基于卡尔曼滤波的PS-InSAR地表形变预测方法

doi:10.7523/j.issn.2095-6134.2017.06.011

中国科学院大学学报 ›› 2017, Vol. 34 ›› Issue (6): 743-750.DOI: 10.7523/j.issn.2095-6134.2017.06.011

基于卡尔曼滤波的PS-InSAR地表形变预测方法

刘星^1,2,3, 吕孝雷^1,2

1. 中国科学院电子学研究所, 北京 100190;
2. 中国科学院空间信息处理与应用系统技术重点实验室, 北京 100190;
3. 中国科学院大学, 北京 100049

收稿日期:2016-12-08 修回日期:2017-02-27 发布日期:2017-11-15
通讯作者: 刘星
基金资助:
中国科学院"百人计划"项目（Y53Z180390）和民政部国家减灾中心项目（8435-01）资助

PS-InSAR surface deformation prediction method based on Kalman filter

LIU Xing^1,2,3, LÜ Xiaolei^1,2

1. Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China;
2. Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2016-12-08 Revised:2017-02-27 Published:2017-11-15

摘要/Abstract

摘要： PS-InSAR是用于监测大范围地表形变的微波遥感技术，可提供精确地表形变信息，但该技术无法对形变趋势进行预测。现有形变预测方法只能预测少数监测点的形变，不适用于大面积预测。针对这些问题，提出一种基于卡尔曼滤波的PS-InSAR地表形变预测方法。结合PS-InSAR方法的技术流程，从理论上推导设计卡尔曼滤波器，通过真实的多时相SAR数据对该方法进行验证。实验结果表明，该算法可充分利用PS-InSAR形变监测信息，有效预测大面积观测区域的形变趋势。

关键词: 永久散射体技术, 卡尔曼滤波, 形变预测, 数据处理

Abstract: PS-InSAR is a microwave remote sensing technique which provides high-resolution maps of large-scale ground displacement. However, it is incapable of deformation prediction. The existing deformation prediction approaches can be only applied to a few point targets, but are limited in monitoring relatively large areas. In this work, a surface deformation prediction method of PS-InSAR is proposed based on Kalman filter. First, the process of PS-InSAR is outlined. Then a Kalman filter is designed theoretically. Finally, the experiments performed on the real multi-temporal SAR data confirm the validity of the proposed method. The experimental results show that the proposed approach makes full use of the displacement information acquired from PS-InSAR and effectively predicts the trend of ground deformation over wide areas.

Key words: PS-InSAR, Kalman filter, deformation prediction, data procession

中图分类号:

TN957

刘星, 吕孝雷. 基于卡尔曼滤波的PS-InSAR地表形变预测方法[J]. 中国科学院大学学报, 2017, 34(6): 743-750.

LIU Xing, LÜ Xiaolei. PS-InSAR surface deformation prediction method based on Kalman filter[J]. , 2017, 34(6): 743-750.

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基于卡尔曼滤波的PS-InSAR地表形变预测方法

PS-InSAR surface deformation prediction method based on Kalman filter

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