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SAR tomography is a remote sensing technique, extending SAR interferometry, that allows three-dimensional imaging of multiple height-distributed point-like scatterers or volumetric targets. It allows, for example, to solve layover urban scatterers or to analyze the vertical structure of vegetation layers or other targets with significant penetration of the sensor's radiation (dry soil, ice layers, etc.). The ability to monitor the 3-D inner structure of volumetric targets and to extract information about the nature and location of ongoing scattering processes promises a break-through in key environmental problems. Indeed, structural parameters of volume scatterers in the biosphere and cryosphere, such as vegetation height and moisture content, forest vertical structure and biomass, or snow / ice depth and layering are critical inputs for ecological process modeling and enable effective monitoring of ecosystem change. The 3-D tomographic principle has been also extended to higher dimension in the more recent differential tomography methodology, producing 4-D (3-D + time) images bridging the gap between differential interferometry and SAR tomography. Due to their unique capabilities and potential, tomographic SAR techniques have gained significant attention during the last years and become established methods for analysis of all kinds of three-dimensional back-scattering scenarios. In particular, for future space-borne SAR sensors operating in longer wavelength, like BIOMASS, SAOCOM-CS or Tandem-L, it is planned to employ 3-D tomographic imaging modes on an operational basis. This paper aims to review the different state-of-the-art signal processing methods for three-dimensional SAR imaging, which have been developed during the last decade, and for four-dimensional differential tomography. The requirements, advantages and disadvantages of different techniques are assessed and compared and open issues to be addressed in future developments are pointed out. |
