基于消息中间件技术的分布式气象数据同步系统设计和实现

本文针对新的资料传输流程建立后江苏省气象数据实时共享需求,基于消息中间件技术,设计并实现了一种省市气象数据同步系统。提出数据同步系统的总体架构和实现方案,基于业务需求设计了数据库表和消息模型,开发了数据同步状态信息查询Web页面。目前系统已在全省多个地市部署应用,为省市县3级气象业务提供稳定、及时有效的数据支撑,取得较好的应用效果。     

孤岛分布式能源系统的反步控制策略研究

针对含分布式能源（DER）的微电网在孤岛运行模式下自身调节能力有限的问题,基于反步控制方法设计了一种DER系统孤岛运行电压控制策略,解决了DER系统在孤岛运行模式下的电压控制问题.首先,给出了孤岛运行模式下DER系统模型及输出电压数学模型;其次,利用反步控制方法设计了控制器,同时利用李雅普诺夫稳定性理论进行了稳定性分析;最后,利用此控制器在平衡负载及不平衡负载的情况下对输出电压进行控制,并通过仿真验证了反步控制器的有效性.     

基于相对状态符号信息的分布式优化算法

针对网络化多智能体的分布式优化问题,本文讨论一种只利用邻居相对状态的符号信息的分布式算法.该算法不要求与图相关的权重矩阵是双随机矩阵.首先利用优化理论中的惩罚函数法解释该算法,然后分析算法在静态图上的收敛性以及收敛速度.与现有使用邻居相对状态的完整信息的分布式梯度下降算法相比,所提算法的收敛速度并没有本质上降低.另一方面,将所提算法扩展到确定性和随机性的时变图上,并给出相应的收敛性结论.最后,通过数值仿真实验验证算法的有效性.     

基于北斗GEO卫星的磁暴期间电离层TEC响应分析

基于亚太地区北斗GEO卫星数据对2017-05发生在中低纬度地区的磁暴现象进行研究,并使用北斗GEO卫星获取的TEC实测数据对全球电离层图的精度进行评估。进一步对磁暴引起的全球电离层TEC变化进行分析发现,电离层TEC对磁暴的响应出现在磁暴主相开始1~4 h之后,最大扰动值达到20 TECu以上。     

一种由粗到精的光学与SAR遥感图像配准算法

由于光学遥感图像和SAR图像具有明显的非线性强度差异,且SAR图像存在斑点噪声,使得其配准存在较大难度。为此,本文结合基于特征和基于区域图像配准方法的优点,并组合为混合模型,提出一种由粗到精的自动配准算法。以光学遥感图像和SAR图像分别为参考图像和待配准图像,先以基于特征点的SAR-SIFT完成粗配准,再以基于区域的ROEWA-HOG完成精配准。① 采用SAR-SIFT算法进行特征点检测和特征匹配来计算图像的仿射变换模型,以消除参考图像和待配准图像之间明显的旋转、尺度和平移差异,至此完成图像粗配准;② 在此基础上利用分块Harris角点检测在参考图像上获得特征点,并根据特征点确定待配准图像上的同名点搜索区域;③ 计算图像的ROEWA梯度,构造以特征点为中心的模板区域内的HOG特征向量,以SSD作为相似性测度搜索待配准图像上的同名点,完成高精度的图像配准;④ 进行图像配准实验,对配准结果进行目视检查和精度评估。经过多组光学与SAR图像配准实验,验证本文算法能够结合基于特征和基于区域的图像配准方法的优点,较好地抵抗光学与SAR图像之间的非线性强度、旋转、尺度、平移差异和SAR图像的噪声影响,并逐步提高配准精度,最终配准精度达到1个像素左右,实现了光学与SAR图像的高精度自动配准,能够满足光学与SAR图像后续综合应用。     

雷达卫星影像中输电导线散射斑的相位时间序列稳定性分析

分析输电导线散射斑相位的几何关系,选取20幅时间跨度约为1年的TerraSAR条带模式影像,对其中两基铁塔之间6条输电导线形成的散射斑相位时间序列进行分析。文中统计分析构成导线散射斑像元的相位离散度,其标准差约为0.2弧度,表明单个散射斑相位稳定。选取铁塔顶部点的导线散射斑为参考点,与另外5个导线散射斑做差分相位时间序列分析,分析导线之间高程差的理论计算值与实际值的一致性。分析结果显示,导线散射斑差分相位序列的波动可达2弧度以上,与导线间高程差产生的相位不一致。     

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。     

Forest classification and impact of BIOMASS resolution on forest area and aboveground biomass estimation

The European Space Agency (ESA) is currently implementing the BIOMASS mission as 7th Earth Explorer satellite. BIOMASS will provide for the first time global forest aboveground biomass estimates based on P-band synthetic aperture radar (SAR) imagery. This paper addresses an often overlooked element of the data processing chain required to ensure reliable and accurate forest biomass estimates: accurate identification of forest areas ahead of the inversion of radar data into forest biomass estimates.The use of the P-band data from BIOMASS itself for the classification into forest and non-forest land cover types is assessed in this paper. For airborne data in tropical, hemi-boreal and boreal forests we demonstrate that classification accuracies from 90 up to 97% can be achieved using radar backscatter and phase information. However, spaceborne data will have a lower resolution and higher noise level compared to airborne data and a higher probability of mixed pixels containing multiple land cover types. Therefore, airborne data was reduced to 50 m, 100 m and 200 m resolution. The analysis revealed that about 50–60% of the area within the resolution level must be covered by forest to classify a pixel with higher probability as forest compared to non-forest. This results in forest omission and commission leading to similar forest area estimation over all resolutions. However, the forest omission resulted in a biased underestimated biomass, which was not equaled by the forest commission. The results underline the necessity of a highly accurate pre-classification of SAR data for an accurate unbiased aboveground biomass estimation.     

Polarimetric differential SAR interferometry in an arid natural environment

Ground deformation measurements have contributed to a better understanding of the processes and mechanisms involved in natural hazards. Those include landslides, subsidence, earthquakes and volcanic eruptions. Spaceborne Differential Interferometric Synthetic Aperture RADAR (DInSAR) is a well studied technique for measuring ground deformation. Quality of deformation measurements, however, is often degraded by decorrelation. With the advent of fully polarimetric SAR satellite sensors, polarimetric optimization techniques exploiting polarimetric diversity improve the phase quality of interferograms. In this paper, we analyzed three polarimetric optimization methods to determine the optimal one for application in an arid natural environment. We considered coherence decomposition in single and double phase center scenarios. Coherence estimation bias associated with each optimization method has been analyzed. We compared the derived displacement values with terrestrial GPS measurements. The study shows that polarimetric optimization increases the number of coherent pixels by upto 6.89% as compared with a single polarization channel. The study concludes that polarimetric optimization coupled with DInSAR analysis yields more reliable deformation results in a low coherence region.     

顾及目标异质性的极化SAR图像非局部均值滤波

相干斑抑制是极化合成孔径雷达(Pol SAR)图像分析的重要预处理步骤。为了更好地抑制极化SAR图像中的相干斑,本文综合目标的异质性和结构信息,提出基于目标异质性的非局部均值滤波方法。首先利用K分布距离度量目标的异质性,并以异质性为基础,保留图像中的点、线等高异质性目标;然后计算图像块之间的异质性差异,最后将其作为度量非局部均值加权滤波像元相似性的权重系数,实现对Pol SAR图像的相干斑抑制。实验对比结果表明:本文方法能够有效地抑制相干斑,同时对细节信息和极化信息也具有良好的保持性,能够为后续的图像应用提供支持。