丁晓利3,
李志伟4
1. 河海大学水文水资源与水利工程科学国家重点实验室, 南京 210098
2. 河海大学地球科学与工程学院, 南京 211100
3. 香港理工大学土地与地理资讯学系, 九龙 香港
4. 中南大学地球科学与信息物理学院, 长沙 410083
基金项目: 国家自然科学基金（41774003），江苏省自然科学基金（BK20171432），中央高校基本科研业务费专项资金资助（2018B17714），空间信息智能感知与服务深圳市重点实验室（深圳大学）开放基金资助项目（20165006212），中欧龙计划项目第四期（32248_2）资助
详细信息
作者简介: 蒋弥, 男, 1982年生, 副教授, 主要从事InSAR研究.E-mail:mijiang@hhu.edu.cn
中图分类号: P228 收稿日期:2017-08-06
修回日期:2017-12-27
上线日期:2018-12-05
Homogeneous pixel selection algorithm for multitemporal InSAR
JIANG Mi1,2,,DING XiaoLi3,
LI ZhiWei4
1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
2. School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China
3. The Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China
4. School of Geoscience and Info-Physics, Central South University, Changsha 410083, China
MSC: P228
--> Received Date: 06 August 2017
Revised Date: 27 December 2017
Available Online: 05 December 2018
摘要
摘要:分布式雷达目标时序InSAR技术是目前InSAR形变监测领域的主流方向，其中同质样本选取是该技术的基础，其估计精度直接影响SAR影像分辨率与后续参数解算精度.本文在追踪最新研究进展之上，系统回顾了当今统计同质选点算法的优缺点.在参数与非参数两类统计方法的应用中，采用蒙特卡罗方法和真实数据验证定量比较算法差异以及适用场景.根据之前的研究结论，提出一种改进的最优参数统计同质样本选择方法.最后，论文介绍了团队研发的MATLAB开源工具包，涵盖了同质样本提取和时序InSAR协方差矩阵估计两部分内容，为InSAR科研人员和后续数据处理提供高质量、全分辨率的观测源.
关键词: 分布式目标/
时序InSAR/
同质样本选择/
协方差矩阵估计/
开源工具包
Abstract:Synthetic Aperture Radar Interferometry (InSAR) technique for distributed scatterers has become one of the current flavors. Inaccurate estimation of the covariance matrix is regarded as the most important source of error in such applications. The previous studies, named statistically homogeneous pixel selection algorithms, have demonstrated their values to refine the estimate accuracy for each target without loss of image resolution. In this paper, we review these methods globally under parametric and non-parametric statistical framework. The updated one will then be presented by integrating the advantages of the parametric statistics, and evaluated through synthetic and real data. Based on these algorithms, we finally introduce our SHPS-InSAR open-source toolbox, designed for homogeneous pixel selection and covariance matrix estimation. The toolbox includes almost all methods presented in this paper and tries to provide the optimal observable for the researchers in the field.
Key words:Distributed targets/
Multi-temporal InSAR/
Homogeneous pixel selection/
Covariance matrix estimation/
Open-source toolbox
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http://www.geophy.cn/data/article/export-pdf?id=dqwlxb_14782
