基于GPU的SAR成像算法設計與實現(xiàn)
發(fā)布時間：2019-04-09 17:17
【摘要】：合成孔徑雷達(Synthetic Aperture Radar,簡稱SAR)是近幾十年發(fā)展起來的新型雷達,它可以不受光照、天氣的影響實現(xiàn)測繪區(qū)域內的二維高分辨率成像,SAR被廣泛應用在軍事、工業(yè),農(nóng)業(yè)、海洋探測、地質探測等領域。要對測繪帶進行成像,需要處理大量的回波數(shù)據(jù),SAR成像的實質就是利用信號處理的方法來處理這些數(shù)據(jù),從而獲取滿足要求的高分辨率圖像。SAR成像算法復雜,涉及大量的運算,傳統(tǒng)通過CPU進行SAR成像算法實現(xiàn)在實時性上越來越乏力,于是人們不斷地探求信號處理新技術來滿足實時性要求。自NVIDIA推出GPU(Graphic Processing Unit)以來,經(jīng)過十幾年的快速發(fā)展,GPU的使用范圍已不再局限于進行圖像處理與顯示,尤其是2007年NVIDIA推出基于CUDA(Compute Unified Device Archetecture)的新架構GPU,人們初步體驗到了GPU做高速并行計算的強大能力,在全球范圍內掀起了研究GPU算法提速科學運算的潮流。SAR的工作者們也察覺到了這一技術的優(yōu)勢,嘗試將SAR成像算法移植到GPU上,從而滿足自身需要,縮短成像時間。本文主要研究了GPU在SAR成像方面的應用,設計了基于GPU的SAR成像算法,利用GPU做并行計算的優(yōu)勢,縮短SAR成像時間,提高仿真系統(tǒng)的性能。本文主要涉及到的內容有:介紹了SAR成像原理,詳細的說明了如何通過脈沖壓縮技術來獲取高分辨率雷達圖像,給出了正側視模型下的二維頻域成像算法,給出了適用于前斜視與俯沖前斜的成像算法,并對這三種模型做了比較。介紹了GPU的技術特點,設計了基于GPU的SAR成像算法。設計了一個基于GPU的SAR成像仿真系統(tǒng),該系統(tǒng)在主控界面輸入雷達系統(tǒng)參數(shù)并啟動成像算法,最后將成像結果顯示在界面上。本論文的主要貢獻和創(chuàng)新是:(1)設計了方位向空變校正的前斜視SAR成像算法。(2)設計了方位向空變校正的俯沖段SAR成像算法。(3)設計了基于GPU的正側視、前斜視、俯沖段SAR成像算法。(4)設計了基于GPU的SAR成像結果測試系統(tǒng)。
[Abstract]:Synthetic Aperture Radar (Synthetic Aperture Radar,) is a new type of radar developed in recent decades. It can realize two-dimensional high-resolution imaging in mapping area without the influence of light and weather. SAR is widely used in military, industry and agriculture. Ocean exploration, geological exploration and other fields. It is necessary to process a large amount of echo data in order to image the mapping tape. The essence of SAR imaging is to process these data by means of signal processing, so as to obtain high-resolution images that meet the requirements. Involving a large number of operations, the traditional SAR imaging algorithm through CPU is less and less powerful in real-time performance, so people continue to explore new signal processing techniques to meet the real-time requirements. Since the introduction of GPU (Graphic Processing Unit) by NVIDIA, after more than ten years of rapid development, the scope of use of GPU is no longer limited to image processing and display, especially in 2007, NVIDIA launched a new CUDA (Compute Unified Device Archetecture)-based architecture, GPU, People have initially experienced the powerful ability of GPU to do high-speed parallel computing, and set off the trend of research on speed-up and scientific computing of GPU algorithm on a global scale. Sar workers are also aware of the advantages of this technology. This paper attempts to transplant the SAR imaging algorithm to the GPU, so as to meet its own needs and shorten the imaging time. This paper mainly studies the application of GPU in SAR imaging, designs the SAR imaging algorithm based on GPU, makes use of the advantage of GPU to do parallel computation, shortens the SAR imaging time, and improves the performance of the simulation system. The main contents of this paper are as follows: the principle of SAR imaging is introduced, how to obtain high-resolution radar image by pulse compression technique is explained in detail, and the two-dimensional frequency domain imaging algorithm based on forward and side-looking model is given. The imaging algorithms for forward strabismus and subduction forward squint are presented, and the three models are compared. The technical characteristics of GPU are introduced, and the SAR imaging algorithm based on GPU is designed. A SAR imaging simulation system based on GPU was designed. The system inputted the parameters of radar system at the main control interface and started the imaging algorithm. Finally, the imaging results were displayed on the interface. The main contributions and innovations of this thesis are as follows: (1) the forward squint SAR imaging algorithm for azimuth space variation correction is designed. (2) the SAR imaging algorithm for subduction segment is designed based on azimuth space variation correction. (3) the forward side view and forward squint view based on GPU are designed. Subduction segment SAR imaging algorithm. (4) A testing system of SAR imaging results based on GPU is designed.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN957.52
[Abstract]:Synthetic Aperture Radar (Synthetic Aperture Radar,) is a new type of radar developed in recent decades. It can realize two-dimensional high-resolution imaging in mapping area without the influence of light and weather. SAR is widely used in military, industry and agriculture. Ocean exploration, geological exploration and other fields. It is necessary to process a large amount of echo data in order to image the mapping tape. The essence of SAR imaging is to process these data by means of signal processing, so as to obtain high-resolution images that meet the requirements. Involving a large number of operations, the traditional SAR imaging algorithm through CPU is less and less powerful in real-time performance, so people continue to explore new signal processing techniques to meet the real-time requirements. Since the introduction of GPU (Graphic Processing Unit) by NVIDIA, after more than ten years of rapid development, the scope of use of GPU is no longer limited to image processing and display, especially in 2007, NVIDIA launched a new CUDA (Compute Unified Device Archetecture)-based architecture, GPU, People have initially experienced the powerful ability of GPU to do high-speed parallel computing, and set off the trend of research on speed-up and scientific computing of GPU algorithm on a global scale. Sar workers are also aware of the advantages of this technology. This paper attempts to transplant the SAR imaging algorithm to the GPU, so as to meet its own needs and shorten the imaging time. This paper mainly studies the application of GPU in SAR imaging, designs the SAR imaging algorithm based on GPU, makes use of the advantage of GPU to do parallel computation, shortens the SAR imaging time, and improves the performance of the simulation system. The main contents of this paper are as follows: the principle of SAR imaging is introduced, how to obtain high-resolution radar image by pulse compression technique is explained in detail, and the two-dimensional frequency domain imaging algorithm based on forward and side-looking model is given. The imaging algorithms for forward strabismus and subduction forward squint are presented, and the three models are compared. The technical characteristics of GPU are introduced, and the SAR imaging algorithm based on GPU is designed. A SAR imaging simulation system based on GPU was designed. The system inputted the parameters of radar system at the main control interface and started the imaging algorithm. Finally, the imaging results were displayed on the interface. The main contributions and innovations of this thesis are as follows: (1) the forward squint SAR imaging algorithm for azimuth space variation correction is designed. (2) the SAR imaging algorithm for subduction segment is designed based on azimuth space variation correction. (3) the forward side view and forward squint view based on GPU are designed. Subduction segment SAR imaging algorithm. (4) A testing system of SAR imaging results based on GPU is designed.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN957.52
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