Name
Abstract | ||
|---|---|---|
Isolating phase residuals due to inaccurate external digital elevation model (DEM) is important in retrieval and interpretation of deformation behavior from interferometric synthetic aperture radar (InSAR) observations. Multitemporal InSAR (MTInSAR), by taking DEM error as a parameter, can make the isolation possible. However, due to the presence of atmospheric artifacts in observations and improper deformation model employed in the observation system, accurate retrieval of DEM error cannot be guaranteed in current MTInSAR techniques. Considering that the DEM error has a fixed spatial pattern and its contribution to interferometric phase-only changes with spatial baselines, we propose here a nonparametric method that can estimate the DEM error in a more robust way. To retrieve signals having a fixed spatial pattern from unwrapped MTInSAR measurements, the independent component analysis (ICA) is used. Experiments with synthetic and real data sets indicate the proposed method is able to estimate DEM error with no
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information about deformation. Moreover, experiments also show that the method can provide a more robust estimation when the observed phase observations are affected by atmospheric delays and/or the number of interferograms used is limited. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TGRS.2019.2930802 | IEEE Transactions on Geoscience and Remote Sensing |
Keywords | Field | DocType |
Strain,Synthetic aperture radar,Atmospheric modeling,Estimation,Matrix decomposition,Digital elevation models,Deformable models | Computer vision,Interferometric synthetic aperture radar,Remote sensing,Nonparametric statistics,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
57 | 12 | 0196-2892 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongyu Liang | 1 | 84 | 16.39 |
| Lei Zhang | 2 | 90 | 14.86 |
| zhong lu | 3 | 40 | 18.20 |
| Xin Li | 4 | 4 | 3.47 |