Title :
Subspace Tracking in Colored Noise Based on Oblique Projection
Author :
Chen, Minhua ; Wang, Zuoying
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing
Abstract :
Projection approximation subspace tracking (PAST) algorithm gives biased subspace estimation when the received signal is corrupted by colored noise. In this paper, an unbiased version of PAST is proposed for the colored noise scenario. Firstly, a maximum likelihood (ML) and minimum variance unbiased (MVUB) estimator for the clean signal is derived using simultaneous diagonalization and oblique projection. Then, we provide a recursive algorithm, named oblique PAST (obPAST), to track the signal subspace and update the estimator in colored noise. Experimental results show the effectiveness of the obPAST algorithm
Keywords :
approximation theory; covariance matrices; maximum likelihood estimation; noise; signal processing; colored noise; covariance matrix; maximum likelihood estimator; minimum variance unbiased estimator; oblique projection; projection approximation subspace tracking; signal subspace; simultaneous diagonalization; Approximation algorithms; Colored noise; Covariance matrix; Eigenvalues and eigenfunctions; Matrix decomposition; Maximum likelihood estimation; Recursive estimation; Signal processing algorithms; Singular value decomposition; White noise;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location :
Toulouse
Print_ISBN :
1-4244-0469-X
DOI :
10.1109/ICASSP.2006.1660714
