Estimation and compensation of ionospheric delay for SAR interferometry

Brcic, Ramon; Parizzi, Alessandro; Eineder, Michael; Bamler, Richard; Meyer, Franz J.

doi:10.1109/igarss.2010.5652231

Cited by 68 publications

(69 citation statements)

References 3 publications

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“…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]. These methods can generally be divided into two main categories: (1) the range split-spectrum methods are based on …”

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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“…In recent years, several possible methods for the InSAR ionospheric correction have been published, which contains the autofocus techniques to estimate the absolute ionosphere and other techniques to estimate the differential one (Meyer, 2010). However, the former techniques are not able to capture the relatively small irregularities with sufficient accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…The group delay method requires establishing a linear regression between the group delay and the phase advance to estimate the ionosphere phase delay. In fact, the unwanted accuracy of this method is derived for the low precision of the group delay and the low spatial resolution (Brcic, 2010). The Faraday rotation method exploits the quad-polarized measurements to estimate the Faraday rotation angle and the TEC level.…”

Section: Introductionmentioning

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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“…Decorrelation noise is reduced by acquiring images more frequently, increasing bandwidth and using a longer wavelength. Ionospheric phase delay can be estimated using a split-bandwidth system [92], [93], as it is frequency dependent, and tropospheric phase delay could be estimated using a system that simultaneously acquires data in a forward and backward looking direction. The accuracy of precise orbits continues to improve, as do elevation models, reducing residual geometric errors.…”

Section: Looking To the Futurementioning

confidence: 99%

Remote Sensing of Volcanic Hazards and Their Precursors

2012

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Ash, tephra and gas ejected during explosive eruptions provides a major far-reaching threat to population, health and air traffic. Lava flows, lahars and floods from ice capped volcanoes can also have a major influence, as well as landslides that have a potential for tsunami generation if they reach into sea or lakes. Remote sensing contributes to the mitigation of these hazards through the use of synthetic aperture radar interferometry (InSAR) and spectroradiometry. In the case of InSAR, displacements of a volcano's surface can be interpreted in terms of magma movement beneath the ground. Thus the technique can be used to identify precursors to eruptions and to track the evolution of eruptions. Recent advances in algorithm development enable relative displacements over many km to be measured with an accuracy of only a few mm. Spectroradiometry on the other hand allows monitoring of a volcanic eruption through the detection of hot-spots, and monitoring and quantification of the ash and SO 2 emitted by volcanoes into the atmosphere. The tracking of ash plumes during eruptions assists in the identification of areas that should be avoided by aircraft. Here we present a review of these two remote sensing techniques, and their application to volcanic hazards.

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Estimation and compensation of ionospheric delay for SAR interferometry

Cited by 68 publications

References 3 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

Remote Sensing of Volcanic Hazards and Their Precursors

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