Time Series InSAR Ionospheric Delay Estimation, Correction, and Ground Deformation Monitoring With Reformulating Range Split-Spectrum Interferometry

被引：9

作者：

Mao, Wenfei ^{[1
,2
]}

Wang, Xiaowen ^{[1
]}

Liu, Guoxiang ^{[1
]}

Pirasteh, Saied ^{[1
,3
]}

Zhang, Rui ^{[1
]}

Lin, Hui ^{[4
]}

Xie, Yakun ^{[1
]}

Xiang, Wei ^{[5
]}

Ma, Zhangfeng ^{[6
]}

Ma, Peifeng ^{[2
]}

机构：

[1] Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Dept Surveying & Geoinformat, Chengdu 610031, Peoples R China

[2] Chinese Univ Hong Kong, Inst Space & Earth Informat Sci, Hong Kong, Peoples R China

[3] Shaoxing Univ, Inst Artificial Intelligence, Sch Mech & Elect Engn, Shaoxing 312000, Peoples R China

[4] Jiangxi Normal Univ, Sch Geog & Environm, Nanchang 330022, Peoples R China

[5] Chinese Acad Sci, Aerosp Informat Res Inst, Space Microwave Remote Sensing Syst Dept, Beijing 100094, Peoples R China

[6] Hohai Univ, Sch Earth Sci & Engn, Nanjing 211100, Peoples R China

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2023年 / 61卷

基金：

中国国家自然科学基金;

关键词：

Ground deformation; ionospheric delay; reformulating range split-spectrum interferometry (Re-RSSI); time series interferometric synthetic aperture radar (TS-InSAR); SENTINEL-1; TOPS; CENTRAL ANDES; PHASE DELAY; RADAR; COMPENSATION; UPLIFT;

D O I：

10.1109/TGRS.2023.3298919

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Ionospheric phase delay is a critical error source in time series interferometric synthetic aperture radar (TS-InSAR) for the purpose of monitoring ground surface deformation with SAR data obtained from low-frequency radar systems. Recently, the range split-spectrum interferometry (RSSI) method has been employed to estimate and rectify ionospheric errors in TS-InSAR. However, the performance of the RSSI method is largely restricted by the significant linear scale factors resulting from the current small SAR bandwidth. In this study, we propose a reformulating RSSI (Re-RSSI)-based method for correcting the ionospheric error in TS-InSAR by optimizing the linear scale factors, with the aim of improving the accuracy of TS-InSAR measurements. We evaluate the Re-RSSI method using 121 ALOS-1 PALSAR images that cover two distinct regions: the low-latitude Lazufre volcano region and the high-latitude Anaktuvuk River tundra fire region. Our results demonstrate that the Re-RSSI method can effectively remove time series ionospheric errors at both test sites, where we detected ionospheric delays of approximately 2.5 cm/year (yr) and 2.0 cm/yr, respectively. Using Global Navigation Satellite System (GNSS) measurements as ground truth, we achieved an 86.59% improvement rate in the root-mean-square error (RMSE) with the Re-RSSI method, which is significantly higher than the 66.40% improvement rate achieved with the traditional RSSI method.

引用

页数：18