Sensitivity Analysis of DOA Estimation Algorithms to Sensor Errors
Date of Original Version
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
IEEE Transactions on Aerospace and Electronic Systems
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.