| 植被高度的极化干涉互协方差矩阵分解反演法 |
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| 引用本文： | 宋桂萍,汪长城,付海强,解清华.植被高度的极化干涉互协方差矩阵分解反演法[J].测绘学报,2014,43(6):613-636. |
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| 作者姓名： | 宋桂萍 汪长城 付海强 解清华 |
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| 作者单位： | 1. 中南大学地球科学与信息物理学院;
2. 中南大学 |
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| 基金项目： | 国家自然科学基金(41371335);国家863计划(2012AA121301;2011AA120404);测绘遥感信息工程国家重点实验室开放基金(11R03);湖南省自然科学基金(12JJ4035) |
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| 摘 要： | 经典三阶段极化干涉SAR植被高反演算法中地面散射相位估计不准确，从而导致植被高反演精度存在偏差。针对这一关键问题，本文提出基于极化干涉互协方差矩阵分解的植被高度反演新方法。该方法利用Freeman分解理论和极化干涉互协方差矩阵，估计出更准确的地面散射相位；然后，结合RVOG模型反演植被高度。利用欧空局（ESA）的软件PolSARpro模拟的L波段极化SAR数据和亚马逊森林地区的ALOS PALSAR L波段数据进行实验，结果表明本文提出的新算法提取的植被高度相比经典三阶段法精度更高，从而验证了算法的有效性和可靠性。
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| 关 键 词： | 极化干涉SAR 植被高度反演 极化干涉互协方差矩阵 地面随机体散射模型 |
| 收稿时间： | 2012-12-03 |
| 修稿时间： | 2013-05-13 |
A Novel Vegetation Height Inversion Method Based on Polarimetric Interferometric Covariance Matrix Decomposition |
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| Abstract: | Vegetation height inversion results of three-stage inversion process for polarimetric SAR interferometry are seriously affected by the inaccuracies of the underlying ground topographic phase estimation. In order to solve this problem, this paper proposes a new algorithm. This algorithm which combines the Freeman-Durden polarimetric decomposition concept and polarimetric interferometry covariance matrix decomposition obtains the more accurate results. Then it can estimate the vegetation height by applying the RVOG model. Finally, the validity of the proposed algorithm has been tested with the simulated L-band PolInSAR data from PolSARProSim software by ESA and real ALOS PALSAR data covered Amazon forest, and the experiment results show the proposed algorithm is more accurate than the tranditional three-stage inversion process. |
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