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

• Published in: IEEE transactions on signal processing Vol. 62; no. 3; pp. 597 - 606
• Main Authors: Yinguang Li, Guifu Zhang, Doviak, Richard J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2014; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Bayes methods; Climatology; Clutter; Detection, estimation, filtering, equalization, prediction; Economic models; Exact sciences and technology; Grounds; Information, signal and communications theory; Likelihood ratio; Meteorological radar; Meteorology; Noise; Radar; Radar clutter; radar detection; radar polarimetry; Signal and communications theory; Signal, noise; Statistical analysis; Statistics; Telecommunications and information theory; Transaction processing; Vectors; Weather; Performance evaluation; Meteorological radar; radar detection; Test statistic; Ground based measurement; Radar polarimetry; Narrow band; Clutter; Statistical method; Radar remote sensing; Innovation; Covariance; Radar clutter; Volume; Likelihood ratio test; Signal processing; Bayes methods; statistical analysis; Meteorology
• DOI: 10.1109/TSP.2013.2293118
• ISSN: 1053-587X

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.