A charge sharing–based switching scheme for SAR ADCs

This paper presents an energy-efficient switching scheme for successive approximation register (SAR) analogue-to-digital converter (ADC). The proposed scheme employs charge recycling method to keep the capacitor arrays free of transitional energy between bit generations except reset phase. In comparison with the conventional switching scheme, the proposed one achieves 100% transitional energy saving without considering reset phase. In addition, configuration of a 10-bit SAR ADC shows that the proposed switching scheme reduces the capacitor area by 25% compared with the conventional switching scheme.     

基于两层均匀媒质的GPEN SAR地下目标成像方法及其性能分析

地表穿透合成孔径雷达(Ground PENetration SAR,GPEN SAR)为了探测掩埋在地下的目标,通常工作在多层媒质的环境中。传统成像模型是建立在同一均匀媒质的假设上,不再适合于GPEN SAR的实际情况。本文首先建立了两层分区均匀媒质中的成像模型,然后利用后向投影(BP)算法定量分析了成像几何参数、土壤参数等对成像的影响,进而提出了一种修正的后向投影(MBP)算法。MBP算法不仅能够校正两层分区均匀媒质对成像定位的影响,还能估计目标的掩埋深度,提供目标三维位置坐标。仿真结果验证了MBP算法在不同信噪比环境下,对多目标的三维定位精度能满足实际的需要。     

基于扩展分形和CFAR特征融合的SAR图像目标识别

研究了多信息融合技术在SAR图像目标识别中的应用。将扩展分形特征(Extended Fractal)与双参数恒虚警特征(Double Parameter CFAR)形成的多信息进行融合处理。运用Dempster-Shafer证据理论，在决策层对SAR图像中的像素进行识别分类。实验结果表明通过融合对像素分类的准确性明显好于单特征的检测结果，减少了虚警概率，提高了系统的识别能力。     

合成孔径雷达（SAR）的最新发展

全文分若干单元分别论述了机载2D-SAR自聚焦技术，降低斑点技术，MTI-SAR和3D-SAR（含机载和空载），对上述各种SAR分别讨论了工作原理，列出了多个实例以及应用情况。     

干涉条纹图估测基线的方法研究

根据SAR干涉测量原理，提出了利用干涉相干条纹估测基线的方法，并以欧洲空间局资源卫星1号和2号携带的SAR系统在中国新疆伽师试验区获取的串接式（Tan-dem）干涉测量数据为数据源，对提出的方法进行了验证，结果表明，该方法能有效地估测基线，并弥补不能有效获取卫星轨道参数时，对基线进行估测的缺陷，该方法尤其适用于差分干涉测量的研究。     

一种改进的图像域SAR目标散射中心特征提取方法

散射中心是SAR图像目标识别的重要特征。本文基于属性散射中心模型，在文献[6]的基础上，提出了一种改进的图像域SAR目标散射中心特征提取方法。在该方法中，通过引入参数规则化处理步骤，解决了属性散射中心特征提取方法的收敛问题，提高了属性散射中心特征参数估计的精度和效率；提出了一种能同时实现散射中心数目确定和结构判别的方法，实现了散射中心类型的可靠判别。仿真数据和MSTAR实测SAR图像数据的实验结果，验证了本文改进的图像域SAR目标散射中心特征提取方法的有效性。     

合成孔径雷达干扰技术的研究

合成孔径雷达（Synthetic Aperture Radar）是一种新型高辨力成像雷达。其在距离上利用发射的线性调频（LFM）的脉冲压缩信号来获取距离上的高分辨力，在方位上利用接收脉冲之间的多普勒信息获得方位上的高分辨力。本文在简单分析合成孔径雷达工作原理基础上，针对合成孔径雷达的特点与弱点，讨论了几种干扰样式。     

Satellite SAR Remote Sensing of Great Lakes Ice Cover,Part 2. Ice Classification and Mapping

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts.     

Analysis of Resolution of Bistatic SAR

In this paper, the spatial resolutions at different directions of bistatic synthetic aperture radar （BiSAR） have been derived from the ambiguity function. Compared with monostatic signal to noise ratio, BiSAR＇s resolutions of a fixed point target are varying with slow time since BiSAR system is space-variant. Constraints for the assumption of space-invariant bistatic topology are proposed in the paper. Moreover, under the assumption of invariance, the change of resolutions at different point in the image scene is taken into account, and we have specified two key parameters that affect resolutions directly and analyzed the way how they influence on the resolutions.     

SAR图像组合分割算法

由于存在乘性斑点噪声的影响,给SAR图像分割造成很大困难,本文研究利用最大似然区域增长分割算法,提出区域增长前引入自适应边缘检测,图像分割性能获得较大提高.介绍了我们研究的分割性能优异的模拟退火分割算法,提出了分割性能接近模拟退火并且在SAR图像分割中比较实用的模拟退火和最大似然混合分割算法,并给出了这些分割算法的分割性能比较,以及在实际分割SAR图像时应当如何选择分割算法.