Title :
Noniterative subspace tracking
Author :
DeGroat, Ronald D.
Author_Institution :
Erik Jonsson Sch. of Eng. & Comput. Sci., Texas Univ., Richardson, TX, USA
fDate :
3/1/1992 12:00:00 AM
Abstract :
A rank-one spherical subspace update that is appropriate for subspace-based methods like MUSIC and minimum norm is introduced. This noniterative, highly parallel, numerically stabilized, subspace update is closely related to rank-one eigenstructure updating. However, a rank-one subspace update involves less computation than simple rank-one correlation accumulation. Moreover. The frequency tracking capabilities of the noniterative subspace update are virtually identical to and in some case more robust than the more computationally expensive eigen-based methods
Keywords :
matrix algebra; signal processing; DOA problems; MUSIC; direction of arrival; frequency tracking; minimum norm; noniterative subspace tracking; noniterative subspace update; rank-one spherical subspace update; signal processing; subspace-based methods; Computer science; Costs; Eigenvalues and eigenfunctions; Frequency; Instruments; Matrix decomposition; Multiple signal classification; Robustness; Signal resolution; Space technology;
Journal_Title :
Signal Processing, IEEE Transactions on