A Multisquint Framework for Change Detection in High-Resolution Multitemporal SAR Images

Change detection from multitemporal synthetic aperture radar (SAR) images enables mapping applications for earth environmental observation, human activity monitoring, and urban studies. We expand the use of SAR data beyond single-look processing to include the spatial response of targets. This information is derived from a multisquint framework similar to beamforming. To preserve changes detected at nominal resolution, a three-stage change detector exploiting single-look and multisquint processing mode is proposed to mitigate false alarms caused by image artifacts typically found in high-resolution SAR imagery and urban scenarios. After applying the proposed method to multitemporal images, the false alarm rate was reduced by a factor 3, while preserving 95% of the detection rate offered by traditional schemes.