Methods and Performances for Multi-Pass SAR Interferometry

Tebaldini, Stefano; Guarnieri, Andrea Monti

doi:10.5772/9112

Cited by 15 publications

(11 citation statements)

References 22 publications

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“…Each step will be explained in this section of the paper. A model describing the decorrelation of a general distributed scatterer has been described in [18,30].…”

Section: Processing Schemementioning

confidence: 99%

Joint Exploitation of SAR and GNSS for Atmospheric Phase Screens Retrieval Aimed at Numerical Weather Prediction Model Ingestion

Manzoni

Guarnieri

Realini³

et al. 2020

Remote Sensing

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This paper proposes a simple and fast method to estimate Atmospheric Phase Screens (APSs) by jointly exploit a stack of Synthetic Aperture Radar (SAR) images and a dataset of GNSS-derived atmospheric product. The output of this processing is conceived to be ingested by Numerical Weather Prediction Models (NWPMs) to improve weather forecasts. In order to provide wide and dense area coverage and to respect requirements in terms of spatial resolution of ingestion products in NWPMs, both Permanent Scatterers (PSs) and Distributed Scatterers (DSs) are jointly exploited. While the formers are by definition stable targets, but unevenly distributed, the latter are ubiquitous but stable only within a certain temporal baseline that can vary depending on the operational frequency of the radar. The proposed method is thus particularly suited for C, L, and P band missions with low temporal baseline between two consecutive acquisitions of the same scene: these conditions, that are both necessary to provide the dense space-time coverage required by meteorologists, allow for a reliable and robust estimation of APSs thanks to the intrinsic limitation of temporal decorrelation. The proposed technique integrates Zenith Total Delay (ZTD) products computed on a very sparse grid from a network of GNSS stations to correct for SAR orbital errors and to provide the missing phase constant from the derived APS map. In this paper, the complete workflow is explained, and a comparison of the derived APSs is performed with phase screens derived from state-of-the-art SAR processing workflow (SqueeSAR®).

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“…Each step will be explained in this section of the paper. A model describing the decorrelation of a general distributed scatterer has been described in [18,30].…”

Section: Processing Schemementioning

confidence: 99%

Joint Exploitation of SAR and GNSS for Atmospheric Phase Screens Retrieval Aimed at Numerical Weather Prediction Model Ingestion

Manzoni

Guarnieri

Realini³

et al. 2020

Remote Sensing

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show abstract

“…The model assumes a PSI processing scheme of a single-master interferometric stack (

interferograms), derived from SAR acquisitions which are regularly sampled in time. In these hypotheses, the displacement estimation can be modeled as a linear regression in the presence of a normally-distributed, white process, and the mean velocity standard deviation computed as [ 11 , 12 ]:

…”

Section: Performance Analysismentioning

confidence: 99%

“…MTI algorithms dealing with this kind of targets basically explore all the interferograms derivable from the available images in order to select those with reliable coherence values. Different strategies can be adopted (e.g., [ 6 , 7 , 11 ]) to select and estimate the parameters of interest. Regardless, the final estimation depends on the number of interferograms

(for

images), and on de-correlation phase noise affecting each interferogram.…”

Section: Performance Analysismentioning

confidence: 99%

“…Regardless, the final estimation depends on the number of interferograms

(for

images), and on de-correlation phase noise affecting each interferogram. According to [ 11 ], this contribution is dominant when dealing with a large number of images, since in this case it is possible to achieve a robust estimation and removal of the atmospheric noise, which thus becomes negligible. Although a final closed form can be derived (as in [ 11 ]), this still depends on parameters modeling the temporal decorrelation, which are hardly generalizable.…”

Section: Performance Analysismentioning

confidence: 99%

“…According to [ 11 ], this contribution is dominant when dealing with a large number of images, since in this case it is possible to achieve a robust estimation and removal of the atmospheric noise, which thus becomes negligible. Although a final closed form can be derived (as in [ 11 ]), this still depends on parameters modeling the temporal decorrelation, which are hardly generalizable. The proposed model, although confined to a PS targets scenario, provides a simple formulation, which depends on radiometric and geometric parameters that can be easily retrieved for any satellite mission.…”

Section: Performance Analysismentioning

confidence: 99%

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Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry

Bovenga

Belmonte

Refice

et al. 2018

Sensors

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Multi-temporal InSAR (MTI) applications pose challenges related to the availability of coherent scattering from the ground surface, the complexity of the ground deformations, atmospheric artifacts, and visibility problems related to ground elevation. Nowadays, several satellite missions are available providing interferometric SAR data at different wavelengths, spatial resolutions, and revisit time. A new and interesting opportunity is provided by Sentinel-1, which has a spatial resolution comparable to that of previous ESA C-band sensors, and revisit times improved by up to 6 days. According to these different SAR space-borne missions, the present work discusses current and future opportunities of MTI applications in terms of ground instability monitoring. Issues related to coherent target detection, mean velocity precision, and product geo-location are addressed through a simple theoretical model assuming backscattering mechanisms related to point scatterers. The paper also presents an example of a multi-sensor ground instability investigation over Lesina Marina, a village in Southern Italy lying over a gypsum diapir, where a hydration process, involving the underlying anhydride, causes a smooth uplift and the formation of scattered sinkholes. More than 20 years of MTI SAR data have been processed, coming from both legacy ERS and ENVISAT missions, and latest-generation RADARSAT-2, COSMO-SkyMed, and Sentinel-1A sensors. Results confirm the presence of a rather steady uplift process, with limited to null variations throughout the whole monitored time-period.

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FIM-based DSInSAR method for mapping and monitoring of reservoir bank landslides: an application along the Lancang River in China

Motagh

et al. 2023

Landslides

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Methods and Performances for Multi-Pass SAR Interferometry

Cited by 15 publications

References 22 publications

Joint Exploitation of SAR and GNSS for Atmospheric Phase Screens Retrieval Aimed at Numerical Weather Prediction Model Ingestion

Joint Exploitation of SAR and GNSS for Atmospheric Phase Screens Retrieval Aimed at Numerical Weather Prediction Model Ingestion

Performance Analysis of Satellite Missions for Multi-Temporal SAR Interferometry

FIM-based DSInSAR method for mapping and monitoring of reservoir bank landslides: an application along the Lancang River in China

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