应用卫星遥感进行生态环境动态监测

目前,90%的能源、80%以上的工业原料来自于矿产资源。矿产资源开发实际上在消耗两种资源,即矿产资源和环境资源,尤其是资源的露天开采对生态环境造成了极大的破坏。文章选取山西省孝义市作为研究区,以1990年、1999年和2007年三期遥感影像为主体数据源,采用遥感与GIS技术相结合的监测技术手段,建立生态环境评价指标体系和评价方法;采用遥感和GIS技术对矿区生态环境进行实时的监测,科学地评价生态环境状况及预测变化趋势。为研究区今后进行生态环境调查提供了客观、详实、丰富的数据。同时为今后政府部门生态环境治理提供了参考依据。     

星载激光遥感技术的发展及应用

文章简要介绍了星载激光遥感的技术原理与特性,并对几种星载激光雷达在大气探测、星体测绘、冰盖监测及全球高分辨率测绘等领域的应用做了介绍,最后分析了中国发展星载激光遥感现阶段的已有基础及对未来的发展展望。     

Retrieval of crop variables with field-based X-band microwave remote sensing of ladyfinger

Modeling in agriculture has been widely used to retrieve and monitor various soil and crop growth variables. Remote sensing, especially radar sensors can be useful for temporal and spatial monitoring of the soil and plant variables. Therefore, in this paper field measurements of crop ladyfinger were carried out to examine the dependency of radar backscatter on crop–soil variables and to develop a method for monitoring and retrieving crop variables for ladyfinger. A crop-bed was prepared to observe scatterometer response in the angular range of incidence angle 20–70° at 9.89 GHz in the X-band for VV- and HH-polarization. At the same time, soil moisture, plant height, leaf area index and aboveground biomass were measured at various growth stages of crop ladyfinger. The angular variation of scattering coefficient decreases with the age of crop ladyfinger shows the dominance of crop effect on soil moisture effect at the older age. Thus, angular trends are more flat as the plant grows since the effects of soil is masked by developing vegetation. Scattering coefficient increases with the increase of leaf area index for both polarizations (i.e. VV- and HH-). It was found that leaf area index and aboveground biomass of crop ladyfinger are highly correlated with microwave frequency more than with plant height and soil moisture. Leaf area index and biomass of ladyfinger crop were retrieved by polarization based model and non-linear least square optimization model. These two models gave very good results for the retrieval of leaf area index and aboveground biomass.     

Kinetic temperature and carbon dioxide from broadband infrared limb emission measurements taken from the TIMED/SABER instrument

The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment is one of four instruments on NASA’s Thermosphere–Ionosphere–Energetics and Dynamics (TIMED) satellite. SABER measures broadband infrared limb emission and derives vertical profiles of kinetic temperature (Tk) from the lower stratosphere to approximately 120 km, and vertical profiles of carbon dioxide (CO₂) volume mixing ratio (vmr) from approximately 70 km to 120 km. In this paper we report on SABER Tk/CO₂ data in the mesosphere and lower thermosphere (MLT) region from the version 1.06 dataset. The continuous SABER measurements provide an excellent dataset to understand the evolution and mechanisms responsible for the global two-level structure of the mesopause altitude. SABER MLT Tk comparisons with ground-based sodium lidar and rocket falling sphere Tk measurements are generally in good agreement. However, SABER CO₂ data differs significantly from TIME-GCM model simulations. Indirect CO₂ validation through SABER-lidar MLT Tk comparisons and SABER-radiation transfer comparisons of nighttime 4.3 μm limb emission suggest the SABER-derived CO₂ data is a better representation of the true atmospheric MLT CO₂ abundance compared to model simulations of CO₂ vmr.     

基于空间分割的影像条带噪声去除方法

光学遥感卫星影像中包含系统条带噪声和随机条带噪声,由于多种因素的干扰,即使进行系统条带噪声去除后,仍残留部分随机条带噪声。文章通过分析现有卫星遥感影像中的随机条带噪声特性,基于常规的随机条带噪声去除方法,提出一种新的基于空间分割的条带噪声去除算法。该方法以影像的均值、中值以及梯度值构建判定准则,将影像分为动态范围变化较小的多个区域,同时将地物边缘单独提取出来予以保留;然后采用标准矩匹配的方法对单独区域进行处理,在剔除噪声的同时抑制灰度畸变的产生;最后采用中巴地球资源卫星04星（CBERS-04）数据作为试验对象进行了随机噪声去除试验,试验结果表明新方法在去除随机条带噪声的同时很好的保持了原始影像的纹理信息。     

卫星遥感图像数据压缩质量评价研究

针对高保真高速数据压缩算法的卫星应用,采用客观参数评价和主观评价相结合的方法,对卫星遥感图像数据压缩质量评价进行了较系统的研究。通过四次试验实践表明,主观评价具有相当的客观性,是目前遥感图像数据压缩质量评价中最基本、最有效的方法,科学合理地设计主观评价至关重要;客观参数评价是有益的参考方法,在改善某一压缩方法时,峰值信噪比(PSNR)是个较好的衡量标准;主观评价和客观评价有较好的一致性,主要体现在PSNR、相似度(XSD)和全图局域最大误差(LME)等客观评价参数上。     

高光谱图像压缩感知投影与复合正则重构

压缩感知理论提供了一种新的数据获取和压缩思路,能有效地把计算负担从编码端转移到解码端。高光谱数据具备数据稀疏性、空间相关性和谱间相关性,结合这3类先验知识,提出了一种基于复合正则化的高光谱图像压缩感知投影与重构方法。该方法的编码端只需要一个简单的投影操作;在重构算法实现中,基于变量分裂的思想,把具备多个正则项的优化问题转化成多个简单的优化问题,并用迭代方式求解。实验结果表明,本文算法在高光谱图像重构上能获得更高的峰值信噪比和更好的重构效果。该方法具备极低的编码复杂度,适用于资源受限的机载和星载高光谱成像平台。     

基于稀疏随机阵列配置的CS-MIMO雷达感知矩阵构造

压缩感知(CS)理论中的感知矩阵在观测数据获取和信号重建过程中起关键性作用。目前,大部分研究通过引入高斯随机矩阵作为测量矩阵实现压缩观测,这类测量矩阵对硬件要求很高,工程实现困难。提出了一种基于稀疏随机阵列配置的压缩感知-多输入多输出(CS-MIMO)雷达中的感知矩阵构造方法,当MIMO雷达阵元配置为满足某种概率分布的稀疏随机阵列时,发射与接收导引矢量的Kronecker积能够起到压缩测量的作用。从理论上分析了所构造的感知矩阵的归一化互相关系数、Gram矩阵以及阵列方向图之间的内在联系,并证明了当随机阵元位置满足均匀分布时所构造的感知矩阵满足压缩感知重构条件。在这种稀疏随机阵列配置方式下,既可以避免额外引入随机测量矩阵,又能减少所需的阵元个数,从而大大降低CS-MIMO雷达系统复杂度。仿真实验表明,该方法具有较低的感知矩阵归一化互相关系数,与满阵CS-MIMO雷达相比能够在减少阵元个数的同时获得良好的重构性能,且使重构所需运算量大大降低。     

CT local reconstruction of solid rocket motor based on PI-POCS-TVM

In order to test the defects of solid rocket motor (SRM) accurately and efficiently, the computed tomography (CT) inspection scheme for SRMs defects was investigated and a CT local reconstruction algorithm called prior information projection onto convex sets total variation minimization (PI-POCS-TVM) was developed. The SRM was first inspected by industrial CT (ICT) to generate a low resolution SRM image used as the prior information, then high resolution local inspection was carried out for SRM's defects. To validate the effectiveness of the CT inspection scheme for SRMs defects, one SRM was inspected by a narrow fan beam ICT system. Filtered back projection (FBP) algorithm, POCS, POCS-TVM and PI-POCS-TVM algorithms were applied to reconstruct CT images. The performance of these algorithms was also compared. Results demonstrated the effectiveness of the CT inspection scheme for SRM's defects. Moreover, the PI-POCS-TVM algorithm has better local reconstruction image quality than the other three algorithms, showing great significance for accurate measurement of SRM's defects.      

飞机起落架噪声源定位的压缩感知算法

目前针对飞机起落架噪声源定位的研究方法主要是将麦克风阵列与波束成形算法相结合。常规波束成形（CBF）算法在计算时存在主瓣宽度过宽、结果易受旁瓣影响的问题。高级波束成形算法在计算时效率较差,有时会有违背物理现象的假声源出现。提出了一种将正交匹配追踪（OMP）算法与奇异值分解（SVD）相结合的起落架噪声源定位的OMP-SVD压缩感知算法。在消声实验室内进行飞机起落架噪声源定位试验,将OMP-SVD算法、CBF算法和OMP算法在不同频率下获得的结果进行对比。试验结果表明：①与OMP算法相比,OMP-SVD算法在不同频率下均能准确定位出起落架主声源;②与CBF算法相比,OMP-SVD算法显著提高了分辨率。