URV ESPRIT FOR TRACKING TIME-VARYING SIGNALS

ESPRIT is an algorithm for determining the fixed directions of arrival of a set of narrowband signals at an array of sensors. Unfortunately, its computational burden makes it unsuitable for real time processing of signals with time-varying directions of arrival. In this work we d evelop a new implementation of ESPRIT that has potential for real time processing. It is based on a rank-revealing URV decomposition, rather than the eigendecomposition or singular value decomposition used in p revious ESPRIT algorithms. We demonstrate its performance on simulated data representing both constant and time-varying signals. We find tha t the URV-based ESPRIT algorithm is effective for estimating time-vary ing directions-of-arrival at considerable computational savings over t he SVD-based algorithm.