Finance

Physics

Geology

Terrain

Mathematics

Radar imaging

Algorithm

Optics

Statistics

Signal-to-noise ratio (imaging)

Plane (geometry)

Artificial intelligence

Azimuth

Position (finance)

Economics

Tomography

Geography

Geometry

Computer science

Cartography

Synthetic aperture radar

Likelihood-ratio test

Computer vision

Radar

Remote sensing

Telecommunications

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

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

Performance Improvement for SAR Tomography Based on Local Plane Model