Performance Improvement for SAR Tomography Based on Local Plane Model

Multilook approaches have been applied in synthetic aperture radar (SAR) tomography (TomoSAR), for improving the density and regularity of persistent scatterers reconstructed from multipass SAR images both rural urban regions. operations assume that all a given neighborhood are similar height, thereby providing additional data recovering position reflectivity single scatterer, so higher signal-to-noise ratio can be achieved. This is equivalent to assuming belonging local range–azimuth cells located on horizontal planes. The present article generalizes this approach by adopting so-called plane (LP) model TomoSAR imaging areas, accounting variations height not negligible. Furthermore, an LP-generalized likelihood test (LP-GLRT) algorithm developed implement previous idea. Compared with multilook generalized algorithm, LP-GLRT shows better performance case structures terrains experiments based simulated TerraSAR-X images.