A Low-Power High-Resolution Broad-Band Radar Using a Pulse Compression Technique for Meteorological Application

A new high-resolution Ku-band Doppler radar for meteorological applications has been developed. With the new system design, the radar can accurately measure the radar reflectivity factor with 4-m resolution over a range from 40 m to several kilometers for 100-mW power using a pulse compression technique. Details of the system design, signal processing algorithm, and data acquisition procedures are described. To demonstrate the accuracy of the system, the radar reflectivity measurements are compared with the Joss-Waldvogel disdrometer measurements, and fairly good agreement is shown. The ability of the system to capture the backscattered signal and Doppler spectrum from rain volume at low altitude with high resolution is demonstrated for both convective- and stratiform-type rain events.     

Selection of Pulse Repetition Frequency in High-Precision Oceanographic Radar Altimeters

A readily computable formula to perform versatile analysis of the nonstationary pulse-to-pulse correlation properties of ocean altimeter returns is presented. Using this formula, the correlation coefficient and correlation interval depending on the reference time, sea state, and system parameters have been analyzed. The results have suggested that the pulse repetition frequency should adaptively be adjusted to the sea state to ensure precise altitude measurements.     

一种融合测高仪与地面GPS数据的单站电离层反演方法

电离层层析成像技术非常适用于检测电离层电子密度的大尺度空间分布及其扰动。利用地面单站的GPSTEC值和另一站的数字测高仪观测数据,结合国际参考电离层（IRI）,利用MART算法反演得到测站上空电子密度的垂直分布。利用白天和夜间的实测数据进行了CIT反演,结果表明了该方法的可靠性。     

Comparison and Integration of Radar and Optical Data for Land Use/Cover Mapping

Abstract

This study examined the complementarity of spaceborne radar and optical data for surface feature identification. RADARSAT data sets were assessed independently and in combination with Landsat Thematic Mapper (TM) multispectral data. The primary methodology was spectral signature extraction and the application of a statistical decision rule to classify the surface features for a site near Kericho, Kenya. Relative accuracy of the resultant classifications was established by digital integration and comparison to reference information derived from field visitation. Speckle filtering was a great improvement over the poor results achieved with the unfiltered, original radar data but still not adequate for accurate land cover classification. The extraction and use of Variance texture measures was found to be very advantageous. The overall results were not significant improvements over speckle removal (6% increase) but several individual classes, forest and urban, had excellent results with texture. Combinations of radar with Landsat TM greatly improved results, achieving near perfect classification of all individual classes. The highest overall accuracy was achieved with a merger that included the best individual texture image and six reflectance bands of the TM data. The systematic strategy of this study, determination of the best individual method before introducing the next procedure, was effective in managing a very complex, almost infinite set of analysis possibilities.     

Comparison of Deep Underwater Measurements and Radar Observations of Rainfall

Deep-water acoustical measurements of rainfall are compared to high-resolution ground radar observations for the first time. The measurements of underwater ambient sound were made from a subsurface mooring near Methoni, Greece, in 2004. The acoustical measurements were at 60-, 200-, 1000-, and 2000-m depths. Simultaneous ground-based polarimetric -band radar observations were made over the acoustic mooring. Comparisons show acoustic detection of rain events and storm structure that are in agreement with the radar observations. Results from a comparison between the underwater sound pressure level at different depths and the observed radar reflectivities are presented.     

Shapes on a plane: evaluating the impact of projection distortion on spatial binning

ABSTRACT

One method for working with large, dense sets of spatial point data is to aggregate the measure of the data into polygonal containers, such as political boundaries, or into regular spatial bins such as triangles, squares, or hexagons. When mapping these aggregations, the map projection must inevitably distort relationships. This distortion can impact the reader’s ability to compare count and density measures across the map. Spatial binning, particularly via hexagons, is becoming a popular technique for displaying aggregate measures of point data sets. Increasingly, we see questionable use of the technique without attendant discussion of its hazards. In this work, we discuss when and why spatial binning works and how mapmakers can better understand the limitations caused by distortion from projecting to the plane. We introduce equations for evaluating distortion’s impact on one common projection (Web Mercator) and discuss how the methods used generalize to other projections. While we focus on hexagonal binning, these same considerations affect spatial bins of any shape, and more generally, any analysis of geographic data performed in planar space.     

校准三维模型基矩阵的函数映射的对应关系计算

在利用函数映射计算模型间对应关系时,提出了一种校准三维几何模型之间基矩阵的新方法,将模型间对应关系的构建转化为由模型特征函数构建的基矩阵之间的校准运算。首先计算三维模型的Laplace算子,获得模型的特征值和特征向量,并利用所得到的特征向量构建基矩阵;其次,提出了协方差的最小值校准算法,以计算模型基矩阵之间的校准矩阵 S ,并用矩阵 S 对两个模型的函数基进行校准;最后,计算校准模型所有点的高斯曲率来采样源模型尖端特征点,并在校准后的目标模型上遍历所有点,以寻求最优对应点来构建等距变换（或近似等距变换）的三维模型间的对应关系。通过计算采样点与最优对应点的测地错误,以衡量所提算法的匹配准确率。实验结果表明,与已有算法相比,本算法可以较为准确地构建两个或多个模型间的对应关系,同时也克服了模型自身对称性影响对应关系计算的问题。     

Fusion of Radar and Optical Data for Land Cover Mapping

Abstract

This study examined the complementarity of radar and optical data for feature identification. Spaceborne radar and Landsat Thematic Mapper (TM ) multispectral data sets were assessed independently and in combination to classify a site near Wad Medani, Sudan. Radar processing procedures included speckle reduction, texture extraction and post‐processing smoothing. Relative accuracy of the resultant classifications was established by comparison to ground truth information derived from field visitation. Neither speckle filtering nor post‐classification smoothing were improvements over the poor results obtained with the unfiltered, original radar data. Texture measures were significant improvements over the original data (20 percent overall accuracy increase) and several, but not all, individual classes had excellent results. Landsat TM had good overall results (80 percent correct) but considerable spectral confusion between urban and bare soil. Combination of radar with Landsat TM greatly improved results, achieving near perfect classification of all individual classes. The systematic strategy of this study, determination of the best individual method before introducing the next procedure, was effective in managing a complex set of analysis possibilities.     

全极化SAR数据的最大后验概率分类

结合后验概率对分类的影响和全极化SAR数据特点,提出了一种全极化SAR数据分类方法。首先将全极化SAR数据的协方差矩阵转换为9个服从正态分布的强度量;然后通过迭代分类计算类别出现的概率,对9个强度量进行基于最大后验概率的分类。以黑龙江省逊克县境内的一景ALOS PALSAR全极化数据为例,用该方法进行分类,总体精度和Kappa系数分别达到81.34%和0.84,优于传统的最大似然分类方法。