LAUSR

Multibaseline polarimetric synthetic aperture radar interferometry (PolInSAR) is one of the advanced technologies of forest height inversion, as it provides rich observation information. In this letter, we propose a new iterative reweighted method for multibaseline PolInSAR joint inversion of forest height. First, we establish a better stochastic model and weight function to obtain more accurate parameter estimation considering the relationship between vertical wavenumber and forest height. Second, according to the proposed inversion criterion, the baseline observations with unsuitable interferometric geometry are regarded as gross errors and eliminated through reweighted iteration. Finally, we select airborne P-band synthetic aperture radar (SAR) data collected by the F-SAR system during the AfriSAR 2016 campaign for experimental validation. The experimental results show that using initial iteration values obtained by three optimal baseline selection methods, the accuracy of the proposed method achieves 4.47, 4.46, and 4.24 m, which is about 34.74%, 32.32%, and 33.23% higher than those of the existing multibaseline joint inversion method [root mean square error (RMSE) = 6.85, 6.59, and 6.35 m], respectively.