Forest Height and Underlying Topography Inversion Using Polarimetric SAR Tomography Based on SKP Decomposition and Maximum Likelihood Estimation

The key point of forest height and underlying topography inversion using synthetic aperture radar tomography (TomoSAR) depends on the accurate positioning phase centers different scattering mechanisms. traditional nonparametric spectrum analysis methods (such as beamforming Capon) have limited vertical resolution cannot accurately distinguish closely spaced scatterers. In addition, it is very difficult to estimate ground or canopy heights with single polarimetric SAR images because there no guarantee that profile will generate two clear separate peaks for all cells. A TomoSAR method based SKP (sum Kronecker products) decomposition iterative maximum likelihood estimation proposed in this paper. On one hand, has a higher than methods. other separation mechanism conducive centers. This was applied tropical over TropiSAR2009 test site Paracou, French Guiana six passes images. accuracy up 1.489 m 1.765 m. Compared capon methods, greatly improved topography.