Sensitivity Analysis of DOA Estimation Algorithms to Sensor Errors
Document Type
Article
Date of Original Version
1-1-1992
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. © 1992 IEEE
Publication Title, e.g., Journal
IEEE Transactions on Aerospace and Electronic Systems
Volume
28
Issue
3
Citation/Publisher Attribution
Li, Fu, and Richard J. Vaccaro. "Sensitivity Analysis of DOA Estimation Algorithms to Sensor Errors." IEEE Transactions on Aerospace and Electronic Systems 28, 3 (1992): 708-717. doi: 10.1109/7.256292.
