Title :
MUSIC, G-MUSIC, and Maximum-Likelihood Performance Breakdown
Author :
Johnson, Ben A. ; Abramovich, Yuri I. ; Mestre, Xavier
Author_Institution :
Inst. for Telecommun. Res., Univ. of South Australia, Mawson Lakes, SA
Abstract :
Direction-of-arrival estimation performance of MUSIC and maximum-likelihood estimation in the so-called ldquothresholdrdquo area is analyzed by means of general statistical analysis (GSA) (also known as random matrix theory). Both analytic predictions and direct Monte Carlo simulations demonstrate that the well-known MUSIC-specific ldquoperformance breakdownrdquo is associated with the loss of resolution capability in the MUSIC pseudo-spectrum, while the sample signal subspace is still reliably separated from the actual noise subspace. Significant distinctions between (MUSIC/G-MUSIC)-specific and MLE-intrinsic causes of ldquoperformance breakdown,rdquo as well as the role of ldquosubspace swaprdquo phenomena, are specified analytically and supported by simulation.
Keywords :
Monte Carlo methods; array signal processing; direction-of-arrival estimation; matrix algebra; maximum likelihood estimation; random processes; G-MUSIC; MUSIC pseudo-spectrum; Monte Carlo simulations; actual noise subspace; drection-of-arrival estimation; general statistical analysis; maximum-likelihood estimation; maximum-likelihood performance breakdown; random matrix theory; Australia; Covariance matrix; Electric breakdown; Maximum likelihood detection; Maximum likelihood estimation; Multiple signal classification; Performance analysis; Signal analysis; Signal resolution; Statistical analysis; Array signal processing; G-estimation; generalized likelihood-ratio tests; signal detection and estimation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2008.921729