Tomographic SAR inversion by L1-norm regularization-the compressive sensing approach

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Abstract

Synthetic aperture radar (SAR) tomography (TomoSAR) extends the synthetic aperture principle into the elevation direction for 3-D imaging. The resolution in the elevation direction depends on the size of the elevation aperture, i.e., on the spread of orbit tracks. Since the orbits of modern meter-resolution spaceborne SAR systems, like TerraSAR-X, are tightly controlled, the tomographic elevation resolution is at least an order of magnitude lower than in range and azimuth. Hence, super-resolution reconstruction algorithms are desired. The high anisotropy of the 3-D tomographic resolution element renders the signals sparse in the elevation direction; only a few pointlike reflections are expected per azimuthrange cell. This property suggests using compressive sensing (CS) methods for tomographic reconstruction. This paper presents the theory of 4-D (differential, i.e., spacetime) CS TomoSAR and compares it with parametric (nonlinear least squares) and nonparametric (singular value decomposition) reconstruction methods. Super-resolution properties and point localization accuracies are demonstrated using simulations and real data. A CS reconstruction of a building complex from TerraSAR-X spotlight data is presented.

Original languageEnglish
Article number5482209
Pages (from-to)3839-3846
Number of pages8
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume48
Issue number10
DOIs
StatePublished - Oct 2010

Keywords

  • Compressive sensing (CS)
  • TerraSAR-X
  • differential synthetic aperture radar tomography (D-TomoSAR)
  • urban mapping

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