Performance Assessment of Change Detection Based on Robust PCA for Wavelength Resolution SAR Images Using...

One of the main challenges in Synthetic Aperture Radar (SAR) change detection involves using SAR images from different flight passes. Depending on the flight pass, objects have different specular reflections since the radar cross-sections of these objects can be totally different between passes. Then, it is common knowledge that the flight passes must be close to identical for conventional SAR change detection. Wavelength-resolution SAR refers to a SAR system with a spatial resolution approximately equal to the wavelength. This high relative resolution helps to stabilize the ground clutter in the SAR images. Consequently, the restricted requirement about identical flight passes for SAR change detection can be relaxed, and SAR change detection becomes possible with nonidentical passes. This paper shows that robust principal component analysis (RPCA) is efficient for change detection even using wavelength-resolution SAR images acquired with very different flight passes. It presents several SAR change detection experimental results using flight pass differences up to 95°. For slightly different passes, e.g., 5°, our method reached a false alarm rate (FAR) of approximately one false alarm per square kilometer for a probability of detection (PD) above 90%. In a particular setting, it achieves a PD of 97.5% for a FAR of 0.917 false alarms per square kilometer, even using SAR images acquired with nonidentical passes.