基于模糊推理的SAR干扰效果评估

对SAR干扰效果的评估是目前的一个研究热点。在依据SAR图像受干扰情况评估SAR干扰效果的过程中,人的主观因素占主导地位。对于这种不确定性的评判,该文介绍了一种基于模糊推理的SAR干扰效果评估方法。首先,建立了SAR干扰效果评估指标;接着,借助相关领域专家的经验知识和推理规则,采用定性与定量相结合的方法,建立了模糊推理数学模型;最后,利用所建立的指标和模型进行干扰效果综合评判,得到了合理的、令人满意的结果。     

基于DPCA的机载SAR系统运动误差及其补偿

基于相位中心偏置天线（DPCA）技术的机栽SAR系统在实际运用中普遍存在着因雷达平台运动不稳定导致DPCA约束条件不满足的问题,这在很大程度上影响了机载SAR系统的杂波抑制性能。针对这个问题,该文以双天线机载SAR系统为模型,通过对DPCA的对消原理和运动误差的分析,结合插值理论,对载机匀加速运动状态下造成的运动误差提出了一种基于三次样条函数的运动补偿算法。通过计算机仿真,验证了该算法的有效性,且算法易于工程实现。     

合成孔径雷达的有源欺骗干扰方法研究

本文根据SAR成像原理和地面回波信号模型,提出了对SAR进行有源欺骗干扰的方法.文中详细地讨论了有源干扰的基本原理,分析了干扰信号模型,并用实际SAR数据进行了仿真实验,欺骗图像成功加到了真实SAR图像中.     

速度与PRF失配对MPCSAR成像的影响及补偿方法研究

简述了多相位中心合成孔径雷达(MPCSAR)原理及其空时不等效的研究现状,对平台速度与脉冲重复频率(PRF)失配引起的成对回波虚像进行了深入研究,从数学上严格推导了成对回波的位置,分析了两种虚像 (欠采样虚像及失配虚像)的形成机理.论文还提出了在频域进行相位补偿以消除这种成对回波虚像的简单方法.给出的仿真实例验证了本文的结果.     

基于提升方向波变换域的SAR图像压缩

提出了一种基于提升方向波变换SAR图像的压缩算法.该算法构造了方向波变换的提升方案,通过改进的四叉树分块算法寻找局部最优的变换方向,有效地描述了图像中的方向特征.根据变换系数分布特性构造了多方向各向异性的多级零树结构,提高了编码效率.对多幅SAR图像的压缩实验表明,较之基于小波的SPIHT和JPEG2000等算法,本文方法在性能指标和视觉效果方面均得到了明显提高,尤其在低比特率下,优势更加突出.     

基于两时相图像联合分类的SAR图像变化检测

传统分类后比较法(post-classification comparison,PCC)存在分类累积误差问题,且对单幅图像分类精度要求较高,对此,根据不同时相图像的不变信息所具有的相关性,提出了一种基于两时相图像联合分类的SAR图像变化检测方法.该方法以灰度值作为输入信息,通过相似度计算可得两时相图像对应位置像素的灰度相似度,然后求解全局相似度阈值,并用于控制基于K-均值的联合分类器对两时相图像进行联合分类,最后通过类别比较获得变化检测结果.实验结果表明本文方法不但可提高单幅图像的分类精度,而且能够精确地把不同时相图像的不变地物信息划分为同一类别,减少了分类累积误差的影响,提高了变化检测性能.     

Pipeline of Successive Approximation Converters with Optimum Power Merit Factor

In this paper, we present a low power 12 bit 5 MSPS, successive approximation converter architecture using pipeline technique. The converter consumes 4 mW at the Nyquist rate input with 1.8 V power supply. By combination of pipeline and successive architecture, the entire circuit, simulated at the transistor level in a 0.18 μ CMOS process, achieves a FoM (Figure of Merit) of 0.19 pJ/conversion. Jinghua Li was born in 1973. He received the MSEE and BSEE Degree from College of Electronics and information, Shanghai Jiaotong University and Harbin Engineering University in 1997 and 1994 respectively. He is currently pursuing Ph.D degree in Department of Electrical Engineering, Texas A&M University, College Station, TX, USA. In 1997, he joined Bell Laboratory (China), Lucent Technologies as a member of technical staff. He worked on single-chip HDTV decoder IC and Sonet/SDH SoC for various projects in Murray Hill, NJ, USA and Shanghai China. He also finished projects on hardware implementation of Video conference/Phone based on H.263 standard as his master thesis. Since 2000, he has been a research assistant in Analog Mixed Signal center, TAMU. Most currently his research interests are focused on low power analog to digital conversion IC design, CMOS implementation of 10 G/2.5 G clock data recovery IC for high speed serial communications. Franco Maloberti received the Laurea Degree in Physics (Summa cum Laude) from the University of Parma, Parma Italy, in 1968 and the Dr. Honoris Causa degree in electronics from the Instituto Nacional de Astrofisica, Optica y Electronica (Inaoe), Puebla, Mexico in 1996. In 1993 he was a Visiting Professor at ETH-PEL, Zurich. He was Professor of Microelectronics and Head of the Micro Integrated Systems Group University of Pavia, Pavia, Italy and the TI/J.Kilby Analog Engineering Chair Professor at the Texas A&M University. He is currently the Distinguished Microelectronic Chair Professor at University of Texas at Dallas and part-time Professor at the University of Pavia, Italy. His professional expertise is in the design, analysis and characterization of integrated circuits and analogue digital applications, mainly in the areas of switched capacitor circuits, data converters, interfaces for telecommunication and sensor systems, and CAD for analogue and mixed A-D design. He has written more than 250 published papers, three books and holds 15 patents. He was in 1992 recipient of the XII Pedriali Prize for his technical and scientific contributions to national industrial production. He was co-recipient of the 1996 Institute of Electrical Engineers (U.K.) Fleming Premium for the paper “CMOS Triode Transistor Transconductor for high-frequency continuous time filters.” He has been responsible at both technical and management levels for many research programs including ten ESPRIT projects and has served the European Commission as ESPRIT Projects' Evaluator, Reviewer and as European Union expert in many European Initiatives. He served the Academy of Finland on the assessment of electronic research in Academic institutions and on the research programs' evaluations. Dr. Maloberti was Vice-President, Region 8, of the IEEE Circuit and Systems Society from 1995 to 1997 and an Associate Editor of IEEE-Transaction on Circuit and System-II. He received the 1999 IEEE CAS Society Meritorious Service Award, the 2000 CAS Society Golden Jubilee Medal, and the IEEE Millenium Medal. He is the President of the IEEE Sensor Council and member of the Board of Governors of the IEEE CAS Society. He is a member of the Italian Electrothecnical and Electronic Society (AEI), the Editorial Board of Analog Integrated Circuits and Signal Processing, and Fellow of IEEE.     

基于邻域信息的SAR图像变化检测

为了减少合成孔径雷达(SAR)图像中乘性斑点噪声对变化检测结果的影响,充分地利用了像素的邻域信息。首先使用邻域比值(NR)方法构造差异图像,然后提出基于邻域信息的模糊C均值聚类(FCM)算法。NR算子在构造差异图像时能够较好地保留图像信息并抑制噪声的干扰。同时将邻域信息引入到FCM算法的目标函数,以邻域加权距离改进了FCM算法在欧式距离计算中的不足,并约束了隶属度函数,减少了噪声对邻域中心像素的干扰。通过以上考虑像素邻域信息的算法,得到了差异图像的聚类结果,从而实现了SAR图像的变化检测。实验结果表明,所提算法较传统的FCM和K-means聚类算法,可以较好地保留图像变化区域的信息,同时提高了SAR图像变化检测的准确度。     

星载SAR方位模糊研究

本文根据方位模糊产生机理详细分析了方位向成像处理参数、波长、方位方向图副瓣对方位模糊的影响.通过分析可知:方位分辨率相同时,低频段SAR系统模糊问题更严重,但可通过提高重频、压低方向图副瓣电平等方法可改善方位模糊,最后仿真验证了上述结论并给出改善方位模糊的设计考虑.     

多方位高分辨率SAR的三维目标自动重建(一)目标像的检测

用多方位SAR图像融合获取立体目标信息是高分辨率SAR的一项关键应用技术.以t长方体为建筑物目标模型,提出从多方位米级分辨率SAR图像自动重建三维立体建筑物目标的方法.全文分两部分,第一部分介绍从米级分辨率SAR图像检测提取建筑物目标像的方法.先用恒虚警率(CFAR)检测器检测各方位SAR图像中建筑物目标像的边缘,然后用脊滤波细化边缘,再根据条状建筑物像的直线特征,用分块平行线Hough变换检测平行线段,最终检测得到平行四边形的建筑物目标像.文中用虚拟场景模拟的SAR图像和机载全极化X波段Pi-SAR图像做试验,提取了建筑物目标像.第二部分以本文为基础进行三维建筑物目标群的重建.