GNSS水汽层析的自适应代数重构算法  

Adaptive Algebraic Reconstruction Algorithms for GNSS Water Vapor Tomography

作　　者：张文渊 张书毕[1,2] 左都美[3] 丁楠 刘鑫[1,2] ZHANG Wenyuan;ZHANG Shubi;ZUO Dumei;DING Nan;LIU Xin(School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China;Jiangsu Key Laboratory of Resources and Environmental Information Engineering,China University of Mining and Technology,Xuzhou 221116,China;Nanjing Institute of Surveying,Mapping and Geotechnical Investigation,Co.Ltd,Nanjing 210019,China;School of Geography,Geomatics and Planning,Jiangsu Normal University,Xuzhou 221116,China)

机构地区：[1]中国矿业大学环境与测绘学院,江苏徐州221116 [2]中国矿业大学江苏省资源环境信息工程重点实验室,江苏徐州221116 [3]南京市测绘勘察研究院有限公司,江苏南京210019 [4]江苏师范大学地理测绘与城乡规划学院,江苏徐州221116

出　　处：《武汉大学学报（信息科学版）》2021年第9期1318-1327,共10页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金(41774026,41904013);陕西省自然科学基础研究计划(2020JQ-738)。

摘　　要：代数重构算法在对流层三维水汽反演中具有一定的优势,系统研究了加法代数重构、乘法代数重构、联合代数重构这3种算法,并发展了自适应代数重构算法。该算法针对3种传统算法中误差分配的不足进行了改正,提出了顾及体素块水汽密度变化对全球导航卫星系统(global navigation satellite system, GNSS)斜路径水汽含量影响的动态误差分配原则。此外,将基于GNSS信号的高度角定权模型引入到该算法中,使层析结果更靠近高精度的观测值。利用2016年7月徐州连续运行基准站系统的GNSS实测数据和探空站数据对该算法进行分析,试验结果表明,3种自适应算法反演的水汽密度的均方根误差、标准差、平均绝对偏差都低于传统算法,其中,均方根误差分别降低了25.91%、15.81%和24.64%。在小雨、中雨、大雨3种天气条件下,自适应代数重构算法的水汽廓线分布均优于传统算法的结果,其中,自适应联合代数重构算法反演的水汽廓线与探空廓线最一致。Objectives:Global navigation satellite system(GNSS) tomography, characterized by reconstructing the three-dimensional distribution of the atmospheric water vapor, has proved its capacity for studying the extreme weather events. The ill-conditioned problem resulting from the GNSS acquisition geometry is the critical issue of the GNSS tomography system. Algebraic reconstruction techniques, with the advantages of simple iteration and fast convergence, has been widely applied to the tropospheric tomography. However, the error allocation principle based on the intersection length of GNSS rays with each ray-voxel affects the accuracy of tomographic results. An improved adaptive algebraic reconstruction techniques are proposed to address this problem.Methods:In view of the unreasonable error allocation in the traditional algorithm, we suggest a new error allocation principle based on the variation of water vapor density(WVD) in voxels for the adaptive algorithms, in which the product of the intersection length and WVD is considered as a new principle to redistribute the difference between the GNSS slant water vapor(SWV)and the reconstructed SWV. Besides, the weight matrix model of elevation angles is introduced to the improved algorithm to optimize the tomographic results.Results:The new algorithms are tested by measured data from Xuzhou continuously operating reference stations(CORS) network and radiosonde during July2016. Experimental results reveal that the WVD derived from the adaptive algorithms performs better than that of the general algorithms in root mean squared error(RMSE), standard deviation(STD) and mean absolute error(MAE), and the RMSE is decreased by 25.91%, 15.81%, and 24.64% for adaptive algebraic reconstruction technique(AART), adaptive multiplicative algebraic reconstruction technique(AMART)and adaptive simultaneous iterative reconstruction technique(ASIRT) respectively. Under the conditions of light rain, moderate rain and heavy rain, the adaptive algorithms retrieve better water vapor profile than

关 键 词：全球导航卫星系统 对流层层析 自适应代数重构算法 水汽密度 高度角定权 

分 类 号：P228[天文地球—大地测量学与测量工程]