http://www.cnr.it/ontology/cnr/individuo/prodotto/ID200807
A New SBAS-DInSAR approach based on a redundant set of small baseline interferograms (Contributo in atti di convegno)
- Type
- Label
- A New SBAS-DInSAR approach based on a redundant set of small baseline interferograms (Contributo in atti di convegno) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Alternative label
Yang Y., Pepe A., Manzo M., Lanari R. (2012)
A New SBAS-DInSAR approach based on a redundant set of small baseline interferograms
in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany, 23-27 July 2012
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Yang Y., Pepe A., Manzo M., Lanari R. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) (literal)
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- IREA-CNR
National University of Defense Technology, China (literal)
- Titolo
- A New SBAS-DInSAR approach based on a redundant set of small baseline interferograms (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-4673-1159-5 (literal)
- Abstract
- We present an efficient algorithm to mitigate noise effects in differential interferograms by exploiting the temporal relationships among a redundant set of small baseline interferograms. The core of the proposed technique is represented by the estimation of the (wrapped) filtered phase values associated to the available SAR acquisitions. This result is achieved by using conventional multi-look interferograms by applying a non-linear maximization procedure that exploits only phase information, and does not require any assumption on the statistics of the complex-valued SAR images involved in the interferogram generation. Subsequently, from the retrieved phase images, a filtered version of the original interferograms can be simply reconstructed and used to generate deformation time series by the conventional Small BAseline Subset (SBAS) approach.
The experimental results, achieved by applying the proposed approach to a dataset consisting in 39 SAR data acquired from 2002 to 2010 over the Abruzzi (Central Italy) area confirm the effectiveness of the proposed method. (literal)
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