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Efficient Tomographic Inversion Based on Refined Scatterer Pre-Estimation
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DOI：10.1109/LGRS.2022.3203037.png)
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Abstract
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During the last decade, the synthetic aperture radar (SAR) tomography (TomoSAR) technique in 3-D reconstruction is significantly improved. In particular, compressed sensing (CS) has become the best suit for urban tomographic inversion. Among CS algorithms, the orthogonal matching pursuit (OMP) combined with Bayesian information criterion (BIC) has relatively low computational complexity, and however, its scatterer estimation accuracy needs to be improved. To address the problem, a prior scatterer estimation with an innovative triple-threshold detection algorithm is proposed, which not only greatly reduces the number of iterations but also helps suppress artifacts. Experiments on real data show that the priori overlay times maps provided by the proposed algorithm are closer to the reference maps than other two pre-estimation algorithms. Artifacts in 3-D reconstruction results are well suppressed at less than half the time cost of original OMP-BIC.
Keywords:
Estimation
Tomography
Three-dimensional displays
Coherence
Indexes
Dispersion
Synthetic aperture radar
Persistent scatterer interferometry (PSI)
scatterers detection
synthetic aperture radar (SAR)
tomographic processing
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