Study of the experimental performance of AR-based data-extrapolation algorithms for high-resolution radar imaging

Abstract

In this letter, we compare the experimental performance of data-extrapolation algorithms for high-resolution radar imaging. The three methods considered in this paper are based on the autoregressive (AR) model, including the Burg method, the modified covariance method, and the modified covariance method, coupled with singular value decomposition. The performance of each algorithm in terms of extrapolation accuracy is compared using the radar cross-section (RCS) data of an F117 model measured in the compact range facility. (C) 2001 John Wiley & Sons, Inc.