Towards validation of SCIAMACHY lunar occultation NO2 vertical profiles

Vertical profiles of stratospheric nitrogen dioxide (NO₂) have been retrieved from moderate resolution lunar occultation transmission spectra measured by Scanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Environmental Satellite (ENVISAT). These measurements were taken over the high southern latitude of 50°–90° during the period of 2003–2005. To assess the accuracy of the retrieved NO₂ profiles, the SCIAMACHY nighttime NO₂ profiles were compared with NO₂ profiles retrieved from sunrise solar occultation spectra measured by the Halogen Occultation Experiment (HALOE) and the Stratospheric Aerosol and Gas Experiments II (SAGE II) using a photochemical correction model. The validation results show good agreement of SCIAMACHY lunar occultation NO₂ with scaled HALOE and SAGE II profiles. The relative mean differences (rmd) with scaled HALOE profiles are within −13% to +5% and standard deviations (rms) of the relative differences are within 3–19% between 25 and 38 km. The rmd and rms with scaled SAGE II NO₂ profiles are in the range of −9 to +7 and 10–17% respectively between 22 and 39 km.     

“实践九号”A卫星光学遥感图像杂散光噪声去除

杂散光是影响卫星光学遥感图像像质的重要因素,严重时会在图像上形成明暗的杂散光条纹噪声,降低图像的对比度和清晰度。文章针对“实践九号”A（SJ-9A）卫星光学遥感图像存在的杂散光噪声现象,设计了一种基于成像载荷焦面入射杂散光空间分布特征的遥感图像杂散光条纹噪声去除方法,通过测量杂散光在推扫遥感图像上的空间分布特征,建立杂散光分布特征模型,采用分块自适应算法进行杂散光噪声滤波,消除SJ-9A遥感图像上随时空变化的杂散光条纹噪声。杂散光噪声去除后图像整体色调均匀,无条带噪声,满足CCD/TDI-CCD推扫遥感图像辐射校正精度（广义噪声）优于5%的指标要求。     

Progress for Spaceborne Microwave Remote Sensing in China

In this paper,technological progress for China's microwave remote sensing is intro-duced.New developments of the microwave remote sensing instruments for meteorological satellite FY-3,ocean dynamic measurement satellite(HY-2),environment small SAR satellite(HJ-1C) and China's lunar exploration satellite(Chang'E-1),geostationary orbit meteorological satellite FY-4M,are reported.     

TanDEM-X: A radar interferometer with two formation-flying satellites

TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an innovative formation-flying radar mission that opens a new era in spaceborne radar remote sensing. The primary objective is the acquisition of a global digital elevation model (DEM) with unprecedented accuracy (12 m horizontal resolution and 2 m relative height accuracy). This goal is achieved by extending the TerraSAR-X synthetic aperture radar (SAR) mission by a second, TerraSAR-X like satellite (TDX) flying in close formation with TerraSAR-X (TSX). Both satellites form together a large single-pass SAR interferometer with the opportunity for flexible baseline selection. This enables the acquisition of highly accurate cross-track interferograms without the inherent accuracy limitations imposed by repeat-pass interferometry due to temporal decorrelation and atmospheric disturbances. Besides the primary goal of the mission, several secondary mission objectives based on along-track interferometry as well as new bistatic and multistatic SAR techniques have been defined, representing an important and innovative asset of the TanDEM-X mission. TanDEM-X is implemented in the framework of a public–private partnership between the German Aerospace Center (DLR) and EADS Astrium GmbH. The TanDEM-X satellite was successfully launched in June 2010 and the mission started its operational data acquisition in December 2010. This paper provides an overview of the TanDEM-X mission and summarizes its actual status and performance. Furthermore, results from several scientific radar experiments are presented that show the great potential of future formation-flying interferometric SAR missions to serve novel remote sensing applications.     

基于GPU的高光谱遥感图像PPI并行优化

传统高光谱遥感信息处理算法的执行效率较低,无法满足海量遥感数据的实时处理需求。文章对基于图形处理器（graphic processing unit,GPU）的高光谱遥感信息处理并行优化方法进行了研究,针对高光谱遥感图像混合像元分解中广泛使用的纯净像元指数算法,提出了一种基于矩阵乘法的GPU并行优化算法,并给出了实验比较和性能测试数据。实验表明,该优化方法在保证结果准确性的同时,运行效率显著提升,算法加速比最高达到634倍,验证了基于GPU的高光谱数据处理并行优化算法的有效性,能够较好地满足高光谱遥感信息实时处理的应用需求。     

压缩感知在电容层析成像中的应用

压缩感知(CS)理论是在充分利用信号稀疏性或可压缩性的情况下,对信号进行少量采样即可实现信号的精确重建。本文尝试将CS理论应用于电容层析成像(ECT)图像重建中,首先,使用快速傅里叶变换(FFT)基将原始图像灰度信号进行稀疏化处理;其次,将ECT灵敏度矩阵的各行按随机顺序进行排列,得到ECT系统随机观测矩阵;最后,选取当前普遍使用的基于内点法、梯度投影(GPSR)算法以及贪婪算法的CS图像重建算法进行ECT图像重建,并与线性反投影及Landweber迭代算法进行了对比。仿真实验结果表明:基于CS图像理论的ECT图像重建算法,其重建精度有所提高。本文同时分析了3种CS图像重建算法的优缺点及适用范围。     

透视空天红外遥感探测技术:演进规律与发展趋势

空天红外遥感探测技术对国民经济发展和战略国防能力建设具有重要意义,是推动我国红外科技进步的关键引擎,更是实现航天科技强国战略的重要基石。本文重点展现了气象卫星观测技术、地物目标精细成像技术、红外焦平面探测器技术以及新时代背景下的遥感应用等多个与红外科技紧密相连的关键领域的研究进展。通过系统梳理相关技术的发展脉络,总结演进规律,并深入剖析最新研究成果,旨在精准洞察未来空天红外科技的潜在发展方向,为我国红外科技的不断创新和航天事业的蓬勃发展提供坚实的支撑。     

改进独立成分分析在高光谱图像分类中的应用

针对独立成分分析在使用常规数值求解时容易陷入局部最优解的问题,以及采用神经学习算法时神经元激活函数的限制问题,将遗传算法与独立成分分析相结合,并对模型进行改进,提出了适合于高光谱数据无监督分类的模型.该算法采用最大化非高斯性进行成分的统计独立性度量,利用四阶累积量-峰度作为遗传算法的适应度函数.在应用分析中,将该算法应用于推扫式高光谱成像仪(PHI,Push-broom Hyperspectral technique Imager)数据地物分类能够获得全局最优解,在没有先验信息情况下实现地物的精细分类;与传统高光谱无监督分类算法比较,表明该算法的适用性,并具有更高的分类精度和准确性.      

推扫成像遥感卫星图像定位精度分析与设计

分析了影响推扫成像遥感卫星图像定位精度的各种误差源,给出了一种图像定位精度的分析和设计方法,分析了侧摆成像条件下高程和目标斜距的不确定性对图像定位精度的影响。     

新型遥感图像增强技术

基于方向辅助信号和所需带宽,提出一种基于各向异性BEMD的遥感图像融合增强算法。首先,给定的方向辅助信号和其对应负信号加到原始信号中去,构建两个待分解信号;然后,应用传统BEMD把两个待分解信号进行分解,获取的分量相加得到对应的IMFs,辅助信引同时在相加的过程中被移除,同时该过程有效地避免了边界效应和模式混叠,该方法...