| 复数域最小二乘平差及其在POLInSAR植被高反演中的应用 |
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| 引用本文： | 朱建军,解清华,左廷英,汪长城,谢建.复数域最小二乘平差及其在POLInSAR植被高反演中的应用[J].测绘学报,2014,43(1):45-51. |
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| 作者姓名： | 朱建军 解清华 左廷英 汪长城 谢建 |
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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： | 国家自然科学基金项目;国家自然科学基金项目 |
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| 摘 要： | 传统的测量观测值都是实数，因此测量平差都是在实数空间中进行的。然而，随着科学技术的快速发展，现代测绘领域中出现了一些用复数表示的观测数据。与实数数据一样，这些复数数据同样面临着如何从带有误差的观测值中找出未知量的最佳估计值的问题。但目前涉及复数观测的数据处理时，主要还是依据观测过程，分步或直接解算，不能考虑观测误差、多余观测信息等。针对这一情况，本文介绍了复数域中数据处理的最小二乘方法，试图将测量平差从实数域推广到复数域，并定量研究了两种平差准则的优劣性。为了了解复数域最小二乘的有效性，本文以极化干涉SAR植被高反演为例，建立复数域平差函数模型和随机模型，构建复数域最小二乘法反演植被高。结果表明该算法反演的植被高结果可靠，其精度优于经典植被高反演算法，且计算简单，易于实现。
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| 关 键 词： | 测量平差 复数域最小二乘 极化干涉SAR 植被高反演 三阶段算法 |
| 收稿时间： | 2012-08-17 |
| 修稿时间： | 2013-02-04 |
Complex Least Squares Adjustment and Its Application in Tree Height Inversion with POLInSAR Data |
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| Abstract: | The surveying observations in traditional geodesy and remote sensing usually are real numbers, so the theory of surveying adjustment is based on real space. However, in modern geodesy and remote sensing, more and more observations are expressed in complex form. As same as the real number observations, the complex number observations are also facing the problem that how to identify the best estimations of unknown parameters from the observations with errors. However, data processing methods involving complex observations are mainly step-by-step or direct solver based on the observation process which cannot consider observation errors, redundant observation and so on. For this situation, this paper introduces least squares methods of complex data processing and tries to extend surveying adjustments from the real number space to the complex number space. Meanwhile, the two adjustment criteria in complex domain are compared quantitatively. In order to understand effectiveness of complex least squares, the tree height inversion from POLInSAR data is taken as an example. We firstly establish complex adjustment function model and stochastic model for POLInSAR tree height inversion and apply complex least squares method to estimate tree height. The results show that the complex least squares approach is reliable and better than other classic tree height retrieval methods. Besides, the method is simple and easy to realize. |
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| Keywords: | Surveying adjustment Complex least squares Polarimetric interferometric SAR (POLInSAR) Tree height inversion Three-stage algorithm |
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