Paper Info
Title
Bias analysis of the MUSIC location estimator
Abstract
The authors present a rigorous bias analysis of the MUSIC location estimator, and they derive an accurate and concise bias expression. The analysis is based on the second-order Taylor series expansion of the derivative of the null spectrum, properties of the null spectrum, and statistics of the estimated signal eigenvectors. It is proven that in the derivation the remainder term in the second-order Taylor series can be dropped but the second-order terms cannot be. Simulations verify that the bias expression is valid over a wide range of signal-to-noise ratios (SNRs) extending down into the resolution threshold region of MUSIC. Although asymptotic, this expression can be accurately applied to a limited number of snapshot cases. The utility of the expression is shown by using it in a study of MUSIC location estimator characteristics. Estimate bias and standard deviation are compared for variations in SNR, numbers of sensors and snapshots, and source correlation. MUSIC resolvability and estimator performance bounds are addressed, accounting for bias
Year
DOI
Venue
1992
10.1109/78.157296
IEEE Transactions on Signal Processing
Keywords
Field
DocType
array signal processing,eigenvalues and eigenfunctions,spectral analysis,statistical analysis,MUSIC location estimator,SNR,array signal processing,asymptotic expression,bias analysis,estimated signal eigenvectors,estimator performance bounds,null spectrum,resolution threshold,second-order Taylor series expansion,sensors,signal statistics,signal-to-noise ratios,simulations,snapshot,source correlation,standard deviation
Signal processing,Control theory,Remainder,Algorithm,Bias of an estimator,Statistics,Standard deviation,Eigenvalues and eigenvectors,Mathematics,Estimator,Taylor series,Consistent estimator
Journal
Volume
Issue
ISSN
40
10
1053-587X
Citations 
PageRank 
References 
39
6.81
11
Authors
2
Name
Order
Citations
PageRank
X. Xu112940.35
K. Buckley211634.21