Scattering information extraction is crucial for enhanced target characterization. While numerous parameters have been introduced to describe scattering from targets using full-polarimetric SAR data, the challenge lies in obtaining such scattering-type information from dual-polarimetric SAR data. This study presents an ingenious approach to address this challenge. We propose a novel index for characterizing surface scattering by leveraging dual-polarimetric Sentinel-1 SLC as well as GRD SAR data. Our method uniquely utilizes a Stokes vector component to effectively distinguish 'surface-like' scattering from targets. Notably, the results from our proposed index competently align with similar scattering-type parameters derived from full-polarimetric SAR data.
Radar surface scattering index from dual-pol Sentinel-1 SLC and GRD SAR data
Bhattacharya A.;Gamba P.
2024-01-01
Abstract
Scattering information extraction is crucial for enhanced target characterization. While numerous parameters have been introduced to describe scattering from targets using full-polarimetric SAR data, the challenge lies in obtaining such scattering-type information from dual-polarimetric SAR data. This study presents an ingenious approach to address this challenge. We propose a novel index for characterizing surface scattering by leveraging dual-polarimetric Sentinel-1 SLC as well as GRD SAR data. Our method uniquely utilizes a Stokes vector component to effectively distinguish 'surface-like' scattering from targets. Notably, the results from our proposed index competently align with similar scattering-type parameters derived from full-polarimetric SAR data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
