Title :
Statistical comparison of subspace based DOA estimation algorithms in the presence of sensor errors
Author :
Li, Fu ; Vaccaro, Richard
Author_Institution :
Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA
Abstract :
A non-asymptotic statistical performance analysis using matrix approximation is applied to subspace based algorithms for direction-of-arrival (DOA) estimation in the presence of sensor errors. In particular, the MUSIC, min-norm, state-space realization (TAM and DDA) and ESPRIT algorithms are analyzed. An analytical expression of the variance of the DOA estimation error is developed for theoretical comparison in a greatly simplified and self-contained fashion. The tractable formulas provide insight into the algorithms. Simulation results verify the analysis.<>
Keywords :
error statistics; parameter estimation; signal processing; statistical analysis; DDA; DOA estimation error; ESPRIT; MUSIC; TAM; array signal processing; direction-of-arrival; matrix approximation; min-norm algorithm; nonasymptotic statistical performance analysis; sensor errors; state-space realization; subspace based algorithms; Algorithm design and analysis; Approximation algorithms; Array signal processing; Covariance matrix; Direction of arrival estimation; Estimation error; Performance analysis; Radar signal processing; Sensor arrays; Signal processing algorithms;
Conference_Titel :
Spectrum Estimation and Modeling, 1990., Fifth ASSP Workshop on
Conference_Location :
Rochester, NY, USA
DOI :
10.1109/SPECT.1990.205601
