In this paper, we present a sparse four-dimensional tomographic synthetic aperture radar (4D TomoSAR) imaging scheme that can estimate elevation and linear as well as non-linear seasonal deformation rates of scatterers using the interferometric phase. Unlike existing sparse processing techniques that use fixed dictionaries based on a linear deformation model, we use a variable dictionary for the non-linear deformation in the form of seasonal sinusoidal deformation, in addition to the fixed dictionary for the linear deformation. We estimate the amplitude of the sinusoidal deformation using an optimization method and create the variable dictionary using the estimated amplitude. We show preliminary results using simulated data that demonstrate the soundness of our proposed technique for sparse 4D TomoSAR imaging in the presence of non-linear deformation.
Ahmed Shaharyar Khwaja and Müjdat Çetin, "Sparse 4D TomoSAR imaging in the presence of non-linear deformation," Proc. SPIE 10647, Algorithms for Synthetic Aperture Radar Imagery XXV, 106470J (Presented at SPIE Defense + Security: April 19, 2018; Published: 27 April 2018); https://doi.org/10.1117/12.2303530.
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