Paper Info
Title
Numerically stable method of signal subspace estimation based on multistage Wiener filter.
Abstract
In this paper, a numerically stable method of signal subspace estimation based on Householder multistage Wiener filter (HMSWF) is proposed. Numerical stability of the method lies on the fact that the Householder matrix in HMSWF ensures the unitary blocking operation and significantly strengthens the orthogonality of basis vectors, especially in the finite-precision implementation. In the following, we analyze the numerical stability of HMSWF and MSWF based on the correlation subtractive structure (CSS-MSWF) by establishing the equivalence between the forward recursion of MSWF and the Arnoldi algorithm in numerical linear algebra. Besides, the equivalence between HMSWF and the Householder QR decomposition (QRD) on the Krylov matrix underlying in MSWF is directly established. Based on the relationship, two theoretical upper bounds of the orthogonality error of basis vectors in signal subspace are obtained and it is demonstrated that the orthogonality of basis vectors based on HMSWF is perfectly preserved by the numerically well-behaved Householder matrix, and the corresponding signal subspace estimation is much more numerically stable than that based on CSS-MSWF. Simulations show the numerical stability of the proposed method of signal subspace estimation by HMSWF.
Year
DOI
Venue
2010
10.1007/s11432-010-4103-9
SCIENCE CHINA Information Sciences
Keywords
Field
DocType
upper bound,qr decomposition,wiener filter,numerical stability,numerical linear algebra
Wiener filter,Mathematical optimization,Orthogonality,Householder's method,Householder transformation,Signal subspace,QR decomposition,Numerical linear algebra,Numerical stability,Mathematics
Journal
Volume
Issue
ISSN
53
12
null
Citations 
PageRank 
References 
2
0.44
8
Authors
4
Name
Order
Citations
PageRank
Xuebin Zhuang120.44
X. W. Cui221926.61
Mingquan Lu312230.09
Zhenming Feng4839.77