基于有理多项式模型的星载高分InSAR影像制作数字高程模型的研究

合成孔径雷达干涉测量是一种利用SAR影像复数据的相位信息提取地面三维信息的技术,它通过获取地面目标在两幅SAR影像上的相位差值来解算该点的三维坐标。有理多项式（RPC,Rational Polynomial Coefficient）模型作为一种数学意义上的几何模型,它独立于传感器和平台,简单且具有通用性,可建立地面任意坐标与影像空间的关系。本文在RPC模型用于替代星载SAR的距离多普勒模型和星载InSAR的干涉相位方程基础上,研究 RPC模型应用于星载高分辨率InSAR影像制作DEM的可行性和精度。利用兰州COSMO-SkyMed数据和资源三号三线阵数据制作的DEM为参考数据进行实验验证,RPC模型用于InSAR技术生成的DEM,中误差为7.55米。     

高分辨率星载SAR数据产品分级研究

有理函数模型RF在卫星图像领域的主要应用是进行对象空间和图像空间的转换。Radarsat-2元数据中使用三阶有理函数模型和80个有理多项式模型参数RPCs(Rational Polynomial Coefficients),为RF模型从光学图像领域的应用扩展到合成孔径雷达(SAR)图像领域提供了契机。本文对多种传感器、成像模式及不同处理级别SAR图像的RPC产品的制作和属性进行综述,主要研究高分辨率星载SAR卫星标准分级产品的制作流程。以中国广州作为实验区域,利用该地区不同级别的条带模式SM(Strip Map)Terra SAR-X和COSMO-Sky Med数据,对提出的分级和生产方案进行验证,结果表明,有理函数模型在SAR图像产品分级体系中具有可行性且效果良好。     

基于RPC的TerraSAR-X影像立体定向平差模型

针对新型高分辨率雷达卫星TerraSAR-X立体像对,本文提出采用基于RPC的平差模型,通过少量的地面控制点来拟合因传感器不稳定、平台星历数据不精确及测距误差引起的影像几何畸变,从而达到精确定向目的.为验证RPC平差模型的适用性,通过在立体成像区域均匀市设人工角反射器点的方法验证其模型精度,并评估了其三维定向平差后的精...     

Rational function modeling for spaceborne SAR datasets

As a kind of generic sensor model, the rational function model (RFM) has been widely used in geometric processing of optical images, but has not yet been applied to SAR datasets. In this article the feasibility and methodology of rational function (RF) modeling for SAR datasets are investigated. After a review of the mathematic formulation of the RF model and the Range-Doppler model for SAR systems, the feasibility of applying RFM to SAR datasets is analyzed. Afterwards a two-stage approach is proposed as the key technique for SAR RF modeling to solve unknown parameters of RFM in a fast and unbiased way. The effectiveness and advantages of this approach are demonstrated by comparisons with traditional methods. Experimental results obtained for various spaceborne SAR datasets of different processing levels show that RFM is a suitable replacement of the rigorous Range-Doppler model for spaceborne SAR images. Furthermore, the impacts of several factors including the control point grid size, the number of elevation layers, and the orbit precision on SAR RFM solutions are evaluated quantitatively. The results show that the number of elevation layers is a key factor in SAR RF modeling, and its value should be set carefully according to terrain conditions of study areas. Finally, potential applications of SAR RFM are discussed in brief.     

On RPC model of satellite imagery

The RPC model has recently raised considerable interest in the photogrammetry and remote sensing community. The RPC is a generalized sensor model that is capable of achieving high approximation accuracy. Unfortunately, the computation of the parameters of RPC model is subject to the initial of the parameter in all available liteature. An algorithm for computation of parameters of RPC model without initial value is presented and tested on SPOT-5, CBERS-2, ERS-1 imageries. RPC model is suitable for both push-broom and SAR imagery.     

基于影像模拟的星载SAR影像正射纠正

对山地和高山地等选点困难地区的星载SAR影像进行正射纠正时,通常采用距离多普勒模型进行影像模拟纠正。但由于每类星载SAR影像辅助数据不同,所建立的距离多普勒模型均不相同,从而导致针对每类星载SAR影像需要采用不同的软件模块进行模拟和正射纠正。针对该缺点,采用RPC模型代替距离多普勒模型并利用改进的模拟影像灰度确定方式进行星载SAR影像模拟,在此基础上建立模拟影像和真实SAR影像之间关系进行正射纠正。采用四川某地区的TerraSAR-X影像,将正射纠正的实际精度和理论精度进行对比,验证本文提出的理论和方法。     

On RPC model of satellite imagery

IntroductionThe rational polynomial coefficient ( RPC)model is a generalized sensor model that is usedas an alternative solution for the rigorous sensormodel for IKONOS of the spacei maging. As thenumber of sensors increases along with greatercomplexity ,…     

基于有理函数模型的星载SAR影像几何校正

主要研究了面向星载合成孔径雷达SAR(Synthetic Aperture Radar)影像几何处理的有理函数模型RFM(Rational Function Model)的建模、求解和应用方法。首先采用与地形无关的方式,利用严密的距离-多普勒模型(Range Doppler,RD)构建虚拟控制点格网来进行RFM建模,实现了一种RFM模型参数的快速无偏解算新方法,能够取得相对于RD模型很高的拟合精度,在几何定位功能上实现了对RD模型的有效替代,同时大大提高了计算效率。然后在此基础上利用RFM模型实现了星载SAR影像的快速几何校正,为了提高几何校正结果的绝对定位精度,引入少量地面控制点对RFM模型进行了像方改正处理,以消除SAR影像几何定位的系统误差,并利用ENVISAT ASAR数据的实验结果验证了本文方法的有效性。     

玉树地震灾情SAR遥感监测与信息服务系统

在玉树地震中,中国首套自主知识产权的机载多波段多极化干涉SAR测图系统,发挥全天时主动遥感的优势,成功服务于抗震救灾中。依据玉树地震灾情综合地理信息监测与评估工作,着重探讨SAR遥感影像用于地震灾情监测与评估中的处理方法和技术路线,研究制定了地震灾区灾情综合地理信息监测指标,通过快速几何处理、快速变化信息提取、快速目标判读和灾害空间危险性评估,实现了玉树地震震区灾情综合地理信息的解译、制图和统计评估。在此基础上,开发了玉树地震灾情综合地理信息服务系统,实现了灾情监测信息的综合管理、可视化查询和统计分析。     

天绘一号卫星三线阵影像RPC模型定位精度验证与分析

天绘一号卫星以RPC参数作为主要的影像辅助数据提供给用户,对传感器的技术参数进行隐藏.文中简要介绍RPC模型的立体定位方法,并针对定位结果中存在的明显的系统误差,采用像方补偿方案进行补偿,最后利用两景天绘一号卫星三线阵影像RPC模型对测区进行实验验证和分析.结果表明,采用少量地面控制点进行系统误差补偿后,定位精度提升效果明显,验证了模型的正确性和有效性.     

A comparative data-fusion analysis of multi-sensor satellite images

Remote-sensing data play an important role in extracting information with the help of various sensors having different spectral, spatial and temporal resolutions. Therefore, data fusion, which merges images of different spatial and spectral resolutions, plays an important role in information extraction. This research investigates quality-assessment methods of multisensor (synthetic aperture radar [SAR] and optical) data fusion. In the analysis, three SAR data-sets from different sensors (RADARSAT-1, ALOS-PALSAR and ENVISAT-ASAR) and optical data from SPOT-2 were used. Although the PALSAR and the RADARSAT-1 images have the same resolutions and polarisations, images are gathered in different frequencies (L and C bands, respectively). The ASAR sensor also has C-band radar, but with lower (25 m) resolution. Since the frequency is a key factor for penetration depth, it is thought that the use of different SAR data might give interesting results as an output. This study describes a comparative study of multisensor fusion methods, namely the intensity-hue-saturation, Ehlers, and Brovey techniques, by using different statistical analysis techniques, namely the bias of mean, correlation coefficient, standard deviation difference and universal image quality index methods. The results reveal that Ehlers' method is superior to the others in terms of spectral and statistical fidelity.     

基于严格仿射变换模型的遥感影像RPC参数求解

提出了利用少量地面控制点,采用基于严格仿射变换模型求解遥感影像的RPC参数,并对CBERS-02B卫星HR相机遥感影像进行了试验,获得了一些有意义的结论。     

Accuracy Assessment of Digital Elevation Model Generated by SAR Stereoscopic Technique Using COSMO-Skymed Data

Radargrammetry technique using the stereoscopic synthetic aperture radar (SAR) images is used for the generation of a digital elevation model (DEM) of a region requires only the amplitude images. SAR stereoscopic technique is analogous to the stereo-photogrammetric technique where the optical stereoscopic images are used for DEM generation. While the advantages of the SAR images are their indifference to atmospheric transparency and solar illumination conditions, the side-looking geometry of the SAR increases the complexity in the SAR stereo analysis. The availability of high spatial and temporal resolution SAR data in recent years has facilitated generation of high-resolution DEM with greater vertical accuracy using radargrammetric technique. In the present study, attempt has been made to generate the DEM of Dehra Dun region, India, from the COSMO-Skymed X-band SAR data-pair acquired at 8 days interval through the radargrammetry technique. Here, radargrammetric orientation approach has been adopted to generate the DEM and various issues and processing steps with the radargrammetry technique have been discussed. The DEM was validated with ground measured elevation values using a differential global positioning system and the root-mean-square error of the DEM was found as 7.3 m. The DEM was compared with the reference DEM of the study area generated from the Cartosat-1 stereo data with a model accuracy of 4 m.     

基于RPC模型的高分辨率卫星影像精确定位

介绍高分辨率卫星影像RPC模型的定义及其解算方法,推导RPC模型立体定位的基本方程,在此基础上对RPC模型的区域网平差进行深入研究。IKONOS卫星数据的实验结果表明,RPC模型误差呈现较强的系统性,但通过物方或像方的补偿立体定位可达到优于1.3 M的定位精度,区域网平差是最优的定位方法,精度可达1.1 M。     

Soil Moisture Estimation in a Vegetated Area Using Combination of AIRSAR and Landsat5-TM Images

High difference between dielectric constant of water (dielectric constant about 80) and dielectric constant of dried soil (dielectric constant about 2–3) makes Synthetic Aperture Radar (SAR) highly capable in soil moisture estimation. However, there are other factors which affect on radar backscattering coefficient. The most important parameters are vegetation cover, surface roughness and sensor parameters (frequency, polarization and incidence angle). In this paper, the importance of considering the effects of these parameters on SAR backscatter coefficients is shown by comparing different soil moisture estimation models. Moreover, an experimental soil moisture estimation model is developed. It is shown that this model can be used to estimate soil moisture under a variety of vegetation cover densities. The new developed model is based on combination of different indices derived from Landsat5-Thematic Mapper and AIRSAR images. The AIRSAR image is used for extraction of backscattering coefficient and incidence angle while TM image is used for calculation of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI) and Brightness Temperature. Then a soil moisture estimation model which is named as Hybrid model is developed based on integration of all of these parameters. The accuracies of this model are assessed in the NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7 by using SAR data in C band and L band frequencies and also in different polarizations of HH, HV, VV and TP. The results show that for instance in L band with HV polarization, R-square values of 0.728, 0.628 and 0.527 are obtained between ground measured soil moisture and estimated soil moisture values using the Hybrid model for NDVI ranges of 0–0.2, 0.2–0.4 and 0.4–0.7, respectively.     

基于阈值分割与决策树的SAR影像水体信息提取

目前我国的GF-3 SAR数据可实现全天时全天候的对地观测,已服务于海洋、减灾、水利、气象等多个领域。改进了基于阈值分割法与决策树的GF-3 SAR影像水体信息提取方法,首先对GF-3 SAR影像进行基本处理;再采用KI二值化阈值分割法进行图像分割;然后通过构建知识决策树模型来提取水体信息,为了提高精度,采用GDEM数据进行地表建模,提取山体阴影;最后利用空间分析功能将地形建模阴影图与提取的水体范围进行匹配,去除山体阴影,进而获得水体信息的精确范围。通过混淆矩阵计算得到水体信息提取的总体精度为89.22%,Kappa系数为0.71,精度优于基于光学GF-2号影像的水体指数法提取结果。整个流程人工干预少,具有自动化更强、效率更高的优势。     

Mini SAR遥感系统测图

Mini SAR遥感系统,用微小型SAR做传感器,通过小型飞机或无人机为遥感平台获取地物信息,但载机平台在空中易受气流影响而偏离预设航线产生运动误差。文中首先分析载机平台运动特点,介绍系统中IMU/GPS组合导航数据预处理过程,论述载机平台转动误差、速度误差对SAR成像距离模型的影响。MiniSAR遥感系统获取的影像清晰,可用于制作正射影像图、基础地理信息库更新、灾害监测应急等领域,但不足之处在于影像中某些金属目标出现方位散焦现象。     

基于SVD算法的RPC纠正

在高分辨率遥感卫星影像RPC模型纠正过程中,有理函数参数的解算是问题的关键,为了克服该算法的误差方程经法化后存在严重病态的问题,提出了SVD算法,即奇异值分解法。根据精度评定的计算结果看到,SVD对处理奇异或者近似奇异的方程组或矩阵都非常有效,保证RPC纠正精度。     

深度学习在光学和SAR影像融合研究进展

遥感影像融合作为影像处理领域中最具有挑战的工作,一直是学术界研究的热点。合成孔径雷达SAR（Synthetic Aperture Radar）具备全天时、全天候、穿透云雾等多种特点,却因存在相干斑噪声等问题,使得影像难以解译。相比之下,光学影像可以反映地物的光谱和空间信息,易于解译,但容易受到云雾干扰,造成信息丢失,将光学与SAR影像数据融合可以实现不同类型传感器成像之间的信息互补,能够更好地为后续的影像分析与解译提供方便。本文首先对光学和SAR影像融合进行了系统性回顾,包括传统融合方法和基于深度学习方法在影像融合方面的最新工作,重点阐述了卷积神经网络CNN（Convolutional Neural Network）、生成式对抗网络GAN（Generative Adversarial Networks）等框架在光学和SAR影像融合中的进展;然后总结了光学和SAR影像融合在深度学习领域开发的数据集,并做了简单介绍和说明;最后,从数据集、时间序列影像融合、融合评价体系和算法轻量化等4个方面对光学和SAR影像融合的未来发展趋势进行了展望。     

基于静态模型的多视角SAR图像目标识别方法

传统的多视角SAR图像集合对于目标姿态角具有高度敏感性,因此在用于目标识别时存在一些不足之处。针对该问题提出一种多视角SAR图像的静态建模方法,它将来自一个目标多个视角下的图像信息集成到一个综合的数据结构中,并且该数据结构与目标散射中心有关而与角度无关。然后利用静态模型对不完全姿态角的目标数据进行静态建模,利用模板匹配法对输入多视角图像进行目标识别。理论分析和仿真结果表明,本方法在每个目标只有少量姿态角模板数据可用的情形下比传统模型具有优势。