基于酉ESPRIT算法的极化干涉相位估计

目前SAR极化干涉测量地形参数已经成为一种新兴的前沿技术。在现有提取极化干涉相位的技术中,由空间谱估计理论发展而来的,利用MUSIC、TLS-ESPRIT算法获取干涉相位信息的方法正逐步完善起来。但由于SAR信号存在散射点的观测数据少的问题,利用上述方法往往不能得到更高精度的干涉相位。作者提出的基于酉ESPRIT算法估算干涉相位的方法,充分利用了复观测数据以及共轭数据中的信息,使得观测数据等效增加了一倍,从而提高了植被高度参数的估计精度。本文详细阐述了该方法的原理和实施步骤,并通过对SIR-C/X-SAR的L波段实际数据进行验证处理,表明酉ESPRIT算法十分有效。

Unitary ESPRIT-based phase estimation for polarimetric SAR interferometry

At present,poiarimetric SAR interferometry has being a kind of new technology of measuring the terrain parameters.Among known methods of extracting interferometric phase,some methods that are developed from spatial spectrum estimation and extracting interferometric phase by MUSIC or TLS-ESPRIT algorithm have been becoming more perfect.But these methods can not get higher phase precision because the SAR signals only have few observation data.An interferometric phase estimated method by Unitary ESPRIT-based can improve estimated precision using the complex observation data and its conjugated data.In this paper,the algorithm is proposed and described in detail.Using SIR-C/X-SAR L band data,its effectiveness is tested.