Forest Analysis Using SAR Tomography and Maximum Likelihood Inspired Spectral Estimation

Conference: EUSAR 2018 - 12th European Conference on Synthetic Aperture Radar
06/04/2018 - 06/07/2018 at Aachen, Germany

Proceedings: EUSAR 2018

Pages: 5Language: englishTyp: PDF

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Campo Becerra, Gustavo Martin del; Nannini, Matteo; Reigber, Andreas (Microwaves and Radar Institute, German Aerospace Center (DLR), Germany)

This paper treats the synthetic aperture radar (SAR) tomography (TomoSAR) non-linear inverse problem, within the framework of maximum likelihood (ML) estimation theory. In this context, a novel non-parametric spectral analysis (SA) technique, addressed in a closed fixed-point iterative fashion, is presented. The main goal of the proposed approach is to provide resolution-enhancement, with suppression of artifacts and ambiguity levels reduction, to an initial estimate of the continuous power spectrum pattern (PSP), retrieved using the celebrated matched spatial filter (MSF) beamforming technique. The feature enhancing capabilities of the proposed method are corroborated via processing L-band airborne multi-baseline SAR data of the German Aerospace Center (DLR), acquired by the F-SAR system over the forested test site of Froschham, Germany, in 2017.