Compressed Sensing Applied to Weather Radar

被引：24

作者：

Mishra, Kumar Vijay ^{[1
]}

Kruger, Anton ^{[1
]}

Krajewski, Witold F. ^{[1
]}

机构：

[1] Univ Iowa, Iowa City, IA 52242 USA

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

compressed sensing; remote sensing; matrix completion; weather radar; dwell time;

D O I：

10.1109/IGARSS.2014.6946811

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：

We propose an innovative meteorological radar, which uses reduced number of spatiotemporal samples without compromising the accuracy of target information. Our approach extends recent research on compressed sensing (CS) for radar remote sensing of hard point scatterers to volumetric targets. The previously published CS-based radar techniques are not applicable for sampling weather since the precipitation echoes lack sparsity in both range-time and Doppler domains. We propose an alternative approach by adopting the latest advances in matrix completion algorithms to demonstrate the sparse sensing of weather echoes. We use Iowa X-band Polarimetric (XPOL) radar data to test and illustrate our algorithms.

引用

页码：1832 / 1835

页数：4

共 21 条

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[2]

Baraniuk Richard, 2007, 2007 IEEE Radar Conference, P128, DOI 10.1109/RADAR.2007.374203

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