测绘学报 ›› 2016, Vol. 45 ›› Issue (10): 1200-1209.doi: 10.11947/j.AGCS.2016.20150457

• 摄影测量学与遥感 • 上一篇    下一篇

干涉图像第二类统计Goldstein自适应滤波方法

赵文胜, 蒋弥, 何秀凤   

  1. 河海大学地球科学与工程学院, 江苏 南京 211100
  • 收稿日期:2015-09-10 修回日期:2016-07-28 出版日期:2016-10-20 发布日期:2016-11-08
  • 通讯作者: 蒋弥 E-mail:mijiang@hhu.edu.cn
  • 作者简介:赵文胜(1985-),男,博士生,研究方向为InSAR数据处理与应用。E-mail:wensheng_zh@hhu.edu.cn
  • 基金资助:

    国家自然科学基金(41404009;41274017);国家科技支撑计划(2015BAB07B10);国家测绘地理信息局测绘基础研究基金(15-01-04);江苏省交通运输科技与成果转化项目(16Y08)

Improved Adaptive Goldstein Interferogram Filter Based on Second Kind Statistics

ZHAO Wensheng, JIANG Mi, HE Xiufeng   

  1. School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China
  • Received:2015-09-10 Revised:2016-07-28 Online:2016-10-20 Published:2016-11-08
  • Supported by:

    The National Natural Science Foundation of China (Nos. 41404009;41274017);The National Key Technology Research and Development Program(No.2015BAB07B10);The Surveying and Mapping Basic Research Program of National Administration of Surveying, Mapping and Geoinformation (No.15-01-04);The Transportation Technology and Achievements Transformation Project of Jiangsu Province(No.16Y08)

摘要:

干涉图滤波是InSAR数据处理中的关键步骤之一,滤波结果的优劣会直接影响到相位观测的质量和最终产品精度。本文结合干涉图滤波算法的研究进展,对Goldstein频率域滤波及其经典改进算法进行了系统分析和比较,在此基础上提出了一种基于第二类统计的稳健相干性估计量的Goldstein自适应滤波方法。本文采用模拟数据和Envisat ASAR真实数据与现有方法进行了验证,试验结果表明,新的滤波方法在保持细节和抑制噪声方面优势更加明显。

关键词: Goldstein滤波, 相位噪声, 第二类统计, 相干系数

Abstract:

Interferometric filtering is one of the most important procedures in InSAR data processing as it refers to the quality of phase observations and the final products. A variant under the framework of Goldstein filter is presented in this paper, which is based on the robust coherence estimator from the second kind statistics. Compared with the state-of-the-art, the significant advantage of the new method is that more accurate filtering parameter alpha can be deduced and therefore better performance of the Goldstein filtering can be expected. Experimental results from both simulation and real Envisat ASAR data demonstrate the value of the method.

Key words: Goldstein filter, phase noise, second kind statistics, coherence

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