基于重构距离向分谱法的时序InSAR电离层校正及分析

毛文飞; 王晓文; 刘国祥; 杨友涛; 向卫; 蔡嘉伦; 符茵; 张瑞

doi:10.3969/j.issn.0258-2724.20210541

基于重构距离向分谱法的时序InSAR电离层校正及分析

doi: 10.3969/j.issn.0258-2724.20210541

毛文飞^1,,
王晓文^{1, 2},
刘国祥^{1, 2},
杨友涛^{1, 2},
向卫¹,
蔡嘉伦¹,
符茵¹,
张瑞^{1, 2, ,}

1.
西南交通大学地球科学与环境工程学院，四川成都611756
2.
西南交通大学高速铁路运营安全空间信息技术国家地方联合工程实验室，四川成都611756

基金项目: 国家自然科学基金（41804009, 42071410, 41771402）；四川省科技计划（2020YJ0322, 2020JDTD0003, 2018JY0664, 2019ZDZX0042, 2020JDTD0003, 2020YJ0322）

详细信息

作者简介:
毛文飞（1990—），男，博士研究生，研究方向为InSAR电离层估计与校正及形变监测与分析，E-mail：wenfeimao@my.swjtu.edu.cn

通讯作者:
张瑞（1982—），男，副教授，博士，研究方向为定量遥感和合成孔径雷达干涉测量，E-mail：zhangrui@swjtu.edu.cn

中图分类号: P237
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- 被引次数: 30
出版历程
- 收稿日期: 2021-07-05
- 修回日期: 2022-01-07
- 网络出版日期: 2024-03-20
- 刊出日期: 2022-04-11

Ionospheric Correction and Analysis for Time-Series InSAR Based on Reformulating Range Split Spectrum Interferometry

MAO Wenfei^1
,,
WANG Xiaowen^{1, 2},
LIU Guoxiang^{1, 2},
YANG Youtao^{1, 2},
XIANG Wei¹,
CAI Jialun¹,
FU Yin¹,
ZHANG Rui^{1, 2
, ,}

1.
Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
2.
State-Province Joint Engineering Laboratory of Spatial Information Technology of High-Speed Rail Safety, Southwest Jiaotong University, Chengdu 611756, China

摘要

摘要:
合成孔径雷达干涉技术（InSAR）受电离层延迟影响较大，特别是在低高纬地区，用于时序InSAR解算的干涉对数量大大减少，严重影响了低频合成孔径雷达（SAR）系统的监测精度. 针对该问题，引入重构距离向分谱法（RRSSI），将其扩展为时序InSAR电离层误差估计与校正方法. 为测试方法性能，获取2006年6月至2010年8月间覆盖阿拉斯加Anaktuvuk河区域的ALOS-1 PALSAR数据进行实验. 实验结果表明：本文方法能够有效估计时序InSAR结果中的电离层误差，且对小空间尺度电离层扰动具有较高的敏感性；经提出方法校正后，研究区域的年平均形变速率均值从校正前的1.46 cm/a降至0.49 cm/a，而标准差则从1.16 cm/a降至0.65 cm/a，精度显著提升；选取时序点的累积形变由校正前的大幅波动变得更加平稳，更符合形变规律.
- 小基线集-InSAR /
- 电离层校正 /
- 距离向分谱法 /
- 时序
Abstract:
Interferometric synthetic aperture radar (InSAR) is greatly affected by ionospheric delay, especially at low and high latitudes, which decreases the number of available interferometric pairs for time-series InSAR and the monitoring accuracy of low-frequency SAR systems. To this end, the reformulating range split spectrum interferometry (RRSSI) was introduced for the ionospheric error estimation and correction in time-series InSAR. The performance of the proposed method was tested by ALOS-1 PALSAR images covering the Anaktuvuk River area in Alaska from June 2006 to August 2010. The experimental results show that the proposed method can effectively estimate the ionospheric errors of time-series InSAR results and is sensitive to ionospheric disturbances at small spatial scales. After correction, the average annual deformation rate in the study area decreases from 1.46 to 0.49 cm/year, and the standard deviation from 1.16 to 0.65 cm/year, indicating an improvement in monitoring accuracy. Additionally, the cumulative deformation of the selected time-series points becomes more stable than the large fluctuation before correction, which is more consistent with the real deformation.
- SBAS-InSAR /
- ionospheric correction /
- range split spectrum method /
- time series

HTML全文

图 1 时序InSAR电离层延迟估计与校正

Figure 1. Delay estimation and correction for time-series InSAR ionospheric

下载: 全尺寸图片幻灯片

图 2 研究区域及SAR数据覆盖范围

Figure 2. Study area and SAR data coverage

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图 3 电离层校正前后的重缠绕差分InSAR干涉图

Figure 3. Rewrapped differential InSAR interferograms before and after ionospheric correction

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图 4 年平均形变速率及统计

Figure 4. Average annual deformation rate and statistics

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图 5 时序点的累积形变曲线

Figure 5. Cumulative deformation curve of time series points

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图 6 RRSSI方法与RSSI方法的电离层校正对比

Figure 6. Comparison of ionospheric correction between RRSSI method and RSSI method

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参考文献(26)

[1]	WRIGHT P A, QUEGN S, WHEADON N S, et al. Faraday rotation effects on L-band spaceborne SAR data[J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41(12):2735-2744.
[2]	PI X Q. Ionospheric effects on spaceborne synthetic aperture radar and a new capability of imaging the ionosphere from space[J]. Space Weather,2015,13(11):737-741.
[3]	MEYER F, BAMLER R, JAKOWSKI N, et al. The potential of low-frequency SAR systems for mapping ionospheric TEC distributions[J]. IEEE Geoscience and Remote Sensing Letters,2006,3(4):560-564.
[4]	MAO W F, LIU G X, WANG X W, et al. An InSAR ionospheric correction method based on variance component estimation with integration of MAI and RSS measurements[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021,14:1423-1433. doi: 10.1109/JSTARS.2020.3045267
[5]	ZHANG B C, DING X L, ZHU W, et al. Mitigating ionospheric artifacts in coseismic interferogram based on offset field derived from ALOS-PALSAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2016,9(7):3050-3059. doi: 10.1109/JSTARS.2016.2533441
[6]	KAZUO O C. Recent trend and advance of synthetic aperture radar with selected topics[J]. Remote Sensing,2013,5(2):716-807.
[7]	ROTT H. Advances in interferometric synthetic aperture radar (InSAR) in earth system science[J]. Progress in Physical Geography: Earth and Environment,2009,33(6):769-791. doi: 10.1177/0309133309350263
[8]	刘国祥,陈强,罗小军,等. InSAR原理与应用[M]. 北京: 科学出版社, 2019.
[9]	AOKI Y, FURUYA M, DE ZAN F, et al. L-band synthetic aperture radar: current and future applications to earth sciences[J]. Earth, Planets and Space,2021,73(1):1-4. doi: 10.1186/s40623-020-01323-x
[10]	RAUCOULES D, DE MICHELE M. Assessing ionospheric influence on L-band SAR data: implications on coseismic displacement measurements of the 2008 Sichuan earthquake[J]. IEEE Geoscience and Remote Sensing Letters,2010,7(2):286-290.
[11]	JUNG H S, LEE D T, LU Z, et al. Ionospheric correction of SAR interferograms by multiple-aperture interferometry[J]. IEEE Transactions on Geoscience and Remote Sensing,2013,51(5):3191-3199. doi: 10.1109/TGRS.2012.2218660
[12]	WEGMULLER U, STROZZI T, WERNER C. Ionospheric path delay estimation using split-beam interferometry[C]//2012 IEEE International Geoscience and Remote Sensing Symposium. Munich: IEEE, 2012: 3631-3634.
[13]	FREEMAN A F. Calibration of linearly polarized polarimetric SAR data subject to faraday rotation[J]. IEEE Transactions on Geoscience and Remote Sensing,2004,42(8):1617-1624.
[14]	ZHU W, JUNG H S, CHEN J Y. Synthetic aperture radar interferometry (InSAR) ionospheric correction based on faraday rotation: two case studies[J]. Applied Sciences,2019,9(18):3871.1-3871.19.
[15]	GOMBA G, PARIZZI A, DE ZAN F, et al. Toward operational compensation of ionospheric effects in SAR interferograms: the split-spectrum method[J]. IEEE Transactions on Geoscience and Remote Sensing,2015,54(3):1446-1461.
[16]	FATTAHI H, SIMONS M, AGRAM P. InSAR time-series estimation of the ionospheric phase delay: an extension of the split range-spectrum technique[J]. IEEE Transactions on Geoscience and Remote Sensing,2017,55(10):5984-5996.
[17]	GOMBA G, DE ZAN F, PARIZZI A. Ionospheric phase screen and ionospheric azimuth shift estimation combining the split-spectrum and multi-squint methods[C]//Proceedings of EUSAR 2016: 11th European Conference on Synthetic Aperture Radar. Hamburg: VDE, 2016: 1-4.
[18]	LIANG C R, LIU Z, FIELDING E J, et al. InSAR time series analysis of L-band wide-swath SAR data acquired by ALOS-2[J]. IEEE Transactions on Geoscience and Remote Sensing,2018,56(8):4492-4506. doi: 10.1109/TGRS.2018.2821150
[19]	LIANG C R, AGRAM P, SIMONS M, et al. Ionospheric correction of InSAR time series analysis of C-band sentinel-1 TOPS data[J]. IEEE Transactions on Geoscience and Remote Sensing,2019,57(9):6755-6773.
[20]	WEGMÜLLER U, WERNER C, FREY O, et al. Reformulating the split-spectrum method to facilitate the estimation and compensation of the ionospheric phase in SAR interferograms[J]. Procedia Computer Science,2018,138:318-325. doi: 10.1016/j.procs.2018.10.045
[21]	BERARDINO P, FORNARO G, LANARI R, et al. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J]. IEEE Transactions on Geoscience and Remote Sensing,2002,40(11):2375-2383.
[22]	ZHANG Y, FATTAHI H, AMELUNG F. Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction[J]. Computers & Geosciences,2019,133:104331.1-104331.29.
[23]	JONES B M, KOLDEN C A, JANDT R, et al. Fire behavior, weather, and burn severity of the 2007 anaktuvuk river tundra fire, north slope, Alaska[J]. Arctic, Antarctic, and Alpine Research,2009,41(3):309-316. doi: 10.1657/1938-4246-41.3.309
[24]	LIU L, JAFAROV E E, SCHAEFER K M, et al. InSAR detects increase in surface subsidence caused by an Arctic tundra fire[J]. Geophysical Research Letters,2014,41(11):3906-3913. doi: 10.1002/2014GL060533
[25]	LIAO H. Ionospheric correction of interferometric sar data with application to the cryospheric sciences[D]. Alaska Fairbanks: University of Alaska Fairbanks, 2018.
[26]	ZHANG B. Mitigation of ionospheric artifacts in InSAR data for estimating earthquake deformation[D]. Hong Kong: The Hong Kong Polytechnic University, 2020.

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