由于单基线极化干涉SAR技术(如三阶段法、ESPRIT算法等)反演植被参数的方法受限于具有最小地体幅度比的观测数据,影响冠层或地表有效相位中心的估计,因此往往低估植被的高度。该文通过增加另一个基线的极化干涉SAR数据在一定程度上解决单基线反演技术存在的这个缺陷,并适当改进双基线极化干涉SAR技术,降低植被参数估计的动态偏差,最后用模拟数据和实际数据验证了该方法。
For vegetation parameter inversion, the single baseline polarimetric SAR interferometry technique, such as the three-stage method and the ESPRIT algorithm, is limited by the observed data with the minimum ground to volume amplitude ratio, which effects the estimation of the effective phase center for the vegetation canopy or the surface, and thus results in the underestimated vegetation height. In order to remove this defect of the single baseline inversion techniques in some extend, another baseline polarimetric SAR interferometry data is added on vegetation parameter estimation in this paper, and a dual baseline polarimetric SAR interferometry technique for the extraction of the vegetation parameter is investigated and improved to reduce the dynamic bias for the vegetation parameter estimation. Finally, the simulated data and real data are used to validate this dual baseline technique.