Backscattering separation coming from ground and canopy is one of the main aims in dealing with forest scenario using synthetic aperture radar (SAR) tomography. Theoretically SAR tomography (TomoSAR) provides layover solution, but in practice, insufficient vertical resolution using typical reconstruction approaches may not be sufficient for identification of the vertically aligned scatterers. To cope with this intrinsic issue, we proposed a method that separates the ground and canopy backscatterings based on Random-Volume-over-Ground (RVOG) model and by employing the generalized likelihood ratio test (GLRT) detection schemes over the covariance matrix. Such a separation allows identification of interference of the backscattering, which simply brings the possibility to resolve and separate ground and canopy superposition in the tomogram. Experimental validation of the proposed methodology is provided using a real data set acquired by the ONERA SETHI in the framework of the ESA's campaign, TropiSAR.

ON THE SEPARATION OF GROUND AND CANOPY SCATTERINGS USING SINGLE POLARIMETRIC MULTI-BASELINE SAR TOMOGRAPHY

Budillon, A;Ferraioli, G;Pascazio, V;Schirinzi, G
2019-01-01

Abstract

Backscattering separation coming from ground and canopy is one of the main aims in dealing with forest scenario using synthetic aperture radar (SAR) tomography. Theoretically SAR tomography (TomoSAR) provides layover solution, but in practice, insufficient vertical resolution using typical reconstruction approaches may not be sufficient for identification of the vertically aligned scatterers. To cope with this intrinsic issue, we proposed a method that separates the ground and canopy backscatterings based on Random-Volume-over-Ground (RVOG) model and by employing the generalized likelihood ratio test (GLRT) detection schemes over the covariance matrix. Such a separation allows identification of interference of the backscattering, which simply brings the possibility to resolve and separate ground and canopy superposition in the tomogram. Experimental validation of the proposed methodology is provided using a real data set acquired by the ONERA SETHI in the framework of the ESA's campaign, TropiSAR.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/83925
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