Direction-of-arrival estimation by subspace rotation methods - ESPRIT

Abstract

Results of simulations comparing the performance of ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) and the MUSIC (MUltiple Signal Classification) algorithm are presented. ESPRIT exploits an underlying rotational invariance among signal subspaces induced by an array of sensors with a translational invariance structure. In contrast, the MUSIC algorithm uses intersections between the array manifold and the signal subspace to estimate the directions. ESPRIT is shown to have performance advantages over MUSIC in certain scenarios apart from its previously reported implementational advantages.