Ground Clutter Detection Using the Statistical Properties of Signals Received With a Polarimetric Radar

Polarimetric weather radars provide additional measurements that allow better characterization of the targeted medium. Because ground clutter has different polarimetric characteristics from weather echoes, dual-polarization measurements can be used to distinguish one from the other. Ground clutter a...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on signal processing Vol. 62; no. 3; pp. 597 - 606
Main Authors Yinguang Li, Guifu Zhang, Doviak, Richard J.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.02.2014
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Polarimetric weather radars provide additional measurements that allow better characterization of the targeted medium. Because ground clutter has different polarimetric characteristics from weather echoes, dual-polarization measurements can be used to distinguish one from the other. Ground clutter and weather signals also have different statistical properties which can be utilized to distinguish one from the other. A test statistic, obtained from the generalized likelihood ratio test (GLRT), and a simple Bayesian classifier (SBC), with inputs from the mean and covariance of the received signals, are developed to detect ground clutter in the presence of weather signals. It is found that the test statistic produces false detections caused by narrow-band zero-velocity weather signals while the SBC can effectively neutralize them. This work is aimed at detecting ground clutter based solely on data from each resolution volume. The performances of the test statistic and SBC are shown by applying them to radar data collected with the University of Oklahoma-Polarimetric Radar for Innovation in Meteorology and Engineering.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2013.2293118