Title :
An extension of the PASTd algorithm to both rank and subspace tracking
Author_Institution :
Dept. of Electr. Eng., Ruhr-Univ., Bochum, Germany
Abstract :
In this letter, we present an extension of the PASTd algorithm to both rank and signal subspace tracking. It has a low computational complexity O(nr), where n is the input vector length, and r denotes the signal subspace dimension. Its performance in tracking time-varying direction of arrival is comparable with that of the expensive eigenvalue decomposition and more robust than the O(n/sup 2/) rank revealing URV updating algorithm proposed by Stewart.<>
Keywords :
computational complexity; direction-of-arrival estimation; eigenvalues and eigenfunctions; signal processing; tracking; PASTd algorithm extension; computational complexity; eigenvalue decomposition; projection approximation subspace tracking with deflation; rank tracking; signal subspace tracking; time-varying direction of arrival; Computational complexity; Computational efficiency; Covariance matrix; Direction of arrival estimation; Eigenvalues and eigenfunctions; Frequency estimation; Multiple signal classification; Music information retrieval; Robustness; Signal processing algorithms;
Journal_Title :
Signal Processing Letters, IEEE
