發(fā)布時(shí)間：2018-09-07 19:34

【摘要】：本文以非合作運(yùn)動(dòng)目標(biāo)的分布式雷達(dá)成像為對(duì)象,以空間譜理論為基礎(chǔ),通過(guò)綜合考慮分布式系統(tǒng)的空間展開(kāi)特性、發(fā)射信號(hào)帶寬、目標(biāo)相對(duì)運(yùn)動(dòng)對(duì)成像的作用及其相互關(guān)系,重點(diǎn)開(kāi)展了以雙基地逆合成孔徑雷達(dá)(Bistatic Inverse Synthetic Aperture Radar, B-ISAR)為基本系統(tǒng)形式的運(yùn)動(dòng)目標(biāo)分布式雷達(dá)成像技術(shù)研究,主要工作如下： 首先,針對(duì)分布式雷達(dá)成像的基本單元——B-ISAR的特殊幾何構(gòu)型,提出了基于運(yùn)動(dòng)分解的回波建模方法,所建立的回波模型能夠解析的表達(dá)B-ISAR成像結(jié)果的幾何畸變、二維定標(biāo)因子與系統(tǒng)構(gòu)型及目標(biāo)運(yùn)動(dòng)之間的關(guān)系,從而將成像的畸變校正和定標(biāo)問(wèn)題轉(zhuǎn)化成了參數(shù)估計(jì)問(wèn)題。在此基礎(chǔ)上推導(dǎo)出了一般條件下目標(biāo)在三維空間中運(yùn)動(dòng)時(shí)B-ISAR的成像平面,并分析了距離-多普勒(Range-Doppler, RD)成像結(jié)果的幾何畸變與定標(biāo)特征,為后續(xù)章節(jié)的研究打下了基礎(chǔ)。 其次,利用目標(biāo)散射的稀疏先驗(yàn)信息,研究了壓縮感知在運(yùn)動(dòng)目標(biāo)分布式成像中的應(yīng)用,主要是兩個(gè)方面：1)針對(duì)B-ISAR的RD成像存在幾何畸變及二維無(wú)法直接定標(biāo)的問(wèn)題,提出了一種聯(lián)合幾何畸變校正及定標(biāo)的B-ISAR稀疏成像算法；2)提出了一種基于T/R-R (transmitter/receiver-receiver)構(gòu)型的運(yùn)動(dòng)目標(biāo)稀疏融合成像方法,以簡(jiǎn)單的系統(tǒng)構(gòu)型在短的相干處理時(shí)間內(nèi)實(shí)現(xiàn)了運(yùn)動(dòng)目標(biāo)的高分辨率稀疏成像。 第三,針對(duì)一般運(yùn)動(dòng)目標(biāo)的高分辨率成像問(wèn)題,提出了一種新的分布式成像構(gòu)型——多輸入單輸出ISAR (Multiple Input Single Output ISAR, MISO-ISAR),在獲得高分辨率的同時(shí)盡可能的簡(jiǎn)化了系統(tǒng)復(fù)雜度、提高了系統(tǒng)的抗干擾能力、機(jī)動(dòng)能力及生存能力,體現(xiàn)了高性能和可實(shí)用性的良好折中。 最后,在MISO-ISAR的基礎(chǔ)上,提出了基于運(yùn)動(dòng)接收機(jī)的三維成像方法,該方法利用一維的發(fā)射機(jī)陣列和運(yùn)動(dòng)的接收機(jī),即可實(shí)現(xiàn)運(yùn)動(dòng)目標(biāo)的三維成像,系統(tǒng)結(jié)構(gòu)簡(jiǎn)單實(shí)用性較強(qiáng)。
[Abstract]:In this paper, the distributed radar imaging of non-cooperative moving targets is taken as the object. Based on the spatial spectrum theory, the spatial expansion characteristics of the distributed system, the bandwidth of the transmitted signal, the effect of the relative motion of the target on the imaging and their mutual relations are considered synthetically. The research of distributed radar imaging technology with bistatic inverse synthetic aperture radar (Bistatic Inverse Synthetic Aperture Radar, B-ISAR) as the basic system is emphasized. The main work is as follows: first of all, Aiming at the special geometric configuration of B-ISAR, the basic unit of distributed radar imaging, an echo modeling method based on motion decomposition is proposed. The echo model can represent the geometric distortion of B-ISAR imaging results analytically. The relation between the two-dimensional calibration factor and the system configuration and the target motion, so the distortion correction and calibration problem of the imaging is transformed into the parameter estimation problem. On this basis, the imaging plane of B-ISAR is derived under general conditions, and the geometric distortion and calibration characteristics of range Doppler (Range-Doppler, RD) imaging results are analyzed, which lays a foundation for the study of the following chapters. Secondly, using the sparse prior information of target scattering, the application of compression sensing in distributed imaging of moving target is studied. There are two aspects: 1) the problem of geometric distortion in RD imaging of B-ISAR and the problem that two-dimensional image can not be directly calibrated. A B-ISAR sparse imaging algorithm combining geometric distortion correction and calibration is proposed. A sparse fusion imaging method for moving objects based on T/R-R (transmitter/receiver-receiver) configuration is proposed. The high resolution sparse imaging of moving targets is realized in a short coherent processing time with a simple system configuration. Thirdly, a new distributed imaging configuration, multiple input single output (ISAR (Multiple Input Single Output ISAR, MISO-ISAR), is proposed to solve the problem of high resolution imaging of moving targets, which simplifies the system complexity as much as possible while obtaining high resolution. It improves the anti-jamming ability, maneuverability and survivability of the system, and embodies a good compromise between high performance and practicability. Finally, on the basis of MISO-ISAR, a 3D imaging method based on motion receiver is proposed. This method uses one-dimensional transmitter array and moving receiver to realize 3D imaging of moving object. The system structure is simple and practical.
【學(xué)位授予單位】：中國(guó)科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN957.52

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 石光明;劉丹華;高大化;劉哲;林杰;王良君;;壓縮感知理論及其研究進(jìn)展[J];電子學(xué)報(bào);2009年05期

2 朱宇濤;郁文賢;粟毅;;一種基于MIMO技術(shù)的ISAR成像方法[J];電子學(xué)報(bào);2009年09期

3 李志林;陳后金;李居朋;姚暢;楊娜;;一種有效的壓縮感知圖像重建算法[J];電子學(xué)報(bào);2011年12期

4 董健;尚朝軒;高梅國(guó);傅雄軍;;雙基地ISAR成像平面研究及目標(biāo)回波模型修正[J];電子與信息學(xué)報(bào);2010年08期

5 吳曼青;;數(shù)字陣列雷達(dá)及其進(jìn)展[J];中國(guó)電子科學(xué)研究院學(xué)報(bào);2006年01期

6 楊建宇;;雷達(dá)技術(shù)發(fā)展規(guī)律和宏觀(guān)趨勢(shì)分析[J];雷達(dá)學(xué)報(bào);2012年01期

7 朱宇濤;粟毅;;一種M~2發(fā)N~2收MIMO雷達(dá)平面陣列及其三維成像方法[J];中國(guó)科學(xué):信息科學(xué);2011年12期

8 顧福飛;池龍;張群;羅迎;朱豐;;稀疏陣列L型MIMO雷達(dá)運(yùn)動(dòng)目標(biāo)三維成像方法[J];微波學(xué)報(bào);2012年03期

9 文再文;印臥濤;劉歆;張寅;;壓縮感知和稀疏優(yōu)化簡(jiǎn)介[J];運(yùn)籌學(xué)學(xué)報(bào);2012年03期

10 周萬(wàn)幸;;ISAR成像系統(tǒng)與技術(shù)發(fā)展綜述[J];現(xiàn)代雷達(dá);2012年09期

相關(guān)博士學(xué)位論文 前6條

1 徐浩;基于空間譜理論和時(shí)空兩維隨機(jī)輻射場(chǎng)的雷達(dá)成像研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2011年

2 朱宇濤;多通道ISAR成像技術(shù)研究[D];國(guó)防科學(xué)技術(shù)大學(xué);2011年

3 張冬晨;InISAR三維成像的關(guān)鍵技術(shù)研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2009年

4 謝曉春;壓縮感知理論在雷達(dá)成像中的應(yīng)用研究[D];中國(guó)科學(xué)院研究生院（空間科學(xué)與應(yīng)用研究中心）;2010年

5 張穎康;非合作目標(biāo)雷達(dá)高維感知相關(guān)算法的研究[D];北京交通大學(xué);2012年

6 徐建平;壓縮感知算法在雷達(dá)成像中的應(yīng)用研究[D];電子科技大學(xué);2012年

，

本文編號(hào)：2229213