Compressive Sensing for Multibaseline Polarimetric SAR Tomography of Forested Areas

The structure of forests is an important indicator of ecosystem dynamics and enables the modeling and monitoring of ecological change. Synthetic aperture radar tomography (TomoSAR) provides scene reflectivity estimation of vegetation along elevation coordinates. Due to the advantages of superresolution imaging and a small number of measurements, compressive sensing (CS) inversion techniques for SAR tomography were successfully developed and applied. This paper addresses the 3-D imaging of forested areas based on the framework of CS using fully polarimetric (FP) multibaseline SAR interferometric (MB-InSAR) tomography at P-band. A new CS-based FP MB-InSAR tomography method is proposed: a sum of Kronecker product (SKP) decomposition-based CS FP MB-InSAR tomography method (FP-SKPCS TomoSAR method). The method, based on an assumption that the reflectivity signal of a single scattering mechanism (SM) is more sparse than that of a composite of SMs, recovers the reflectivity profile of different SMs by using the CS technique. This method not only allows superresolution imaging with a low number of acquisitions but also can estimate the polarimetric SM of the vertical structure of forested areas. The effectiveness of these novel techniques for polarimetric SAR tomography is demonstrated using FP P-band airborne data sets acquired by the ONERA SETHI airborne system over a test site in Paracou, French Guiana, and the results of the vertical structure of forested areas derived by the method are verified by in situ test data.