Title :
Performance degradation of DOA estimators due to unknown noise fields
Author :
Li, Fu ; Vaccaro, Richard J.
Author_Institution :
Dept. of Electr. Eng., Portland State Univ., Portland, OR, USA
fDate :
3/1/1992 12:00:00 AM
Abstract :
A statistical performance analysis of subspace-based directions-of-arrival (DOA) estimation algorithms in the presence of correlated observation noise with unknown covariance is presented. The analysis of five different estimation algorithms is unified by a single expression for the mean-squared DOA estimation error which is derived using a subspace perturbation expansion. The analysis assumes that only a finite amount of array data is available
Keywords :
noise; signal processing; array data; correlated observation noise; directions-of-arrival; estimation algorithms; mean-squared DOA estimation error; noise fields; performance degradation; signal processing; statistical performance analysis; subspace perturbation expansion; Algorithm design and analysis; Background noise; Colored noise; Crosstalk; Degradation; Direction of arrival estimation; Interference; Performance analysis; Sensor arrays; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on
