Journal ArticleDOI
The statistical performance of the MUSIC and the minimum-norm algorithms in resolving plane waves in noise
Mostafa Kaveh,A. Barabell +1 more
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An asymptotic statistical analysis of the null-spectra of two eigen-assisted methods, MUSIC and Minimum-Norm, for resolving independent closely spaced plane waves in noise finds an approximate expression for the resolution threshold of two plane waves with equal power in noise.Abstract:
This paper presents an asymptotic statistical analysis of the null-spectra of two eigen-assisted methods, MUSIC [1] and Minimum-Norm [2], for resolving independent closely spaced plane waves in noise. Particular attention is paid to the average deviation of the null-spectra from zero at the true angles of arrival for the plane waves. These deviations are expressed as functions of signal-to-noise ratios, number of array elements, angular separation of emitters, and the number of snapshots. In the case of MUSIC. an approximate expression is derived for the resolution threshold of two plane waves with equal power in noise. This result is validated by Monte Carlo simulations.read more
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Two decades of array signal processing research: the parametric approach
Hamid Krim,Mats Viberg +1 more
TL;DR: The article consists of background material and of the basic problem formulation, and introduces spectral-based algorithmic solutions to the signal parameter estimation problem and contrast these suboptimal solutions to parametric methods.
Journal ArticleDOI
MUSIC, maximum likelihood, and Cramer-Rao bound
Petre Stoica,Nehorai Arye +1 more
TL;DR: The Cramer-Rao bound (CRB) for the estimation problems is derived, and some useful properties of the CRB covariance matrix are established.
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Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations
TL;DR: This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them.
Journal ArticleDOI
Nested Arrays: A Novel Approach to Array Processing With Enhanced Degrees of Freedom
Piya Pal,P.P. Vaidyanathan +1 more
TL;DR: A new array geometry, which is capable of significantly increasing the degrees of freedom of linear arrays, is proposed and a novel spatial smoothing based approach to DOA estimation is also proposed, which does not require the inherent assumptions of the traditional techniques based on fourth-order cumulants or quasi stationary signals.
Journal ArticleDOI
Performance analysis of Root-Music
Bhaskar D. Rao,K.V.S. Hari +1 more
TL;DR: In this article, the authors analyzed the performance of Root-Music, a variation of the MUSIC algorithm, for estimating the direction of arrival (DOA) of plane waves in white noise in the case of a linear equispaced sensor array.
References
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Journal ArticleDOI
Multiple emitter location and signal parameter estimation
TL;DR: In this article, a description of the multiple signal classification (MUSIC) algorithm, which provides asymptotically unbiased estimates of 1) number of incident wavefronts present; 2) directions of arrival (DOA) (or emitter locations); 3) strengths and cross correlations among the incident waveforms; 4) noise/interference strength.
Book
Time Series: Data Analysis and Theory
TL;DR: This book will be most useful to applied mathematicians, communication engineers, signal processors, statisticians, and time series researchers, both applied and theoretical.
Journal ArticleDOI
Estimating the Angles of Arrival of Multiple Plane Waves
Ramdas Kumaresan,Donald W. Tufts +1 more
TL;DR: In this article, a polynomial D(z) with special properties is constructed from the eigenvectors of C, the zeros of which give estimates of the angle of arrival.
Journal ArticleDOI
Optimality of high resolution array processing using the eigensystem approach
G. Bienvenu,L. Kopp +1 more
TL;DR: In this article, a covariance matrix test for equality of the smallest eigenvalues is presented for source detection, and a best fit method and a test of orthogonality between the "smallest" eigenvectors and the "source" vectors are discussed.
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