Polarimetric Processing of Coherent Random Noise Radar Data for Buried Object Detection

Authors

Yi Xu, University of Nebraska-Lincoln
Ram M. Narayanan, University of Nebraska-Lincoln
Xiojian Xu, University of Nebraska-Lincoln
John O. Curtis, University of Nebraska-Lincoln

Date of this Version

2001

Comments

Published in IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 39, NO. 3, MARCH 2001. Copyright © 2001 IEEE. Used by Permission

Abstract

Random noise polarimetry is a new radar technique for high-resolution probing of subsurface objects and interfaces. The University of Nebraska has developed a polarimetric random noise radar system based on the heterodyne correlation technique. Simulation studies and performance tests on the system confirm its ability to respond to phase differences in the received signals. In addition to polarimetric processing capability and the simplified system design, random noise radar also possesses other desirable features, such as immunity from radio frequency interference (RFI). The paper discusses the theoretical foundations of random noise polarimetry, and presents examples out of the entire data set collected that demonstrate the usefulness of the image processing and Stokes matrix presentation to enhance target detection using the coherent random noise radar.