方位多相位中心SAR高分辨率寬測繪帶成像技術(shù)研究
發(fā)布時間：2018-09-14 11:04
【摘要】：合成孔徑雷達(SAR)以其全天候、全天時獲取高分辨二維地表圖像的能力已經(jīng)成為一種不可或缺的空間對地遙感手段,無論是在災(zāi)害監(jiān)測、海洋測繪等民用領(lǐng)域還是在廣域偵察、艦船檢測等軍事領(lǐng)域,都受到了高度的的重視并得到了廣泛的應(yīng)用。受制于系統(tǒng)固有約束,常規(guī)星載SAR系統(tǒng)不能滿足現(xiàn)代空間對地觀測任務(wù)所提出的連續(xù)高分辨率寬測繪帶(HRWS)成像需求。采用沿航向分布的多通道接收,方位多相位中心(AMPC)SAR系統(tǒng)能夠在低脈沖重復(fù)頻率(PRF)工作條件下獲得方位向的高分辨率,從而實現(xiàn)連續(xù)HRWS成像。立足于HRWS成像應(yīng)用需求,圍繞AMPC SAR數(shù)據(jù)處理與系統(tǒng)性能分析難點,對信號建模與重建、系統(tǒng)性能分析、陣列誤差建模與校正以及AMPC SAR模式拓展等關(guān)鍵技術(shù)展開研究,主要內(nèi)容與創(chuàng)新點總結(jié)如下:第二章對AMPC SAR內(nèi)在原理與信號模型進行闡述。通過對品質(zhì)因子與最小天線面積的分析,揭示出AMPC SAR系統(tǒng)的本質(zhì)在于通過對傳統(tǒng)單天線陣面進行重新配置并結(jié)合方位向數(shù)字波束形成(DBF)技術(shù)實現(xiàn)HRWS觀測,付出的代價是系統(tǒng)靈敏度的損失,但是并未克服最小天線面積約束。通過對空間采樣特性的分析,給出了廣義上的均勻采樣PRF表達式,并給出了基于DPCA方法重建后的等效PRF表達式。第三章對AMPC SAR信號重建與性能分析兩方面問題展開研究。囿于信號模型的局限,常規(guī)信號重建方法只能對寬度為整數(shù)倍PRF的雜波譜進行重建,從而導(dǎo)致重建性能在特殊PRF條件下的極度惡化,進而對系統(tǒng)參數(shù)設(shè)計提出了嚴(yán)格的要求。本文建立了修正回波譜模型,將重建信號帶寬這一重要處理參數(shù)擴展至任意值而非局限于整數(shù)倍的PRF,顯著提升常規(guī)信號重建方法的穩(wěn)健性,顯著提高了系統(tǒng)參數(shù)設(shè)計的自由度。基于修正回波譜模型建立了AMPC SAR信號重建的統(tǒng)一DBF處理框架,在此框架下對一系列信號重建方法的重建性能進行分析與比較,從而為信號重建方法優(yōu)選與系統(tǒng)參數(shù)設(shè)計提供有力支撐。第四章對陣列誤差建模與校正問題展開研究。將通道響應(yīng)誤差與相位中心位置誤差統(tǒng)一建模為陣列的沿航位置誤差、幅度誤差和相位誤差,指出相位中心位置誤差將引入較大的相位誤差,而該相位誤差又與下視角緊密相關(guān),從而呈現(xiàn)出空變特性。基于雜波功率譜的衰減特性,提出了一種新的陣列誤差估計方法,該方法將雜波譜兩側(cè)區(qū)間的功率與雜波譜中心區(qū)間的功率的比值作為優(yōu)化目標(biāo),得到了穩(wěn)健的誤差估計性能。提出修正正交子空間方法,可在通道數(shù)較少條件下也能基于信號子空間與噪聲子空間的正交性獲得穩(wěn)健的誤差估計性能。提出基于陣列誤差模型的相位誤差擬合方法,可實現(xiàn)對AMPC SAR數(shù)據(jù)中存在的空變性相位誤差進行快速估計與高精度校正。第五章對基于AMPC體制的雙指向SAR(BiDi-SAR)成像技術(shù)展開研究。單通道BiDi-SAR對系統(tǒng)PRF有著嚴(yán)苛的要求。本文提出AMPC BiDi-SAR觀測模式,并提出了基于LS算法的頻譜分離方法,可顯著降低系統(tǒng)對PRF的嚴(yán)苛要求,顯著提高了BiDi-SAR系統(tǒng)觀測能力與系統(tǒng)設(shè)計自由度。仿真實驗與實測數(shù)據(jù)處理結(jié)果驗證了相關(guān)理論分析的正確性以及本文所提信號處理方法的有效性,從而為面向HRWS應(yīng)用的AMPC SAR系統(tǒng)參數(shù)設(shè)計與實測數(shù)據(jù)處理提供有力支撐。
[Abstract]:Synthetic Aperture Radar (SAR) has become an indispensable means of space-to-ground remote sensing because of its ability to acquire high-resolution two-dimensional surface images all-weather and all-time. It has been highly valued and widely used in civil areas such as disaster monitoring, marine surveying and mapping, wide-area reconnaissance, ship detection and other military fields. Constrained by the inherent constraints of the system, conventional spaceborne SAR systems can not meet the requirements of continuous high resolution and wide mapping band (HRWS) imaging proposed by modern space-to-Earth observation missions. With multi-channel reception along the course distribution, the azimuth multi-phase center (AMPC) SAR system can obtain a square under low pulse repetition rate (PRF) operating conditions. Based on the requirement of HRWS imaging application, the key technologies of signal modeling and reconstruction, system performance analysis, array error modeling and calibration, and AMPC SAR mode expansion are studied around the difficulties of data processing and system performance analysis of AMPC SAR. In the second chapter, the intrinsic principle and signal model of AMPC SAR are described. By analyzing the quality factor and the minimum antenna area, it is revealed that the essence of AMPC SAR system is to reconfigure the traditional single antenna array and realize the HRWS observation by combining the azimuth digital beamforming (DBF) technology. The cost is the sensitivity of the system. By analyzing the characteristics of spatial sampling, the generalized uniform sampling PRF expression is given, and the equivalent PRF expression based on DPCA reconstruction is given. In the third chapter, the problems of AMPC SAR signal reconstruction and performance analysis are studied. The conventional signal reconstruction method can only reconstruct the clutter spectrum whose width is integer times of PRF, which leads to the extreme deterioration of the reconstructed performance under special PRF conditions. Therefore, strict requirements are put forward for the system parameter design. A modified echo spectrum model is established to extend the reconstructed signal bandwidth to arbitrary values rather than local. Limited to integer multiple PRF, the robustness of conventional signal reconstruction methods is improved and the degree of freedom of system parameter design is improved significantly. A unified DBF processing framework for AMPC SAR signal reconstruction is established based on modified echo spectrum model. Under this framework, the reconstruction performance of a series of signal reconstruction methods is analyzed and compared, so as to achieve signal weight. In Chapter 4, the modeling and correction of array errors are studied. The channel response error and the phase center position error are modeled as the yaw position error, amplitude error and phase error of the array. It is pointed out that the phase center position error will lead to larger phase error. Based on the attenuation characteristics of clutter power spectrum, a new array error estimation method is proposed, which takes the ratio of the power at both sides of the clutter spectrum to the power at the center of the clutter spectrum as the optimization objective and obtains robust error estimation performance. The modified orthogonal subspace method can obtain robust error estimation performance based on the orthogonality of signal subspace and noise subspace under the condition of fewer channels. A phase error fitting method based on array error model is proposed to estimate the spatially varying phase errors in AMPC SAR data quickly and accurately. Chapter 5 is devoted to the study of dual-directional SAR (BiDi-SAR) imaging technology based on AMPC. Single-channel BiDi-SAR has strict requirements for PRF. In this paper, AMPC BiDi-SAR observation mode is proposed, and a spectrum separation method based on LS algorithm is proposed, which can significantly reduce the severe requirements of PRF and significantly improve the observation of BiDi-SAR system. The simulation and experimental data processing results verify the correctness of the relevant theoretical analysis and the validity of the signal processing method proposed in this paper, thus providing a strong support for HRWS-oriented AMPC SAR system parameter design and real-time data processing.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN958
本文編號：2242519
[Abstract]:Synthetic Aperture Radar (SAR) has become an indispensable means of space-to-ground remote sensing because of its ability to acquire high-resolution two-dimensional surface images all-weather and all-time. It has been highly valued and widely used in civil areas such as disaster monitoring, marine surveying and mapping, wide-area reconnaissance, ship detection and other military fields. Constrained by the inherent constraints of the system, conventional spaceborne SAR systems can not meet the requirements of continuous high resolution and wide mapping band (HRWS) imaging proposed by modern space-to-Earth observation missions. With multi-channel reception along the course distribution, the azimuth multi-phase center (AMPC) SAR system can obtain a square under low pulse repetition rate (PRF) operating conditions. Based on the requirement of HRWS imaging application, the key technologies of signal modeling and reconstruction, system performance analysis, array error modeling and calibration, and AMPC SAR mode expansion are studied around the difficulties of data processing and system performance analysis of AMPC SAR. In the second chapter, the intrinsic principle and signal model of AMPC SAR are described. By analyzing the quality factor and the minimum antenna area, it is revealed that the essence of AMPC SAR system is to reconfigure the traditional single antenna array and realize the HRWS observation by combining the azimuth digital beamforming (DBF) technology. The cost is the sensitivity of the system. By analyzing the characteristics of spatial sampling, the generalized uniform sampling PRF expression is given, and the equivalent PRF expression based on DPCA reconstruction is given. In the third chapter, the problems of AMPC SAR signal reconstruction and performance analysis are studied. The conventional signal reconstruction method can only reconstruct the clutter spectrum whose width is integer times of PRF, which leads to the extreme deterioration of the reconstructed performance under special PRF conditions. Therefore, strict requirements are put forward for the system parameter design. A modified echo spectrum model is established to extend the reconstructed signal bandwidth to arbitrary values rather than local. Limited to integer multiple PRF, the robustness of conventional signal reconstruction methods is improved and the degree of freedom of system parameter design is improved significantly. A unified DBF processing framework for AMPC SAR signal reconstruction is established based on modified echo spectrum model. Under this framework, the reconstruction performance of a series of signal reconstruction methods is analyzed and compared, so as to achieve signal weight. In Chapter 4, the modeling and correction of array errors are studied. The channel response error and the phase center position error are modeled as the yaw position error, amplitude error and phase error of the array. It is pointed out that the phase center position error will lead to larger phase error. Based on the attenuation characteristics of clutter power spectrum, a new array error estimation method is proposed, which takes the ratio of the power at both sides of the clutter spectrum to the power at the center of the clutter spectrum as the optimization objective and obtains robust error estimation performance. The modified orthogonal subspace method can obtain robust error estimation performance based on the orthogonality of signal subspace and noise subspace under the condition of fewer channels. A phase error fitting method based on array error model is proposed to estimate the spatially varying phase errors in AMPC SAR data quickly and accurately. Chapter 5 is devoted to the study of dual-directional SAR (BiDi-SAR) imaging technology based on AMPC. Single-channel BiDi-SAR has strict requirements for PRF. In this paper, AMPC BiDi-SAR observation mode is proposed, and a spectrum separation method based on LS algorithm is proposed, which can significantly reduce the severe requirements of PRF and significantly improve the observation of BiDi-SAR system. The simulation and experimental data processing results verify the correctness of the relevant theoretical analysis and the validity of the signal processing method proposed in this paper, thus providing a strong support for HRWS-oriented AMPC SAR system parameter design and real-time data processing.
【學(xué)位授予單位】：國防科學(xué)技術(shù)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN958
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