Title :
Sensitivity analysis of DOA estimation algorithms to sensor errors
Author :
Li, Fu ; Vaccaro, Richard J.
Author_Institution :
Dept. of Electr. Eng., Portland State Univ., OR, USA
fDate :
7/1/1992 12:00:00 AM
Abstract :
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
Keywords :
estimation theory; parameter estimation; sensitivity analysis; signal detection; signal processing; statistical analysis; direction of arrival estimation; estimation of signal parameters; mean-squared error; min-norm; multiple signal classification; rotational invariance; sensitivity analysis; sensor errors; simulation; state-space; subspace perturbation expansions; unified statistical performance analysis; Algorithm design and analysis; Analytical models; Array signal processing; Biomedical signal processing; Direction of arrival estimation; Multiple signal classification; Parameter estimation; Performance analysis; Radar signal processing; Sensitivity analysis; Signal analysis; Signal processing algorithms; State estimation;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
