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EnglishSynthetic Aperture Radar Interferometry allows the generation of Digital Elevation Model of an observed scene exploiting the phase signal. In order to provide the 3D reconstruction, a phase unwrapping procedure is required, which is an ill-posed problem. Multichannel datasets are able to solve the ambiguity providing a global solution. Within this manuscript two recently proposed statistical multichannel phase unwrapping methods are considered and compared. The first one is developed in the Bayesian-Markovian framework, while the second one is based on Kalman filtering. Results and comparisons on a simulated data set are reported, showing interesting results.
| Titolo: | Statistical approaches for multichannel phase unwrapping | |
| Autori: | ||
| Data di pubblicazione: | 2013 | |
| Abstract: | Synthetic Aperture Radar Interferometry allows the generation of Digital Elevation Model of an observed scene exploiting the phase signal. In order to provide the 3D reconstruction, a phase unwrapping procedure is required, which is an ill-posed problem. Multichannel datasets are able to solve the ambiguity providing a global solution. Within this manuscript two recently proposed statistical multichannel phase unwrapping methods are considered and compared. The first one is developed in the Bayesian-Markovian framework, while the second one is based on Kalman filtering. Results and comparisons on a simulated data set are reported, showing interesting results. | |
| Handle: | http://hdl.handle.net/11367/31592 | |
| ISBN: | 978-1-4799-0213-2 | |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11367/31592
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