【作者】 李军；

【导师】 胡飞；

【作者基本信息】 华中科技大学 ， 通信与信息系统， 2017， 博士

【摘要】 综合孔径辐射计采用稀疏排布的小孔径天线阵列合成等效的大孔径天线,能够实现瞬时、宽视场、高分辨率成像,避免了传统实孔径辐射计的大孔径天线加工困难以及需要机械扫描的不足。由于上述优势,自20世纪80年代末由射电天文引入对地遥感应用以来,综合孔径辐射测量相关技术与应用得到了极大的发展,以欧洲、美国和中国为首的主要国家或组织都在积极发展以综合孔径辐射计为载荷的卫星遥感观测计划。然而,已有研究表明微波辐射测量遭受了严重的射频干扰(Radio Frequency Interference,RFI)影响,这些射频干扰分布在多个频段,呈强点源辐射特征,通常来自于人为因素,能够淹没原始微波辐射信号,极大恶化了微波辐射测量应用。不同于实孔径辐射测量,由于宽视场以及有限空间频率采样导致成像结果的吉布斯(Gibbs)效应,射频干扰对综合孔径辐射计的恶化作用更为显著。针对当前微波辐射测量应用中面临的严重射频干扰源问题,本文在深入分析综合孔径辐射测量与一般天线阵列处理原理的基础上,提出基于虚拟天线阵的综合孔径辐射计成像方法。本文的主要工作概述如下:(1)在简要介绍微波辐射测量原理的基础上,推导了综合孔径干涉测量模型,分析了综合孔径成像基本原理。并基于综合孔径干涉测量和一般阵列处理的基本原理,从数学模型与等效阵列因子两方面重点研究了综合孔径干涉测量和一般阵列处理的统一数学框架。理论分析表明,基于一般阵列模型的空间匹配滤波数字波束形成方法等价于综合孔径辐射计测量可见度函数经过某个窗函数的傅里叶变换,其中该窗函数为天线阵列位置决定二维序列的自相关函数。因而可以得到,对于具有稀疏阵列排布的综合孔径辐射计,直接应用基于一般阵列处理模型的波束形成方法将导致恶化的成像性能。(2)针对已有综合孔径辐射计成像方法对应等效阵列因子特征(如零陷位置、零陷深度、旁瓣水平、主波束效率等)无法有效调整的不足,提出基于阵列因子综合的综合孔径辐射计成像方法。该方法建立了综合孔径辐射计与虚拟天线阵的等效数学模型,给出了综合孔径辐射计阵列因子的一般表达,并由此提出了基于权向量范数最小化和旁瓣水平最小化的阵列因子综合方法。此外,进一步分析了提出阵列因子综合方法与传统窗函数的数学关系,并由此提出了权向量标度化的必要性。理论分析表明,在一定的条件下,本文提出的方法可以等价于A.Camps等人先前提出的方法以及经典傅里叶方法。最后,通过仿真分析和欧空局SMOS卫星实测数据证实了本文提出方法的有效性,并定性和定量地评估了本文提出方法对SMOS射频干扰源的缓解性能。SMOS射频干扰源缓解实验结果表明:由于SMOS系统存在的残余校正误差,基于权向量范数最小化模型的阵列因子综合方法能有效地缓解中等或较弱强度的射频干扰源;而针对强射频干扰源,在损失空间分辨率的代价下,基于旁瓣水平最小化模型的阵列因子综合方法具有更好的射频干扰源缓解性能。(3)基于综合孔径辐射计的稀疏阵列排布特点,提出了基于增广协方差矩阵的射频干扰源定位方法。该方法将具有稀疏阵列的综合孔径辐射计等效为具有更多阵元的虚拟全填充阵,分析了典型综合孔径辐射计阵列(如U、T、Y和六边形阵等)的虚拟全填充阵模型,研究了由原始测量可见度函数实现虚拟填充阵增广协方差矩阵构造的方法,并以MUSIC算法为例,提出了基于增广协方差矩阵的高分辨率射频干扰源定位方法。针对SMOS射频干扰源定位应用,具体分析了SMOS Y形阵的虚拟全填充阵构造方法,并通过实测SMOS数据证实了提出方法的有效性。实测SMOS数据实验结果表明,在与先前方法具有可比较的定位精度条件下,提出方法的射频源定位结果具有更好的空间分辨率、更小的旁瓣或拖尾效应以及最大的可辨识射频源个数等优势。此外,针对辐射场景成像应用,进一步研究了基于增广协方差矩阵的数字波束形成方法,并通过华中科技大学综合孔径辐射计HUST-ASR原型样机实验证实了提出方法的有效性。(4)基于射频干扰源的空间稀疏分布特性,提出了基于压缩感知的射频干扰源定位方法。基于综合孔径辐射计的虚拟天线阵模型,结合射频干扰源的空间稀疏分布特性,提出了基于?1范数最小化和重加权?1范数最小化的射频干扰源定位方法,并分析了该方法涉及正则化参数选取以及相关器损坏或接收机失效条件下的射频干扰源定位问题。仿真分析和实测SMOS数据实验结果证实了提出方法的有效性。更多还原

【Abstract】 Synthetic aperture interferometric radiometer(SAIR)can synthesis a large aperture by sparsely arranging a number of small aperture antennas to achieve high spatial resolution imaging with a wide instantaneous field-of-view(FOV)and without requiring very large and massive mechanical scanning antenna.Because of these advantages,since SAIR is introduced from radio astronomy to the Earth observation,the technique and application of SAIR are developing very fast,and increasing interests for spaceborn missions are being observed in the last decades,especially for the teams from Europe,USA and China.However,it has been shown that radio frequency interference(RFI)sources present in many microwave radiometry bands and many areas of the world due to the presence of wireless device,which dramatically degrades the performance for the retrieve of geophysical parameters.Compared with real aperture radiometry,RFI is even more serious for SAIR because of the large FOV and the Gibbs-like contamination in the brightness temperature(BT)images from the limited spatial frequency coverage of a SAIR instrument.In this dissertation,in order to reduce the severe degradation effects of RFIs,based on the further analysis for the relationship between the interferometric radiometry and the general array processing,the imaging method of synthetic aperture interferometric radiometry based on virtual antenna arrays is proposed.The main contents of this dissertation are given as follows.(1)After briefly introducing the basis concept of microwave radiometry,and formulating the principles of synthetic aperture interferometric radiometry,further analysis on the unified mathematical framework between the SAIR and the general array processing are presented from the aspects of the system model and equivalent array factor.It is shown that digital beamforming of spatial match filtering based on the general array processing model is equivalent to the discrete Fourier transform of measured visibilities in SAIR with a certain window function,which is the autocorrelation function for the binary series determined by the antenna array placement.Then,the results of SAIR imaging by directly using digital beamforming will degenerate due to the sparse array configuration of SAIR.(2)An imaging method with array factor synthesis in synthetic aperture interferometric radiometers is proposed,which can efficiently control the characteristics of the equivalent array factor of SAIR,such as null position and depth,sidelobe level,mainlobe efficiency and so on.First,the theoretical formulation is established that the SAIR array is equivalent to a virtual antenna array.Then,two types of optimization problems of the array factor synthesis are presented: weight vector norm minimization and sidelobe level minimization.Finally,it is shown that the presented method can be viewed as a specific window with a conjugate symmetry property,and a resulting weight vector scaling is presented to correct the inverse BT.In particular,it is also shown that,in some special case,the presented method is equivalent to the built-in method proposed by A.Camps recently and the conventional inverse discrete Fourier transform(IDFT)method.Simulation results and real SMOS data experiments validate the effectiveness of the presented method.In addition,RFI mitigation results for SMOS applications show that,for the approach of array factor synthesis of weight vector norm minimization,weak and moderate RFIs can be mitigated very well,but it is not enough effective for strong RFIs due to residual calibration errors.On the other hand,for strong RFIs,at the cost of spatial resolution degradation,result shows the approach of sidelobe level minimization can be effective to mitigate strong RFIs.(3)A novel RFI localization approach using covariance matrix augmentation in SAIR is proposed.The proposed approach utilizes the property of the sparse array configuration which is commonly used in SAIR,where the sparse array can be viewed as a virtual filled array with much larger number of antenna elements.The virtual filled arrays of several typical sparse SAIR array geometries(such as,U-,T-,Y-and hexagonal array)are discussed,the construction of the augmented covariance matrix for the virtual filled array is presented,and a typical Direction-of-Arrival estimation approach using MUltiple SIgnal Classification(MUSIC)algorithm based on the augmented covariance matrix is employed for RFI localization.The proposed approach can be applied in SAIR with a sparse array configuration,such as the European Space Agency(ESA)Soil Moisture and Ocean Salinity(SMOS)mission.Results on real SMOS data show that,compared with the classical MUSIC algorithm,the presented approach has an improved performance of RFI localization with comparable accuracy,such as improved spatial resolution,lower sidelobes and larger identifiable number of RFI sources.In addition,for the natural scene imaging application,the digital beamforming method based on augmented covariance matrix is also presented for SAIR.Experiment results of Huazhong University of Science and Technology Aperture Synthesis Radiometer(HUST-ASR)show that,compared with the digital beamforming based on the direct covariance matrix,the presented approach shows a significantly improved imaging performance with respect to the spatial resolution.(4)Utilizing the sparse property of RFI in the observed scene,a high resolution RFI localization method based on compressive sensing is presented in SAIR.The proposed approach is based on the model that SAIR can be understood as a virtual array with a virtual antenna element located in each baseline.When the scene brightness temperature is viewed as a background noise,the RFI sources that we desire to recover are sparse in the spatial domain.Based on the fact,the ?1-norm minimization and reweighted ?1-norm minimization are proposed to enforce the sparsity of the desired RFI sources,and the approach for the choosing of the regularization parameter are also presented.Numerical results show the presented method can achieve super-resolution for RFI localization even when there are some missing data due to correlator or receiver failures.更多还原