Complex Least Squares Adjustment to Improve Tree Height Inversion Problem in PolInSAR

论文摘要

At present,the principal data processing methods involving complex observations are based on two strategies according to characteristics of the observation process,i.e.,step-by-step and direct resolution. However,these strategies have some limitations,e.g. they cannot consider statistical observation error information,redundant observations and so on. This paper applies least squares methods to complex data processing to extend surveying adjustment theory from real to complex number space. We compared the two adjustment criteria for a complex domain in a quantitative way. In order to understand the effectiveness of complex least squares,tree height inversion from PolInSAR data is taken as an example. We firstly established both a complex adjustment function model and a stochastic model for PolInSAR tree height inversion,and then applied the complex least squares method to estimate tree height. Results show that the complex least squares approach is reliable and outperforms other classic tree height retrieval methods; the method is simple and easy to implement.

论文目录

文章来源

类型: 期刊论文

作者: Jianjun ZHU,Qinghua XIE,Tingying ZUO,Changcheng WANG,Jian XIE

来源: Journal of Geodesy and Geoinformation Science 2019年01期

年度: 2019

分类: 基础科学,农业科技

专业: 自然地理学和测绘学,林业

单位: School of Geosciences and Info-Physics,Central South University

基金: The National Natural Science Foundation of China (41274010,40974007,40901172),National Key Basic Research and Development Program of China (2012AA121301),Hunan Provincial Natural Science Foundation of China (12JJ4035),Postgraduate Autonomous Exploration Project of Central South University (2013zzts055),China Scholarship Council (201406370079)

分类号: P237;S758

页码: 1-8

总页数: 8

文件大小: 814K

下载量: 3

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