InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique

Fattahi, H.; Simons, M.; Agram, P. S.

doi:10.1109/tgrs.2017.2718566

Cited by 102 publications

(101 citation statements)

References 33 publications

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“…The L-band SAR systems are more sensitive to the ionospheric phase distortions than the X-and C-band SAR systems. Moreover, the ionospheric phase error can be particularly severe in three main regions including equatorial (such as the Amazon floodplains), middle, and high latitude regions [44,45]. In recent years, various ionospheric correction methods have been proposed for DInSAR processing [45][46][47][48][49][50].…”

Section: Ionospheric Error Removalmentioning

confidence: 99%

“…In recent years, various ionospheric correction methods have been proposed for DInSAR processing [45][46][47][48][49][50]. These methods can generally be divided into two main categories: (1) the range split-spectrum methods are based on the dispersive propagation of the ionosphere to estimate the difference of the phase delay from different wavelengths [45][46][47][48][49][50][51]; (2) the azimuth shift methods are based on the proportional relation between azimuth displacement and azimuth derivative of the ionospheric phases [52][53][54]. The azimuth displacement can be estimated by accurate coregistration or multiple-aperture interferometry (MAI) [53,54].…”

Section: Ionospheric Error Removalmentioning

confidence: 99%

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Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

et al. 2018

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Differential synthetic aperture radar (SAR) interferometry (DInSAR) has been successfully used to estimate water level changes (∂h/∂t) over wetlands and floodplains. Specifically, amongst ALOS PALSAR datasets, the fine-beam stripmap mode has been mostly implemented to estimate ∂h/∂t due to its availability of multitemporal images. However, the fine-beam observation mode provides limited swath coverage to study large floodplains and wetlands, such as the Amazon floodplains. Therefore, for the first time, this paper demonstrates that ALOS2 ScanSAR data can be used to estimate the large-scale ∂h/∂t in Amazon floodplains. The basic procedures and challenges of DInSAR processing with ALOS2 ScanSAR data are addressed and final ∂h/∂t maps are generated based on the Satellite with ARgos and ALtiKa (SARAL) altimetry's reference data. This study reveals that the local ∂h/∂t patterns of Amazon floodplains are spatially complex with highly interconnected floodplain channels, but the large-scale (with 350 km swath) ∂h/∂t patterns are simply characterized by river water flow directions.

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Section: Ionospheric Error Removalmentioning

confidence: 99%

Section: Ionospheric Error Removalmentioning

confidence: 99%

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

et al. 2018

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“…The proper bandwidth and the center carrier frequency are quite important to suppress noise amplification and maintain image information. Meanwhile, in order to improve the result, the interferometric coregistration is carefully analyzed to estimate accurate offsets to recover the coherence (Fattahi, 2017). If the coherence of interferograms formed by sub-bands SLCs are not high enough, an adaptive filter would be required to suppress the noise.…”

Section: The Range Split-spectrum Methodsmentioning

confidence: 99%

Compensation of the Ionospheric Effects on Sar Interferogram Based on Range Split-Spectrum and Azimuth Offset Methods – A Case Study of Yushu Earthquake

Zhu

Zhang

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:InSAR technique can measure the surface deformation with the accuracy of centimeter-level or even millimeter and therefore has been widely used in the deformation monitoring associated with earthquakes, volcanoes, and other geologic process. However, ionospheric irregularities can lead to the wavy fringes in the low frequency SAR interferograms, which disturb the actual information of geophysical processes and thus put severe limitations on ground deformations measurements. In this paper, an application of two common methods, the range split-spectrum and azimuth offset methods are exploited to estimate the contributions of the ionosphere, with the aim to correct ionospheric effects in interferograms. Based on the theoretical analysis and experiment, a performance analysis is conducted to evaluate the efficiency of these two methods. The result indicates that both methods can mitigate the ionospheric effect in SAR interferograms and the range split-spectrum method is more precise than the other one. However, it is also found that the range split-spectrum is easily contaminated by the noise, and the achievable accuracy of the azimuth offset method is limited by the ambiguous integral constant, especially with the strong azimuth variations induced by the ionosphere disturbance.

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“…Ionization of neutral atoms and molecules in the ionosphere from high energy solar radiation results in a mix of neutral gas molecules, free ions and electrons [17]. This influences the propagation of microwave radiation through the ionospheric layer, causing phase shifts such as phase advances and group delays, which translate as azimuth shifts and defocusing between SAR acquisitions [17,18]. Ionospheric effects have a significant impact on SAR satellite imagery acquired using longer wavelength radiation, such as L-band (~24 cm), compared to the shorter wavelengths, such as C-band (~6 cm) and X-band (~3 cm) [18].…”

mentioning

confidence: 99%

“…This influences the propagation of microwave radiation through the ionospheric layer, causing phase shifts such as phase advances and group delays, which translate as azimuth shifts and defocusing between SAR acquisitions [17,18]. Ionospheric effects have a significant impact on SAR satellite imagery acquired using longer wavelength radiation, such as L-band (~24 cm), compared to the shorter wavelengths, such as C-band (~6 cm) and X-band (~3 cm) [18]. On the other hand, tropospheric air refractivity gradients are a function of temperature, pressure, and water vapor, and all vary vertically as a function of height in the atmosphere [13,19].…”

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confidence: 99%

Assessment of Mitigation Strategies for Tropospheric Phase Contributions to InSAR Time-Series Datasets over Two Nicaraguan Volcanoes

et al. 2020

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Interferometric Synthetic Aperture Radar (InSAR) studies of ground displacement are often plagued by tropospheric artifacts, which are phase delays resulting from spatiotemporal variations in the refractivity of air within the troposphere. In this study, we focus on COSMO-SkyMed (X-band) InSAR products obtained over two different types of volcanoes in Nicaragua: the Telica stratovolcano and the Masaya caldera. We examine the applicability of an empirical linear correction method and three Global Weather Models (GWMs) with different spatial and temporal resolutions for removing the tropospheric phase component. We linearly invert the tropospheric-corrected interferograms using the Small BAseline Subset (SBAS) time-series technique to produce time-series of ground displacement. Statistical assessments were performed on the corrected interferograms to examine the significance of the applied corrections on the individual interferograms and time-series results. We find that the applicability of the correction methods is highly case-dependent and that in general, the temporal resolution of GWMs influences their ability to capture turbulent tropospheric phase delays. At the two target volcanoes, our study shows that none of the GWMs are able to accurately capture the tropospheric phase delays. Our study provides a guide for researchers using InSAR data in tropical regions who wish to use tropospheric model corrections to carefully assess the applicability of the different types of tropospheric correction methods.Remote Sens. 2020, 12, 782 2 of 30 which include the true displacement of the ground (∆φ de f ), differences in the orbital geometry of the satellite (∆φ orbit ), contributions of the topography (∆φ topo ), phase delay contributions from the ionosphere and troposphere (∆φ atm ), and other noise contributions such as instrument noise and changes in scattering properties of the ground (∆φ noise ). Topographic contributions can be accounted for by using digital elevation models [13] and orbital geometry contributions can be removed using precise satellite orbits (also known as flattening). With the improvement in satellite technology, thermally-correlated noise contributions from the instruments onboard the satellites can be assessed [14,15]. Poor coherence (low signal-to-noise ratio) pixels due to changes in the scattering properties of the ground can be masked from the ground displacement field.Atmospheric contributions, however, are more difficult to account for as they often involve phase delay contributions from both the ionosphere (60-1000 km) and troposphere (0-10 km), which can bias true ground displacement measurements [12,16]. Ionization of neutral atoms and molecules in the ionosphere from high energy solar radiation results in a mix of neutral gas molecules, free ions and electrons [17]. This influences the propagation of microwave radiation through the ionospheric layer, causing phase shifts such as phase advances and group delays, which translate as azimuth shifts and defocusing between SAR acquisitio...

show abstract

InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique

Cited by 102 publications

References 33 publications

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

Compensation of the Ionospheric Effects on Sar Interferogram Based on Range Split-Spectrum and Azimuth Offset Methods – A Case Study of Yushu Earthquake

Assessment of Mitigation Strategies for Tropospheric Phase Contributions to InSAR Time-Series Datasets over Two Nicaraguan Volcanoes

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