The analysis of multi-temporal SAR data-sets encountered large interest in the remote sensing community during the past few years. The main effort goes toward the extraction of ground displacements signals by means of differential interferometric techniques. In this operational framework an important processing step concerns the estimation and subtraction of signals due to atmospheric artifacts and processing errors. In the present work we apply the technique of Blind Source Separation (BSS) by using the algorithm of Independent Component Analysis (ICA) to Permanent Scatterer processing in order to perform the separation of different signal components. Preliminary investigations are carried out both on simulated and real ERS-1/2 data and results are reported and commented.
Discrimination of different sources of signals in Permanent Scatterers technique by means of Independent Component Analysis
STRAMAGLIA, Sebastiano;
2003-01-01
Abstract
The analysis of multi-temporal SAR data-sets encountered large interest in the remote sensing community during the past few years. The main effort goes toward the extraction of ground displacements signals by means of differential interferometric techniques. In this operational framework an important processing step concerns the estimation and subtraction of signals due to atmospheric artifacts and processing errors. In the present work we apply the technique of Blind Source Separation (BSS) by using the algorithm of Independent Component Analysis (ICA) to Permanent Scatterer processing in order to perform the separation of different signal components. Preliminary investigations are carried out both on simulated and real ERS-1/2 data and results are reported and commented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
