Title :
Most reliable space vector and its application to direction finding
Abstract :
Given a data matrix, we desire a space vector that is the most robust against correlated Gaussian noise perturbations. A closed-form calculation of the most reliable space vector is presented. An attempt to modify the min-norm direction finding algorithm for use in spatio-temporal colored noise is investigated.
Keywords :
Gaussian noise; array signal processing; direction-of-arrival estimation; vectors; DOA estimation; correlated Gaussian noise perturbation; data matrix; direction finding; direction of arrival estimation; min-norm direction finding algorithm; passive sensor arrays; space vector; spatio-temporal colored noise; Colored noise; Direction of arrival estimation; Gaussian noise; Noise measurement; Noise robustness; Null space; Pollution measurement; Probability density function; Sensor arrays; Vectors;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop Proceedings, 2002
Print_ISBN :
0-7803-7551-3
DOI :
10.1109/SAM.2002.1191057
