Implementation of RISAT-1 Hybrid Polarimetric Decomposition Techniques and Analysis Using Corner Reflector Data

With recent advances in polarimetry, Synthetic Aperture Radar (SAR) with Hybrid–polarity architecture, a demonstration of compact polarimetry enabled larger swath coverage, reduced PRF and SAR system complexity as compared to fully polarimetric systems. The first Hybrid Polarimetric Space-borne SAR in Earth Observation orbit, India’s Radar Imaging Satellite (RISAT-1) is a new-fangled gateway to remote sensing user community for land and oceanic applications. In response to a right-circular polarized transmitted signal, based on the derived stokes vectors, Stokes parameters are estimated to produce several useful quantitative measures for generating polarimetric decomposed image. m-delta, m-chi and m-alpha polarimetric decomposition methods along with suitable weighting functions in terms of three principal components are implemented which maps Stokes parameters to RGB image space for representing odd bounce, even bounce and volume scattering targets. Various RISAT-1 Hybrid Fine Resolution Stripmap Single-Look Complex SAR datasets acquired over deployed corner reflectors at calibration site, Shadnagar have been considered over which different hybrid polarimetric decomposition techniques are implemented using in-house developed software. Further analysis produced encouraging results with standard point targets like dihedral and trihedral corner reflectors against distributed targets in the same scene to demonstrate the scattering mechanisms as per their characteristics when interacted with a polarized signal were presented in this paper.     

ENVISAT-ASAR数据产品介绍与数据处理

因ASAR（Advanced Synthetic Aperture Radar）具有全天候、全天时、穿透性强、多种入射角、宽幅成像、多模式、多极化等优势,而成为遥感研究和应用的热点。它是当今最先进的合成孔径雷达数据。本文对ENVISAT的ASAR数据类型进行介绍,并利用欧空局开发的雷达处理工具NEST（Next ESA SAR Toolbox）软件包和ENVI软件对雷达数据进行辐射定标、影像校正和图像滤波处理,为ASAR数据处理方法提供了有益补充。     

地形引起的雷达辐射畸变及其校正

合成孔径雷达影像由于其侧视特点 ,存在着严重的地形引起的几何畸变及辐射畸变。辐射畸变不仅对 SAR辐射标定造成困难 ,而且严重影响了影像分类、土壤湿度信息提取、森林蓄积量信息提取等应用。本文将辐射畸变归结为面积效应和局部入射角效应 ,推导了散射面积归一化因子 ,以消除辐射畸变的面积效应。提出了一种以局部入射角的线性函数表达的后向散射模型 ,在此基础上 ,给出了消除局部入射角效应的校正函数。最后 ,以RADARSAT SAR影像进行地形辐射畸变校正的试验与分析     

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。     

SAR辐射定标中的地物杂波抑制方法

研究了SAR有源编码辐射定标技术,提出了通过移相器进行方位信号编码,通过混频器进行距离信号调频斜率反向的地物杂波抑制方法;采用RD成像算法获得了分布目标的图像,完成了不同分布和强度的地物杂波与定标参考目标的仿真图像,并采用峰值方法对SAR辐射定标精度进行了定量研究。实验结果证明有源编码辐射定标技术能够有效地抑制地物杂波的影响,提高SAR辐射定标精度。     

高分辨率光学/SAR卫星几何辐射定标研究进展

介绍了国内外高分辨率光学/SAR观测卫星进展与发展特点,归纳总结了星载光学/SAR几何辐射定标的基本原理,综述了几何辐射定标研究进展,最后梳理了卫星几何辐射定标的前沿问题。     

Evaluating SAR polarization modes at L-band for forest classification purposes in Eastern Amazon,Brazil

Single, interferometric dual, and quad-polarization mode data were evaluated for the characterization and classification of seven land use classes in an area with shifting cultivation practices located in the Eastern Amazon (Brazil). The Advanced Land-Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data were acquired during a six month interval. A clear-sky Landsat-5/TM image acquired at the same period was used as additional ground reference and as ancillary input data in the classification scheme. We evaluated backscattering intensity, polarimetric features, interferometric coherence and texture parameters for classification purposes using support vector machines (SVM) and feature selection. Results showed that the forest classes were characterized by low temporal backscattering intensity variability, low coherence and high entropy. Quad polarization mode performed better than dual and single polarizations but overall accuracies remain low and were affected by precipitation events on the date and prior SAR date acquisition. Misclassifications were reduced by integrating Landsat data and an overall accuracy of 85% was attained. The integration of Landsat to both quad and dual polarization modes showed similarity at the 5% significance level. SVM was not affected by SAR dimensionality and feature selection technique reveals that co-polarized channels as well as SAR derived parameters such as Alpha-Entropy decomposition were important ranked features after Landsat’ near-infrared and green bands. We show that in absence of Landsat data, polarimetric features extracted from quad-polarization L-band increase classification accuracies when compared to single and dual polarization alone. We argue that the joint analysis of SAR and their derived parameters with optical data performs even better and thus encourage the further development of joint techniques under the Reducing Emissions from Deforestation and Degradation (REDD) mechanism.     

Interferometry with ENVISAT wide swath ScanSAR data

The possibility to get efficient topographic mapping and monitoring of large-scale motions with ScanSAR interferometry has been demonstrated with the Shuttle Radar Topography Mission and RADARSAT mission. The Environmental Satellite Advanced Synthetic Aperture Radar (ASAR) sensor has been designed to provide enhanced capabilities for interferometric applications. Different types of interferometric products can be obtained by combining the various ASAR modes as stripmap synthetic aperture radar [image mode (IM)] and ScanSAR [wide swath (WS) mode]. This letter deals with the possibility to use WS data to get either mixed-mode (IM/WS) or ScanSAR mode (WS/WS) differential interferograms. The impact of digital elevation model localization errors on IM/WS interferograms and of scan pattern synchronization on WS/WS interferograms is investigated. Experimental results are encouraging and show that ASAR ScanSAR data can be routinely used for interferometric applications in both cases.     

基于图像特征的星载SAR图像模拟研究

SAR图像模拟技术被广泛应用于SAR系统的设计和验证、SAR图像的正射纠正、雷达图像解译和目标识别等。随着星载SAR的发展,必然面临着对星载SAR图像模拟的大量需求。本文首先从SAR图像的几何特征和辐射特征出发,探讨了SAR图像模拟技术的原理,分析了RD（Rang Doppler）模型,后向散射模型和斑噪模型。在传统RD模型的基础上,根据不同地形特征（起伏地形和平坦地形）考虑不同的后向散射模型。特别强调了在平坦地形情况下,需要地物分类数据的参与,并利用Ulaby和Dobson的后向散射模型。另外,在SAR图像统计特征的基础上,进行SAR图像的乘性噪声模拟,可以满足更逼真的SAR场景需求。然后,给出了图像模拟的算法流程,并对关键步骤的算法做了分析。最后,在实现基于图像特征的星载SAR图像场景模拟算法的基础上,选择新疆窝依牙地区和天津地区分别进行起伏地形和平坦地形的模拟试验,实验结果证明了本文模拟算法的有效性。     

Terrain radiometric calibration of airborne UAVSAR for forested area

In the field of biomass estimation, terrain radiometric calibration of airborne polarimetric SAR data for forested areas is an urgent problem. Illuminated area correction of σ -naught could not completely remove terrain features. Inspired by Small and Shimada, this paper tested gamma-naught on one mountainous forested area using airborne Uninhabited Aerial Vehicle Synthetic Aperture Radar data and found it could remove most terrain features. However, a systematic increasing trend from far range to near range is found in airborne SAR cases. This paper made an attempt to use the relationship between distance to SAR sensor and γ-naught to calibrate γ -naught. Two quantitative evaluation methods are proposed. Experimental results demonstrate that variation of γ -naught can be constrained to a limited extent from near range to far range. Since this method is based on ground range images, it avoids complicated orthorectification.     

Crop classification from full-year fully-polarimetric L-band UAVSAR time-series using the Random Forest algorithm

Accurate and timely information on the distribution of crop types is vital to agricultural management, ecosystem services valuation and food security assessment. Synthetic Aperture Radar (SAR) systems have become increasingly popular in the field of crop monitoring and classification. However, the potential of time-series polarimetric SAR data has not been explored extensively, with several open scientific questions (e.g. the optimal combination of image dates for crop classification) that need to be answered. In this research, the usefulness of full year (both 2011 and 2014) L-band fully-polarimetric Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data in crop classification was fully investigated over an agricultural region with a heterogeneous distribution of crop categories. In total, 11 crop classes including tree crops (almond and walnut), forage crops (grass, alfalfa, hay, and clover), a spring crop (winter wheat), and summer crops (corn, sunflower, tomato, and pepper), were discriminated using the Random Forest (RF) algorithm. The SAR input variables included raw linear polarization channels as well as polarimetric parameters derived from Cloude-Pottier (CP) and Freeman-Durden (FD) decompositions. Results showed clearly that the polarimetric parameters yielded much higher classification accuracies than linear polarizations. The combined use of all variables (linear polarizations and polarimetric parameters) produced the maximum overall accuracy of 90.50 % and 84.93 % for 2011 and 2014, respectively, with a significant increase of approximately 8 percentage points compared with linear polarizations alone. The variable importance provided by the RF illustrated that the polarimetric parameters had a far greater influence than linear polarizations, with the CP parameters being much more important than the FD parameters. The most important acquisitions were the images dated during the peak biomass stage (July and August) when the differences in structural characteristics between most crops were the largest. At the same time, the images in spring (April and May) and autumn (October) also contributed to the crop classification since they respectively provided unique information for discriminating fruit crops (almond and walnut) as well as summer crops (corn, sunflower, and tomato). As a result, the combined use of only four acquisitions (dated May, July, August, and October for 2011 and April, June, August, and October for 2014) was adequate to achieve a nearly-optimal overall accuracy. In light of the promising classification accuracies demonstrated in this research, it becomes increasingly viable to provide accurate and up-to-date crops inventories over large areas based solely on multitemporal polarimetric SAR.     

Comparison of ERS-SAR and spot data for sugar beet crop cover assessment

The present work was aimed to compare the abilities of radar and optical satellite data to estimate crop canopy cover, which is a key component of productivity estimates. Three ERS-1 SAR images were obtained of East Anglia (UK) in 1995 and one ERS-2 SAR image in 1996. The images covered a study area around the IACR Brooms Barn Sugar Beet Research Institute. Field data comprising radiometric and biophysical measurements of the crop canopy were collected in two fields from June 22 to August 3, 1995 to coincide with ERS-1 SAR overpass dates. In 1996, field data were collected in two fields from June 11 to July 29 on a weekly basis. A previously calibrated version of the water cloud model was inverted to estimate Leaf Area Index (LAI) from ERS-1 and ERS-2 SAR backscatter and soil moisture samples. Canopy cover was estimated from the radar-estimated LAI using a standard exponential relationship that has a well-established coefficient for sugar beet. Radio-metrically and atmospherically corrected data from three SPOT images in 1995 and one SPOT image in 1996 were used to calculate the Optimised Soil Adjusted Vegetation Index (OSAVI), from which crop canopy cover was estimated using a relationship determined previously by canopy modelling. The crop cover values estimated by satellite were in good agreement with those measured on ground with the Parkinson radiometer. Radar data may be able to provide useful estimates of canopy cover for crop production modelling, especially in the case of loss of optical data due to cloud.     

Landsat系列卫星光学遥感器辐射定标方法综述

Landsat系列卫星自1972发射以来,已经连续提供了40多年的中等分辨率多光谱遥感数据,广泛应用于农业、水资源管理、灾害响应等领域。目前,很多研究人员开始考虑利用这些数据开展中分辨率尺度的长时间序列地表定量信息监测,更加精细地反映局地甚至全球气候变化。开展这些研究的前提在于对数据进行辐射定标,并通过不同卫星的交叉辐射传递保证数据辐射精度的一致性。从Landsat 1到Landsat 8,随着遥感器性能和数据获取能力的提升,辐射定标方法不断更新,涉及发射前实验室定标、内定标灯方法、全孔径太阳定标器方法、交叉定标方法、场地定标方法等。本文在对Landsat系列卫星的遥感器性能进行分类、归纳、对比的基础上,系统梳理了Landsat系列卫星遥感器辐射定标方法发展过程以及不同定标方法的优缺点,特别是对定标精度的影响。Landsat系列卫星辐射定标的发展过程为遥感数据高精度定量化应用提供了非常重要的基础,未来辐射定标方法不但要随着新型遥感器研制而更新,更要注重多源遥感数据的交叉验证以及全过程辐射定标方法的完善与应用,保障遥感数据辐射定标精度的一致性。     

顾及大气延迟效应的YG-13A斜距标定

针对大气延迟时变误差影响遥感卫星十三号(YG-13A)斜距标定精度的问题,提出利用顾及大气延迟时变误差的斜距标定方法提高其斜距标定精度的策略。首先,利用基于NCEP气象资料和全球TEC数据的大气延迟改正方法来计算各标定景的大气延迟改正量。其次,将各标定景的大气延迟改正量代入斜距标定模型中。最后,在地面布设高精度角反射器控制点的情况下通过顾及大气延迟时变误差的斜距标定模型求解斜距测量系统误差,从而提高和验证斜距测量精度,角反射器控制点的平面和高程精度均优于0.1 m。利用嵩山遥感定标场地区的4组不同拍摄模式下获得的YG-13A卫星影像数据对比试验表明,相较于传统的斜距定标方法,在顾及大气延迟时变误差的情况下,4组数据的斜距改正值离散度均有所下降。利用太原、天津两个区域3景影像验证斜距改正后的精度,最小值为0.55 m,最大值为0.91 m,均值为0.70 m。试验结果证明了顾及大气延迟时变误差的斜距标定方法的有效性和可行性。     

一种基于图像边缘特征的SAR斑点滤波算法

合成孔径雷达图像上的斑点噪声会阻碍图像的校准、检验、解译和应用,因此斑点噪声的去除是雷达图像处理的一个重要环节。通常的去噪方法在抑制噪声的同时也使得图像的边缘模糊,细节特征损失。理论和实践表明去除图像的斑点噪声和保持图像的边缘信息是无法同步实现的。为了在去除噪声和保持边缘特征之间进行折衷,本文基于MROA边缘检测算法以及均值滤波算法,提出了一种基于图像边缘特征的斑点噪声滤波算法。实验结果表明该算法能够在平滑图像的同时有效保持边缘特征信息。     

敦煌场地CBERS-02 CCD传感器在轨绝对辐射定标研究

对资源一号卫星02星（CBERS-02）,为深入其定量化分析,定期在敦煌绝对辐射校正场地进行了地面同步测量,开展了更新在轨绝对辐射定标研究。另外,运用地表反射率和大气光学特性参量数据,计算出CBERS-02CCD传感器4个波段的绝对辐射标定系数。同时,利用2004年8月25目的Landsat-5 TM图像数据对CBERS-02 CCD传感器的辐射特性进行交叉定标,验证分析了CBERS-02 CCD传感器场地绝对辐射定标的基本特性及其可靠性。另外,为CBERS后续星的传感器改进,提供了分析参量。     

Coherence optimization using the polarization state conformation in PolInSAR

A new coherence optimization algorithm is proposed for polarimetric synthetic aperture radar (SAR) interferometry applications by using the polarization state conformation algorithm based on the polarimetric basis transformation along with the polarization signatures. Through application of this algorithm, the resemblance between the scattering mechanisms of the same target in the repeat-pass polarimetric SAR (POLSAR) images is maximized. Then, coherence maps between the repeat-pass POLSAR images, before and after application of the algorithm, are generated. The coherences obtained by this method represent the best coherences or optimized coherences between the POLSAR images. The effects predicted by the theory are confirmed by the POLSAR data acquired by the Jet Propulsion Laboratory Spaceborne Imaging Radar mission.     

合成孔径雷达图像的近岸海面风场反演

根据海面微波散射原理，给出了星载合成孔径雷达(Synthetic Aperture Radar,SAR)图像海面风场反演的方法。该方法包括SAR图像辐射定标、海面风向确定和风速计算。利用该方法由加拿大RadarsatSAR图像反演获得了中国海南省东南部近岸海区海面风场，并与预报风场作了比较。结果显示，二者相符得很好，风速的均方根误差为0.94m/s，风向的均方根误差为4.03°。     

Discrimination between Babul plantations and Mustard crop using Polarimetric C- and L- band data

Radar sensors can be used for large-scale vegetation mapping and monitoring using backscattering coefficients in different polarizations and wavelength bands. C-band space borne SAR is widely used for the classification of agricultural crops, but can only perform a limited discrimination of various tree species. This paper presents the results of discrimination between mustard crop and babul plantation (Prosopis sp.) using quad polarisation Radarsat 2 and ALOS PALSAR data. Study area is comprised of dense babul plantation along the canal, mustard crop on one side of the canal and Fallow land near to Ramgarh village of Jaisalmer district. Three bands of Radarsat (HH, HV and VV) acquired during peak mustard crop growth stage were integrated with four polarizations (HH, HV, VH and VV) of ALOS PALSAR acquired when crop cover was absent. Using only Radarsat data Jefferies-Matusita (JM) separability between mustard crop and babul plantation was found to be poor (710). Where as in the seven band combination the separability was observed to be high (1374). Among the different polarizations three layer combination, highest separability was observed using cross polarizations (HV and VH) of L-band with any one of the Radarsat Polarisation (HH/HV/VV). This combination of C- and L-band resulted in easy separation of mustard and babul plantation which was otherwise difficult using only Radarsat data.     

不依赖人工定标器的全极化SAR定标研究进展

极化定标是极化合成孔径雷达应用的前提。传统极化定标方法以地面布设的人工定标器为参考,通过极化畸变模型对系统误差进行求解与标定。然而,人工定标器价格昂贵、数量稀少,每次定标任务都需根据传感器过境方向、雷达视角等信息进行设备调整;此外,现代雷达系统工作波位多、入射角调节范围大,不同视角获取影像的定标参数也不相同,这对地面定标设备的布设精度、调整的时效性提出了更高要求。为了及时、快速地完成极化定标,如何以自然界中的某些特殊地物作为人工定标器的替代品来完成定标具有重大的科学价值。本文综述了近年来国内、外提出的不依赖人工定标器的SAR极化定标研究进展（即自主定标）。首先阐述了极化定标的基本流程与极化质量评价体系;然后对近年来高精度自主定标相关研究进行了梳理,根据技术特点将其分为基于自然地物约束的自主极化定标、基于似角反射器的自主极化定标两类,对不同算法适用性进行了分析;最后对未来的研究方向进行了展望。