A Linear Array For Covariance Differencing Via Hyperbolic SVD

A. Bojanczyk; A. Steinhardt

doi:10.1117/12.962269

14 November 1989 A Linear Array For Covariance Differencing Via Hyperbolic SVD

A. Bojanczyk, A. Steinhardt

Proceedings Volume 1152, Advanced Algorithms and Architectures for Signal Processing IV; (1989) https://doi.org/10.1117/12.962269
Event: 33rd Annual Technical Symposium, 1989, San Diego, United States

Abstract

We consider a problem pertaining to bearing estimation in unknown noise using the covariance differencing approach, and propose a linear array of processors which exhibits a linear speed-up with respect to a uniprocessor system. Our solution hinges on a new canonic matrix factorization which we term the hyperbolic singular value decomposition. The parallel algorithm for hyperbolic SVD based bearing estimation is an adaptation of a well known biorthogonalization technique developed by Hestenes. Parallel implementations of the algorithm are based on earlier works on one-sided Jacobi methods. It turns out that strategies for parallelization of Jacobi methods are equally well applicable for computing the hyperbolic singular value decomposition.

Citation Download Citation

A. Bojanczyk and A. Steinhardt "A Linear Array For Covariance Differencing Via Hyperbolic SVD", Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989); https://doi.org/10.1117/12.962269

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