Title :
A Novel Fast High Resolution Music Algorithm
Author_Institution :
Univ. Pasquale Paoli de Corse, Corte, France
Abstract :
The paper describes new techniques to determine the number of sources for a signal based on LU and QR decomposition. We propose novel methods to calculate the threshold for noise subspace estimation used in high resolution array processing methods without eigenvalue decomposition. The paper states that previous techniques primarily use eigenvectors and eigenvalues. We propose an approximation of MUSIC algorithm. This approximation decreases the computational complexity. A full mathematical evaluation of the technique is provided and simulations show that the approach is effective.
Keywords :
approximation theory; array signal processing; computational complexity; decomposition; eigenvalues and eigenfunctions; signal classification; LU decomposition; QR decomposition; approximation; computational complexity; eigenvalues; eigenvectors; fast high resolution MUSIC algorithm; high resolution array processing; multiple signal classification; noise subspace estimation; Approximation methods; Eigenvalues and eigenfunctions; Estimation; Multiple signal classification; Noise; Sensors; Vectors; Array processing; LU factorization; QR factorization; RRLU; Statistical signal processing; additive noise; algebra; detection; direction-of-arrival (DOA); estimation; highresolution; localization; matrix; number of signal sources; oneigenvalues; thresholds;
Conference_Titel :
Signal Processing Systems (SiPS), 2012 IEEE Workshop on
Conference_Location :
Quebec City, QC
Print_ISBN :
978-1-4673-2986-6
DOI :
10.1109/SiPS.2012.37
