气候变化领域集成服务门户(CCPortal): A Kalman Filter Time Series Analysis Method for InSAR

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DOI	10.1029/2019JB019150
	A Kalman Filter Time Series Analysis Method for InSAR
	Dalaison M.; Jolivet R.
发表日期	2020
ISSN	21699313
卷号	125 期号:7
英文摘要	Earth orbiting satellites, such as Sentinel 1A-B, build up an ever-growing set of synthetic aperture radar images of the ground. This conceptually allows for real-time monitoring of ground displacements using Interferometric Synthetic Aperture Radar (InSAR), notably in tectonically active regions such as fault zones or over volcanoes. We propose a Kalman filter for InSAR time series analysis (KFTS), an efficient method to rapidly update preexisting time series of displacement with data as they are made available, with limited computational cost. KFTS solves together for the evolution of phase change with time and for a parametrized model of ground deformation. Synthetic tests of the KFTS reveal exact agreement with the equivalent weighted least squares solution and a convergence of descriptive model parameter after the assimilation of about 1 year of data. We include the impact of sudden deformation events such as earthquakes or slow slip events on the time series of displacement. First tests of the KFTS on ENVISAT data over Mt. Etna (Sicily) and Sentinel 1 data around the Chaman fault (Afghanistan, Pakistan) show precise (±0.05 mm) retrieval of phase change when data are sufficient. Otherwise, the optimized parametrized model is used to forecast phase change. Good agreement is found with classic time series analysis solution and GPS-derived time series. Accurate estimates are conditioned to the proper parametrization of errors so that models and observations can be combined with their respective uncertainties. This new tool is freely available to process ongoing InSAR time series. ©2020. American Geophysical Union. All Rights Reserved.
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187781
作者单位	École Normale Supérieure, PSL Université, CNRS U.M.R. 8538, Laboratoire de Géologie, Paris, France; Institut Universitaire de France, Paris, France
推荐引用方式 GB/T 7714	Dalaison M.,Jolivet R.. A Kalman Filter Time Series Analysis Method for InSAR[J],2020,125(7).
APA	Dalaison M.,&Jolivet R..(2020).A Kalman Filter Time Series Analysis Method for InSAR.Journal of Geophysical Research: Solid Earth,125(7).
MLA	Dalaison M.,et al."A Kalman Filter Time Series Analysis Method for InSAR".Journal of Geophysical Research: Solid Earth 125.7(2020).