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Sensitivity analysis of DOA estimation algorithms to sensor errors

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2 Author(s)
F. Li ; Dept. of Electr. Eng., Portland State Univ., OR, USA ; R. J. Vaccaro

A unified statistical performance analysis using subspace perturbation expansions is applied to subspace-based algorithms for direction-of-arrival (DOA) estimation in the presence of sensor errors. In particular, the multiple signal classification (MUSIC), min-norm, state-space realization (TAM and DDA) and estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithms are analyzed. This analysis assumes that only a finite amount of data is available. An analytical expression for the mean-squared error of the DOA estimates is developed for theoretical comparison in a simple and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analysis

Published in:

IEEE Transactions on Aerospace and Electronic Systems  (Volume:28 ,  Issue: 3 )