Analysis and Evaluation of InSAR Phase Unwrapping Approaches

2011 ◽  
Vol 301-303 ◽  
pp. 1029-1035
Author(s):  
Shu Bi Zhang ◽  
Tuo Fu
Keyword(s):  
Network Flow ◽  
Minimum Cost ◽  
Phase Unwrapping ◽  
Sar Interferometry ◽  
Analysis And Evaluation ◽  
Digital Elevation ◽  
Cut Method ◽  
Minimum Cost Network Flow ◽  
Elevation Model ◽  
Interferometric Sar

In recent years SAR interferometry has become a widely used technique for measuring altitude and displacement of the surface of the earth. Phase unwrapping of the interferometric SAR is a very important step to obtain an accurate DEM(Digital Elevation Model)[1,2,3],and phase unwrapping is not only crucial in InSAR but also a major source in InSAR errors. Therefore, with GAMMA software, VC++ and MATLAB coding implementing six kinds of phase unwrapping approaches ,this paper presents the best method for different situations through two sets of experimental results used for analysing and comparing run time and precision. In the plain and alpine area, the best phase unwrapping methods are separately Goldstein branch-cut method and Minimum Cost Network Flow method.

Multichannel interferometric SAR phase unwrapping using extended Kalman Smoother

2013 ◽  
Vol 5 (3) ◽  
pp. 429-436 ◽  
Author(s):  
Davide Chirico ◽  
Gilda Schirinzi
Keyword(s):  
Phase Unwrapping ◽  
Sensor Data ◽  
Bayesian Estimator ◽  
Bayesian Approaches ◽  
Strong Discontinuities ◽  
Absolute Phase ◽  
Multi Sensor Data Fusion ◽  
Digital Elevation ◽  
Elevation Model ◽  
Interferometric Sar

Phase unwrapping (PU) is one of the key processing steps in reconstructing the digital elevation model (DEM) of a scene from interferometric synthetic aperture radar (InSAR) data. The PU problem entails the estimation of an absolute phase from observation of its noisy principal (wrapped) values. Recently, PU approaches based on Kalman filtering have proved their efficacy in tackling the PU problem even when strong discontinuities of the height profile and noisy data are involved. This paper presents a novel multichannel InSAR PU algorithm using several interferometric SAR images based on the extended Kalman filter. The proposed technique exploits the capability of the Kalman algorithm to simultaneously perform noise filtering, PU, and multi-sensor data fusion. The proposed method, even being a Bayesian estimator, optimally fuses height information coming from an additional maximum likelihood estimator (MLE) combining the benefits of both the Bayesian and the non-Bayesian approaches. The performance of the proposed algorithm has been tested on simulated interferometric images proving the effectiveness of the proposed method.

scholarly journals Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2336 ◽  
Author(s):  
Takashi Nonaka ◽  
Tomohito Asaka ◽  
Keishi Iwashita
Keyword(s):  
Phase Noise ◽  
Atmospheric Effects ◽  
Sar Images ◽  
Single Pass ◽  
Digital Elevation ◽  
Total Phase ◽  
Disaster Monitoring ◽  
The Difference ◽  
Elevation Model ◽  
Interferometric Sar

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.

scholarly journals Minimum cost network flows: Problems, algorithms, and software

2013 ◽  
Vol 23 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Angelo Sifaleras
Keyword(s):  
Network Flow ◽  
Flow Problem ◽  
Network Flows ◽  
Minimum Cost ◽  
Network Flow Problem ◽  
Software Packages ◽  
Wide Range ◽  
Solution Methods ◽  
Minimum Cost Network Flow ◽  
Algorithmic Approaches

We present a wide range of problems concerning minimum cost network flows, and give an overview of the classic linear single-commodity Minimum Cost Network Flow Problem (MCNFP) and some other closely related problems, either tractable or intractable. We also discuss state-of-the-art algorithmic approaches and recent advances in the solution methods for the MCNFP. Finally, optimization software packages for the MCNFP are presented.

scholarly journals Topography and dynamics of Austfonna, Nordaustlandet, Svalbard, from SAR interferometry

1997 ◽  
Vol 24 ◽  
pp. 403-408 ◽  
Author(s):  
Beverley Unwin ◽  
Duncan Wingham
Keyword(s):  
Sar Interferometry ◽  
Synthetic Aperture ◽  
Drainage Basins ◽  
Ice Caps ◽  
Radar Images ◽  
Differential Interferometry ◽  
Digital Elevation ◽  
Radio Echo Sounding ◽  
Velocity Information ◽  
Elevation Model

The ice caps of Nordaustlandet, Svalbard, represent one of the largest glaciated areas outside of Antarctica and Greenland. They demonstrate a variety of different flow regimes within a comparatively compact area. We report on the first interferometrically derived elevation models and velocity visualisations of Austfonna. This initial investigation had three purposes: to determine whether the coherence and velocity characteristics of the region permitted interferometric survey; to determine the accuracy of derived elevations; and to assess the possibility of investigating time-variant flow of the more dynamic ice bodies using differential interferometry. A trio of coherent synthetic aperture radar images from ERS-1 ’s First Ice Phase was identified. The images were combined to separate the topographic and velocity components of the resultant interferograms. The topographic phase difference was used to produce a digital elevation model of Austfonna. Its accuracy relative to radio-echo-sounding derived tie-points is 8 m and its resolution 40 m. We also present synoptic views of the velocity field of three of Austfonna’s drainage basins, and comment on the extraction of useful velocity information.

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