合成孔径雷达多波段的应用及其效果评价

本文综述了不同波段的雷达数据在各应用领域中的优势和不足,并指出在某些领域中,两个或三个波段联合使用有其明显的优势。     

合成孔径雷达多波段的应用及其效果评价

本文综述了不同波段的雷达数据在各应用领域中的优势和不足,并提出在某些领域中,两个或三个波段联合使用有其明显的优势。     

星载合成孔径雷达回波数据仿真研究

本文对星载合成孔径雷达（SAR）图像仿真方法进行了研究,在分析并建立合成孔径雷达回波信号数学模型的基础上,提出了基于分布目标的SAR回波信号数据仿真,进而提出了一种与传统实现方法不同的SAR原始回波数据的生成方法,并用这种方法进行了初步的建模和仿真,验证了其有效性。     

多波段InSAR差分滤波相位解缠方法

依据干涉图零中频矢量滤波经验,设计了多波段InSAR干涉图的差分滤波相位解缠方法。该方法将较短波长干涉图与较长波长干涉图的解缠结果进行差分处理,以降低干涉条纹频率,提高滤波效果和相位解缠性能,从而以较长波长干涉图的解缠结果指导较短波长干涉图的相位解缠。充分利用不同波段干涉图之间的互补相位信息,提高相位解缠的可靠性和解缠精度。采用由DEM仿真的多波段干涉图进行了相位解缠试验,得到了满意的解缠结果,验证了该解缠方法的有效性。     

高分辨率SAR图像杂波模型对比研究

本文针对高分辨率SAR图像的陆地场景,开展Normal分布、Rayleigh分布、LN分布、Weibull分布和Gamma分布模型的对比拟合实验。通过K-S法检验每种模型对不同SAR场景杂波数据的拟合精度,并通过Gamma Map滤波简单说明杂波模型在斑点噪声抑制方面的应用。结果表明,Gamma Map滤波效率高于其他的传统方法。     

干涉合成孔径雷达及其在火山研究中的应用(第一部分:InSAR原理)

干涉合成孔径雷达是一项能够对地表变形进行测量的遥感技术,在一个巨大区域内,它的变形测量精度可达亚厘米级,而其空间分辨率则在数十米以内。本文回顾了InSAR技术的基本理论,阐明了它的工作原理,并对应用InSAR技术进行地表变形测量的相关问题进行了讨论。     

星载方位多波束ScanSAR 成像

提出了一种新型星载方位多波束ScanSAR 工作模式, 实现了在保持方位向高分辨率的前提下对距离向测绘带大幅扩展。分析了该工作方式的特点及主要相位误差, 给出了相应的误差补偿方法。介绍了该工作方式下回波数据的模拟方法, 并讨论了几种适合该工作方式的成像算法。最后通过仿真对该工作方式的可行性及补偿方法的有效性进行了验证。     

机载X波段极化干涉SAR数据非监督分类方法研究

针对经典极化分类算法在处理机载X波段SAR数据时将过多地物分为体散射类型,并且容易受噪声影响,分类结果存在大量误分现象的问题,通过对机载X波段SAR数据非监督分类方法的研究,提出将极化干涉信息用于机载X波段极化干涉SAR数据的分类。通过运用极化干涉数据进行目标分解得到参数A1和A2对数据进行初始分类,然后结合改进的Wishart最大似然分类算法来进行地物的自适应分类。实验结果表明,该方法能有效避免平地效应的影响,抗噪性好,能正确区分三种典型散射类型,分类效果明显优于极化分类效果。     

基于DS点目标的幅度和相位滤波方法研究

分布散射点(Distributed Scatterer,DS)的散射稳定性较永久散射点略弱,但其具有数量多、密度大、存在大量同质点的特征.因此本研究提出基于DS点的幅度和相位滤波方法研究,并展开仿真、实测数据实验和分析.研究结果表明:与传统的基于空间域窗口的均值或中值滤波相比,基于同质点的幅度和相位滤波后的图像平滑程度...     

ALI 数据全色及多光谱波段图像融合方法比较研究

ALl（The Advanced Land Imager）数据是通过地球观测卫星l（E0—1）搭载的高级陆地成像仪所i犬取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目前利用ALl数据的全色波段以及多光谱波段进行高精度图像融合的研究较少,本文进行的实验足分别利用HSV变换、主成分分析（PeA）、Brovey变换、Gram—Schmidt变换等融合方法对ALI数据进行图像融合,通过图像融合结果的质毓评价指标得出较好融合方法是HSV变换。     

浅谈星载合成孔径雷达影像调绘片制作

阐述了星载雷达遥感技术的优势及应用现状,结合我国西部横断山脉外业调绘片生产,介绍了利用TerraSAR-X及RadarSat-2影像制作数字正射影像的数据处理流程,提出了一套行之有效的技术方案。     

SAR图像配准方法综述

随着SAR成像技术的不断发展和对SAR图像应用的迫切需求,涌现了大量的SAR图像配准方法。对国内外最新的SAR图像配准技术和方法进行了全面系统地梳理,总结了各类方法的特点,指出了当前研究存在的问题,展望了SAR图像配准的发展趋势。     

SAR影像在立体测图中的应用

通过对机栽2．5m分辨率SAR影像的布点、平差及单片计算,进一步构建了邻航线间SAR影像的立体模型配对,并通过FeatureStation工作平台的矢量化采集,完成了1：50000比例尺的DLG测图工作。     

Polarimetric SAR cross-calibration method based on stable distributed targets

Polarimetric calibration is essential for the pre-processing of Polarimetric Synthetic Aperture Radar(PolSAR)data because it effectively mitigates polarimetric distortions in the measured PolSAR data.Traditional methods of polarimetric calibration employ man-made calibrators that offer high accuracy.However,the frequency of calibration is often limited due to the labor-intensive and time-consuming nature of deploying such calibrators.Some polarimetric calibra-tion methods based on distributed targets in nature enable more frequent calibration.Nevertheless,these methods are constrained by the availability of specific distributed targets with known polarimetric properties for estimating parameters related to co-polarization chan-nel imbalance(co-pol-imba)parameters.If distributed targets are not appropriately selected or suitable targets are absent within the image scene,the accuracy of calibration will be com-promised.To address this challenge,this paper introduces the idea of cross-calibration,which uses calibrated PoISAR data to determine the real polarimetric property of distributed targets and cross-estimates co-pol-imba parameters for uncalibrated PolSAR data.Furthermore,con-sidering the disparities in imaging geometry between calibrated and uncalibrated PolSAR data,the Cross-Co-Polarization Ratio(CCPR)coefficients are proposed to select stable distributed targets in both the calibrated PolSAR data and the uncalibrated PoISAR data.This approach not only takes into account the impact of co-pol-imba on feature extraction but can also be applied in a broader range of scenes.The real data experiments on the Uninhabited Aerial Vehicle Synthetic Aperture Radar(UAVSAR)data show that the estimated results of the cross-calibration method for co-pol-imba are comparable to the polarimetric calibration method based on man-made calibrators,with an amplitude difference of 0.17 dB and a phase difference of 0.69°.     

Exploiting satellite SAR for archaeological prospection and heritage site protection

Optical and Synthetic Aperture Radar(SAR)remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications,yet further advances are viable through the exploitation of novel sensor data and imaging modes,big data and high-performance computing,advanced and automated analysis meth-ods.This paper showcases the main research avenues in this field,with a focus on archae-ological prospection and heritage site protection.Six demonstration use-cases with a wealth of heritage asset types(e.g.excavated and still buried archaeological features,standing monu-ments,natural reserves,burial mounds,paleo-channels)and respective scientific research objectives are presented:the Ostia-Portus area and the wider Province of Rome(Italy),the city of Wuhan and the Jiuzhaigou National Park(China),and the Siberian\"Valley of the Kings\"(Russia).Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite(e.g.Copernicus Sentinels and ESA Third Party Missions)and aerial(e.g.Unmanned Aerial Vehicles,UAV)platforms,as well as field-based evidence and ground truth,auxiliary topographic data,Digital Elevation Models(DEM),and monitoring data from geodetic campaigns and networks.The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes,identify threats to cultural heritage assets due to ground instability and urban development in large metropolises,and monitor post-disaster impacts in natural reserves.     

SAR点目标的响应形状

人们普遍认为,SAR点目标响应是sinc函数形状,但是,在通常条件下,SAR点目标看上去不象sinc函数形状。文章从驻留相位原理的近似性,数字信号处理和连续信号处理的差别,人类视觉,检波造成的频谱扩展,SAR的斜视等方面,指出其原因,并阐述了使点目标形状象sinc函数形状需要满足的条件。并提出SAR图像从复数图到模值图的转化过程需要满足的条件和处理。     

Improving the Wishart Synthetic Aperture Radar image classifications through Deterministic Simulated Annealing

This paper proposes the use of Deterministic Simulated Annealing (DSA) for Synthetic Aperture Radar (SAR) image classification for cluster refinement. We use the initial classification provided by the maximum-likelihood classifier based on the complex Wishart distribution that is then supplied to the DSA optimization approach. The goal is to improve the classification results obtained by the Wishart approach. The improvement is verified by computing a cluster separability coefficient. During the DSA optimization process, for each iteration and for each pixel, two consistency coefficients are computed taking into account two kinds of relations between the pixel under consideration and its neighbors. Based on these coefficients and on the information coming from the pixel itself, it is re-classified. Several experiments are carried out to verify that the proposed approach outperforms the Wishart strategy. We try to improve the classification results by considering the spatial influences received by a pixel through its neighbors. Finally, a link about the contribution of DSA to thematic mapping is also established.