)會趨于穩(wěn)定,這表明在水下地形雷達成像研究中,水下沙波的波長需要與網(wǎng)格間距達到一定的比例關系以充分描述水下地形所引起的海表面粗糙度變化。對于更復雜的實際環(huán)境,模型中網(wǎng)格大小的選擇還需要兼顧海底地形的復雜程度和實測SAR影像的空間分辨率。
[Abstract]:The depth and change of the coastal zone are of great significance to navigation safety, fishery culture, military and other offshore and offshore operations. With the increasing global climate change and human activities, the hydrological and ecological environment of the coastal zone is facing a threat. The trend of coastal evolution is becoming more and more uncertain. Therefore, scientists need accurate water depth data to verify relevant scientific theories, while coastal managers need to formulate corresponding strategies based on water depth. Compared with the traditional means of ship borne sounding, remote sensing technology has the advantages of large range sampling and short time imaging. SAR (synthetic aperture radar, Synthetic Aperture Radar) not only takes account of the advantages of remote sensing technology, but also has the ability of all-weather and all-weather observation. It is a potential effective tool for monitoring coastal landform evolution in the future. An important application of radar sensors is that we can observe the change of underwater topography. The reason is that the change of water depth can generate the convergence and divergence area of the sea surface flow field, and change the roughness of the sea surface. This complex phenomenon is formed by the interaction between the underwater topography and the flow field and the sea surface waves, and can be explained by the combination of the flow field model and the radar imaging model (underwater terrain radar imaging model). Based on the measured data, the 2 dimensional radar imaging theory of shallow underwater terrain is studied based on the remote sensing technology and numerical simulation. Based on the integration of the flow field numerical model and the RIM (Radar Imaging Model) model, the underwater terrain radar imaging model of the Changjiang Estuary is established. The characteristics of bright and dark stripes caused by complex terrain and hydrodynamic process in the SAR image of the Yangtze River estuary are analyzed and explained. In order to further verify the performance of the underwater terrain radar imaging model, the influence of water depth, wind field and radar parameters on the simulated sea surface roughness is quantitatively analyzed by means of control variables. In addition, an ideal model is established to explore the relationship between grid resolution and analog SAR images. The main achievements are as follows: (1) a 2 dimensional underwater radar imaging model for the Yangtze River estuary is built, which can simulate and radar at any time with complicated underwater topography. The bright and dark stripe appearing in the SAR image of the Yangtze River Estuary can not be explained by the traditional 1 dimensional radar imaging model. The 1 dimensional flow field model or radar imaging model will limit the imaging model to describe the complex underwater topography. Applying the 2 dimensional flow field model to the Changjiang Estuary, we can simulate the complex hydrodynamic environment in the estuary area and the variation of the flow field caused by the change of the water depth, which proves the reliability of the model. The sea surface is obtained by the simulation of flow convergence and divergence and SAR images of 2 dimensional irregular light and dark stripes coincides with the position of the input, through the wind and radar parameters, 2 dimensional radar imaging model simulated SAR images and measured ERS-2 and Sentinel-1 SAR image is more consistent, which indicates that this model has a more reliable terrain radar imaging ability under water, it also laid the foundation for the follow-up of different simulation parameters sensitivity analysis. (2) the main factors and conditions of underwater terrain radar imaging are simulated and analyzed, such as water depth, wind speed, wind direction and radar vision. Based on the established radar imaging model, the influence of water depth, wind speed, wind direction and radar direction on radar backscatter signal is simulated and compared by controlling variables. The results show that the surface roughness of the sea is less affected by the change of the total water depth, and is greatly influenced by the change of the slope of the underwater terrain. According to the results of comprehensive analysis, the downwind (or adverse wind) flow field, relatively low wind speed and the radar direction condition perpendicular to the wind direction are more suitable for shallow underwater terrain radar imaging. (3) the contribution of broken waves is considered in the underwater terrain radar imaging model. Input the same flow field data, and use different radar imaging models to simulate and compare the radar backscatter signals along the cross section of the underwater terrain slope, and compare them with the measured SAR images. The traditional two scale model underestimated the backscatter signal of radar, while the RIM model introduced by breaking wave contributed better in the amplitude and phase of simulation, especially in the case of larger incidence angle. (4) the influence of grid resolution on simulated SAR images is discussed and analyzed. Excluding the influence in the actual conditions of non seabed terrain factors using the ideal numerical model, simulation and analysis of sand water under different scales, different grid resolution of sea surface roughness. The results show that for small scale underwater Sandwaves (wavelength less than 100 meters), relative to the radar with high resolution grid of 10 meters of the simulated backscattering coefficient can reach more than 0.43 dB, indicating that in radar imaging for underwater terrain condition, SAR shadow image with high resolution capability of terrain detection scale under water. In the same underwater terrain, the enhancement of grid resolution can simulate a larger relative sea surface roughness. Compared with the result of high-resolution grid, the radar image obtained from low resolution grid computation is fuzzy, and it can not fully describe the exact geometry and the location of the underwater terrain. When the grid size reaches a certain threshold, the simulated radar backscattering coefficient will be stable, this shows that in the study of underwater terrain radar imaging, and wavelength grid spacing of sand under water reaches a certain proportion in order to fully describe the underwater sea surface topography caused by the roughness change. about
【學位授予單位】：華東師范大學
【學位級別】：博士
【學位授予年份】：2017
【分類號】：P715.5

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