Unified bias analysis for DOA estimation algorithms
F. Li, Yang Lu · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
A statistical analysis using subspace perturbation expansion is applied to the direction of arrival (DOA) estimation bias for MUSIC, Min-Norm, ESPRIT, State-Space Realization (TAM), and Matrix-Pencil algorithms, assuming that only a finite amount of array data is available. The authors obtain an unified analytical expression of the DOA estimation bias for those algorithms in a simple and self-contained fashion. The tractable formula provides insight to the algorithms. Simulation results verify the analytically predicted performance.>