Interferometric synthetic aperture radar statistical inference in deformation measurement and geophysical inversion: a review
With the rapid advancements in synthetic aperture radar (SAR) satellites and associated
processing algorithms over recent decades, interferometric SAR (InSAR) has emerged as a …
processing algorithms over recent decades, interferometric SAR (InSAR) has emerged as a …
An overview of advances in signal processing techniques for classical and quantum wideband synthetic apertures
P Vouras, KV Mishra, A Artusio-Glimpse… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture
with greater angular resolution than is inherently possible from the physical dimensions of a …
with greater angular resolution than is inherently possible from the physical dimensions of a …
Array 3-D SAR tomography using robust gridless compressed sensing
Tomographic synthetic aperture radar (TomoSAR), which can provide 3-D image of the
observed scenes, has become an important technology for topographic mapping, forest …
observed scenes, has become an important technology for topographic mapping, forest …
Complex-valued end-to-end deep network with coherency preservation for complex-valued sar data reconstruction and classification
Deep learning models have achieved remarkable success in many different fields and
attracted many interests. Several researchers attempted to apply deep learning models to …
attracted many interests. Several researchers attempted to apply deep learning models to …
Tomographic SAR inversion by atomic-norm minimization—The gridless compressive sensing approach
X Wang, F Xu - IEEE Transactions on Geoscience and Remote …, 2022 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) tomography (TomoSAR) extends the synthetic aperture
principle into the elevation direction for 3-D imaging. Due to the sparsity of the elevation …
principle into the elevation direction for 3-D imaging. Due to the sparsity of the elevation …
Basis pursuit denoising via recurrent neural network applied to super-resolving SAR tomography
Finding sparse solutions of underdetermined linear systems commonly requires the solving
of regularized least-squares minimization problem, which is also known as the basis pursuit …
of regularized least-squares minimization problem, which is also known as the basis pursuit …
3-d sar autofocusing with learned sparsity
Inevitable inaccuracies of 3-D synthetic aperture radar (3-D SAR) imaging geometry may
cause undesired blurs in reconstructed images. Recent advances show impressive results …
cause undesired blurs in reconstructed images. Recent advances show impressive results …
MAda-Net: Model-adaptive deep learning imaging for SAR tomography
Y Wang, C Liu, R Zhu, M Liu, Z Ding… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The compressive sensing (CS)-based tomographic SAR (TomoSAR) 3-D imaging method
has the shortcoming of low efficiency, mainly represented in two aspects: first, the CS solver …
has the shortcoming of low efficiency, mainly represented in two aspects: first, the CS solver …
3-D SAR data-driven imaging via learned low-rank and sparse priors
In the research topic of three-dimensional (3-D) synthetic aperture radar (SAR) imaging, the
sparsity-enforcing techniques offer promise in shortening the sensing time and improving …
sparsity-enforcing techniques offer promise in shortening the sensing time and improving …
[HTML][HTML] Tropical forest AGB estimation based on structure parameters extracted by TomoSAR
W Li, Y Zhang, J Zhang, H Chen, E Chen… - International Journal of …, 2023 - Elsevier
Forests play a crucial role in quantifying global carbon storage and detecting climate change
in the form of aboveground biomass (AGB), which introduces an approach to study carbon …
in the form of aboveground biomass (AGB), which introduces an approach to study carbon …