Abstract
Interferometric SAR (InSAR) is a practical technique to derive 3-D structure of the earth's surface. This article conducts a comparative study of digital elevation model (DEM) reconstruction using the single-baseline and multibaseline InSAR techniques. To improve the accuracy of the DEM generated from the single-baseline InSAR, we improve the weight definition approach according to the coherence magnitudes for the fusion of single-baseline InSAR DEMs. For multibaseline InSAR, we adopt a method based on the maximum-likelihood estimation (MLE) algorithm, which uses external DEM as a constraint. A TerraSAR-X dataset comprising four SAR images acquired over Barcelona is used for experimental investigation. The accuracies of four types of DEM are comparatively studied, including DEM by single-baseline InSAR, DEM by the fusion of single-baseline InSAR DEMs, DEM by unconstrained multibaseline InSAR, and DEM by constrained multibaseline InSAR. The results show that the proposed weighted fusion of single-baseline InSAR performed slightly better than the constrained multibaseline InSAR method, and both of them performed better than the single-baseline results, demonstrating that multiple observations can effectively improve the accuracy of the reconstructed DEM.
Highlights
Digital elevation models (DEMs), as digital expressions of the terrain, have been widely used in surveying, mapping, building design and disaster reduction [1, 2]
We focus on the following two issues: 1) can the elevation accuracy be improved using DEM fusion by considering the coherence magnitudes? and 2) how does the performance of the multi-baseline Interferometric synthetic aperture radar (SAR) (InSAR) compare with that of the single-baseline InSAR in terms of DEM reconstruction? To improve the applicability of the DEM reconstruction using the InSAR techniques, we improved the weight definition approach of the DEM fusion for single-baseline InSAR and conducted a comparative study of DEM reconstruction using the single-baseline and multi-baseline InSAR techniques
Compared with the weights determined by accuracy statistics of individual DEMs or correlation statistics, the coherence magnitudes were used as weights which are corresponding to individual pixels in our method, which is more reasonable than use a uniform weight for all the points of a DEM
Summary
Digital elevation models (DEMs), as digital expressions of the terrain, have been widely used in surveying, mapping, building design and disaster reduction [1, 2]. Common methods of multi-baseline PU include the Chinese remainder theorem method [21], linear combination method [22], maximum likelihood phase estimation method [23,24,25], and maximum a posteriori (MAP) estimation based on a Bayesian framework [26]. Studies show that these methods possess weak robustness of noise reduction due to their mathematical foundations. We focus on the following two issues: 1) can the elevation accuracy be improved using DEM fusion by considering the coherence magnitudes? and 2) how does the performance of the multi-baseline InSAR compare with that of the single-baseline InSAR in terms of DEM reconstruction? To improve the applicability of the DEM reconstruction using the InSAR techniques, we improved the weight definition approach of the DEM fusion for single-baseline InSAR and conducted a comparative study of DEM reconstruction using the single-baseline and multi-baseline InSAR techniques
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