The Iterative Extraction of the Boundary of Coherence Region and Iterative Look-Up Table for Forest Height Estimation Using Polarimetric Interferometric Synthetic Aperture Radar Data

In this paper, we introduce a refined three-stage inversion algorithm (TSIA) for forest height estimation using polarimetric interferometric synthetic aperture radar (PolInSAR). Specifically, the iterative extraction of boundary coherence region (IEBCR) and look-up table (ILUT) are proposed to improve efficiency traditional TSIA. A class TSIA utilizes (BCR) alleviate underestimation phenomenon in estimation. Given many eigendecompositions BCR (EBCR), analyze relationship eigenvectors between adjacent points on propose IEBCR utilizing power methods. final stage TSIA, (LUT) uses exhaustive search method minimize loss function 2-D grid with defined step sizes thus costs high computational complexity. To deficiency, define random volume over ground (RVoG) based RVoG model prove its monotonicity convergence from analytical numerical view. After analyzing function, ILUT stage. The simulation experiments BioSAR 2008 campaign data illustrate that greatly almost without compromising accuracy.