Multi‐baseline InSAR phase unwrapping method based on mixed‐integer optimisation model
Author(s) -
Jin Biao,
Guo Jiao,
Wei Pengliang,
Su Baofeng,
He Dongjian
Publication year - 2018
Publication title -
iet radar, sonar and navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.489
H-Index - 82
eISSN - 1751-8792
pISSN - 1751-8784
DOI - 10.1049/iet-rsn.2017.0543
Subject(s) - interferometric synthetic aperture radar , synthetic aperture radar , pixel , computer science , baseline (sea) , interferometry , digital elevation model , robustness (evolution) , terrain , phase (matter) , integer (computer science) , algorithm , noise reduction , remote sensing , artificial intelligence , optics , geology , geography , physics , biochemistry , oceanography , chemistry , cartography , gene , programming language , quantum mechanics
Multi‐baseline phase unwrapping operation is a very important step for multi‐baseline Synthetic Aperture Radar Interferometry (InSAR). However, the conventional methods applied for single pixel suffer seriously from the phase noise that exists numerously in the interferometric phase images (i.e. interferograms). In order to improve the robustness to noise, this study proposes an innovative multi‐baseline InSAR phase unwrapping method based on a mixed‐integer optimisation model. The proposed method combines the central and its neighbouring pixels to jointly construct the mixed‐integer optimisation model under the assumption that the pixels within a local window can be approximated by a small slant plane terrain. Furthermore, considering the practical case, the optimal window size is estimated according to the deviation from the interferometric wrapped phase to the assumed linear terrain, and the fast Fourier transform technique is adopted to reduce computational cost. The theoretical analysis and computer simulation demonstrate that the proposed method is able to improve the multi‐baseline phase unwrapping performance and can be applied to reconstruct the digital elevation models for complicated topographies.
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