Statistical comparison of subspace based DOA estimation algorithms in the presence of sensor errors

Abstract

A non-asymptotic statistical performance analysis using matrix approximation is applied to subspace based algorithms for direction-of-arrival (DOA) estimation in the presence of sensor errors. In particular, the MUSIC, min-norm, state-space realization (TAM and DDA) and ESPRIT algorithms are analyzed. An analytical expression of the variance of the DOA estimation error is developed for theoretical comparison in a greatly simplified and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analysis.<>