Subspace tracking with quasi-rectangular data windows

Daniel J. Rabideau

doi:10.1117/12.487346

25 August 2003 Subspace tracking with quasi-rectangular data windows

Daniel J. Rabideau

Proceedings Volume 5096, Signal Processing, Sensor Fusion, and Target Recognition XII; (2003) https://doi.org/10.1117/12.487346
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

In signal processing, it is often necessary to decompose sampled data into its principal components. In adaptive sensor array processing, for example, Singular Value Decomposition (SVD) and/or Eigenvalue Decomposition (EVD) can be used to separate sensor data into “signal” and “noise” subspaces. Such decompositions are central to a number of techniques, such as MUSIC, ESPIRIT, and the Eigencanceller. Unfortunately, SVD and EVD algorithms are computationally intensive. When the underlying signals are nonstationary, “fast subspace tracking” methods provide a far less complex alternative to standard SVD methods. This paper addresses a class of subspace tracking methods known as “QR-Jacobi methods.” These methods can track the r principal eigenvectors of a correlation matrix in O(Nr) operations, where N is the dimensionality of the correlation matrix. Previously, QR-Jacobi methods have been formulated to track the principal eigenvectors of an “exponentially windowed” data correlation matrix. Finite duration data windowing strategies were not addressed. This paper extends the prior QR-Jacobi methods so as to implement rectangular sliding data windows, as well as other windows. Illustrated examples are provided.

Citation Download Citation

Daniel J. Rabideau "Subspace tracking with quasi-rectangular data windows", Proc. SPIE 5096, Signal Processing, Sensor Fusion, and Target Recognition XII, (25 August 2003); https://doi.org/10.1117/12.487346

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available