Abstract
Three dimensional (3D) deformation can be obtained by using differential interferometric synthetic aperture radar (D-InSAR) technique with the cross-heading tracks data of low earth orbit (LEO) SAR. However, this method has drawbacks of the low temporal sampling rate and the limited area and accuracy for 3D defor- mation retrieval. To address the aforementioned problems, by virtue of a geosynchronous (GEO) SAR platform, this paper firstly demonstrates the expressions of 3D deformation and the corresponding errors in GEO SAR multi-angle processing. An optimal multi-angle data selection method based on minimizing position dilution of precision (PDOP) is proposed to obtain a good 3D deformation retrieval accuracy. Moreover, neural network is utilized for analyzing the accuracy of the retrieved 3D deformation under different orbit configurations and geo-locations. Finally, the proposed methods and the theoretical analysis are verified by simulation experiments. A 3D deformation retrieval accuracy of the order of centimeter-level or even millimeter-level can be obtained by using the selected optimal multi-angle data.
| Original language | English |
|---|---|
| Article number | 060303 |
| Journal | Science China Information Sciences |
| Volume | 60 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Jun 2017 |
Keywords
- differential SAR (D-InSAR)
- geosynchronous synthetic aperture radar (GEO SAR)
- multi-angle processing
- neural network
- three dimensional (3D) deformation measurement
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