COMPRESSIVE SENSING FOR NEUTROSPHERIC WATER VAPOR TOMOGRAPHY USING GNSS AND INSAR OBSERVATIONS

被引：0

作者：

Heublein, Marion ^{[1
,2
]}

Zhu, Xiao Xiang ^{[1
,3
]}

Alshawaf, Fadwa ^{[2
]}

Mayer, Michael ^{[4
]}

Bamler, Richard ^{[1
,3
]}

Hinz, Stefan ^{[2
]}

机构：

[1] German Aerosp Ctr DLR, Remote Sensing Technol Inst, Oberpfaffenhofen, Germany

[2] Karlsruhe Inst Technol, Inst Photogrammetry & Remote Sensing, D-76021 Karlsruhe, Germany

[3] Tech Univ Munich, Chair Remote Sensing Technol, D-80290 Munich, Germany

[4] Karlsruhe Inst Technol, Geodet Inst, D-76021 Karlsruhe, Germany

来源：

2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年

关键词：

Atmospheric modeling; tomographic reconstruction; Compressive Sensing; GNSS; InSAR;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents the innovative Compressive Sensing (CS) concept for tomographic reconstruction of 3D neutrospheric water vapor fields using data from Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). The Precipitable Water Vapor (PWV) input data are derived from simulations of the Weather Research and Forecasting modeling system. We apply a Compressive Sensing based approach for tomographic inversion. Using the Cosine transform, a sparse representation of the water vapor field is obtained. The new aspects of this work include both the combination of GNSS and InSAR data for water vapor tomography and the sophisticated CS estimation: The combination of GNSS and InSAR data shows a significant improvement in 3D water vapor reconstruction; and the CS estimation produces better results than a traditional Tikhonov regularization with.. 2 norm penalty term.

引用

页码：5268 / 5271

页数：4