Title :
Fast rank-adaptive beamforming
Author_Institution :
Mission Res. Corp., Monterey, CA, USA
Abstract :
This paper is concerned with the construction of an adaptive beamformer, which uses the dominant subspace information of a sample covariance matrix. We assume that the sample covariance matrix and its eigenvalue decomposition (EVD) are to be updated as data arrive. We present a unified structure for updating the EVD and introduce a robust method for adapting the rank of the dominant subspace. We use the EVD of the sample covariance matrix to build a fast rank-and weight-adaptive beamformer. A useful component of the beamforming routine is a fast algorithm for updating the estimates of the direction of arrival of the dominant sources
Keywords :
array signal processing; covariance matrices; direction-of-arrival estimation; eigenvalues and eigenfunctions; DOA estimation; EVD update structure; adaptive beamformer; direction of arrival estimation; dominant sources; dominant subspace information; eigenvalue decomposition; fast algorithm; fast rank-adaptive beamforming; sample covariance matrix; spectral decomposition; Algorithm design and analysis; Array signal processing; Bibliographies; Covariance matrix; Eigenvalues and eigenfunctions; Joining processes; Matrix decomposition; Performance evaluation; Robustness; Stochastic processes;
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-6339-6
DOI :
10.1109/SAM.2000.877969
