本文選題：SAR成像 + GPU��； 參考：《南京理工大學(xué)》2017年碩士論文

【摘要】：合成孔徑雷達(dá)(SAR)不受時(shí)間、天氣、地域等因素的影響,可以全天候工作,作用距離遠(yuǎn),廣泛應(yīng)用于目標(biāo)探測(cè)、識(shí)別和定位,戰(zhàn)場(chǎng)偵察監(jiān)視,自然災(zāi)害預(yù)報(bào),資源勘探等軍事和民用領(lǐng)域。SAR可以獲得高分辨圖像,但是成像算法復(fù)雜,需要處理大量的回波數(shù)據(jù),運(yùn)算量非常大,對(duì)硬件平臺(tái)提出了很高的要求。本文針對(duì)星載SAR在軌成像處理的應(yīng)用需求,開(kāi)展了 SAR快速成像、目標(biāo)檢測(cè)與成像評(píng)估方法的研究,主要內(nèi)容包括:(1)分析了星載SAR信號(hào)處理系統(tǒng)的設(shè)計(jì)因素,給出了一種以嵌入式GPU為核心的星載SAR信號(hào)處理系統(tǒng),分析了 GPU并行處理效率,探討了 CUDA平臺(tái)的編程模型及存儲(chǔ)模型。(2)詳細(xì)討論了 SAR回波模型,設(shè)計(jì)了 SAR回波信號(hào)存儲(chǔ)方式;針對(duì)Chirp Scaling(CS)成像算法進(jìn)行了并行處理的結(jié)構(gòu)優(yōu)化;針對(duì)NVIDIA GPU信號(hào)處理平臺(tái),設(shè)計(jì)了 CS成像算法并行程序;實(shí)驗(yàn)結(jié)果表明,相對(duì)于CPU平臺(tái),該系統(tǒng)取得了幾十甚至幾百倍的加速比。(3)針對(duì)雙參數(shù)CFAR算法進(jìn)行了相應(yīng)的并行處理結(jié)構(gòu)優(yōu)化,設(shè)計(jì)了雙參數(shù)CFAR算法的并行程序。利用真實(shí)的艦船SAR圖像進(jìn)行了驗(yàn)證,實(shí)驗(yàn)結(jié)果表明該方法目標(biāo)檢測(cè)準(zhǔn)確,與CPU平臺(tái)進(jìn)行對(duì)比,加速比達(dá)到了 400以上。(4)詳細(xì)討論了 SAR圖像質(zhì)量客觀評(píng)價(jià)指標(biāo),利用C#設(shè)計(jì)了 SAR圖像質(zhì)量客觀評(píng)價(jià)的GUI測(cè)試軟件,并對(duì)本文給出的星載SAR快速成像平臺(tái)、傳統(tǒng)CPU成像平臺(tái)所成SAR圖像質(zhì)量進(jìn)行了對(duì)比分析。
[Abstract]:The synthetic Aperture Radar (SAR), which is not affected by time, weather, region and other factors, can work around the clock and has a long range of functions. It is widely used in target detection, identification and positioning, battlefield reconnaissance and surveillance, and natural disaster prediction. High resolution images can be obtained from SAR in military and civil fields such as resource exploration, but the imaging algorithms are complex and need to deal with a large amount of echo data. In order to meet the requirements of spaceborne SAR imaging processing in orbit, this paper studies the methods of SAR fast imaging, target detection and imaging evaluation. The main content of this paper is to analyze the design factors of spaceborne SAR signal processing system. A space-borne SAR signal processing system based on embedded GPU is presented. The efficiency of GPU parallel processing is analyzed. The programming model and storage model of CUDA platform are discussed. The SAR echo model is discussed in detail. The storage mode of SAR echo signal is designed, the structure of parallel processing is optimized for Chirp scaling CSC imaging algorithm, the parallel program of CS imaging algorithm is designed for NVIDIA GPU signal processing platform, and the experimental results show that, compared with CPU platform, a parallel program for CS imaging algorithm is designed. The system achieves a speedup ratio of several tens or even hundreds of times. The parallel processing structure of the two-parameter CFAR algorithm is optimized and the parallel program of the two-parameter CFAR algorithm is designed. The real ship SAR image is used to verify the method. The experimental results show that the method is accurate and compared with CPU platform. The speedup ratio is more than 400. 4) the objective evaluation index of SAR image quality is discussed in detail. The GUI test software for objective evaluation of SAR image quality is designed by using C #, and the SAR image quality of Spaceborne SAR fast imaging platform and traditional CPU imaging platform is compared and analyzed in this paper.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN957.52

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