Abstract
Ground-based interferometric synthetic aperture radar (GB-InSAR) technology can be applied to generate a digital elevation model (DEM) with high spatial resolution and high accuracy. Phase unwrapping is a critical procedure, and unwrapping errors cannot be effectively avoided in the interferometric measurements of terrains with discontinuous heights. In this paper, an improved multi-baseline phase unwrapping (MB PU) method for GB-InSAR is proposed. This method combines the advantages of the cluster-analysis-based MB PU algorithm and the minimum cost flow (MCF) method. A cluster-analysis-based MB PU algorithm (CA-based MB PU) is firstly utilized to unwrap the clustered pixels with high phase quality. Under the topological constraints of a triangulation network, the connectivity graph of any non-clustered pixel is established with its adjacent unwrapped cluster pixels. Then, the absolute phase of these non-clustered pixels can be identified using the MCF method. Additionally, a spatial-distribution-based denoising algorithm is utilized to denoise the data in order to further improve the accuracy of the phase unwrapping. The DEM generated by one GB-InSAR is compared with that generated by light detection and ranging (LiDAR). Both simulated and experimental datasets are utilized to verify the effectiveness and robustness of this improved method.
| Original language | English |
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| Article number | 2543 |
| Journal | Remote Sensing |
| Volume | 14 |
| Issue number | 11 |
| DOIs |
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| Publication status | Published - 1 Jun 2022 |
Keywords
- ground-based interferometric synthetic aperture radar (GB-InSAR)
- minimum cost flow (MCF)
- multi-baseline phase unwrapping (MB PU)
- spatial-distribution-based denoising algorithm (SD-based DA)
- triangulation network