TY - JOUR

T1 - A New Approach to Array Geometry for Improved Spatial Spectrum Estimation

AU - Pillai, S. Unnikrishna

AU - Bar-Ness, Yeheskel

AU - Haber, Fred

PY - 1985/10

Y1 - 1985/10

N2 - In this letter, we address the problem of element placement in a linear aperiodic array for use in spatial spectrum estimation. By making use of a theorem by Caratheodory, it is shown that, for a given number of elements, there exists a distribution of element positions which, for uncorrelated sources, results in superior spatial spectrum estimators than are otherwise achievable. The improvement is obtained by constructing an augmented covariance matrix, made possible by the choice of element positions, with dimension greater than the number of array elements. The augmented matrix is then used in any of the known spectrum estimation methods in conjunction with a correspondingly augmented search pointing vector. Examples are given to show the superior detection capability, the larger dynamic range for spectral peak to background level, the lower sidelobes, and the relatively low bias values, when one of the known spectrum estimation techniques based on eigenstructure is used.

AB - In this letter, we address the problem of element placement in a linear aperiodic array for use in spatial spectrum estimation. By making use of a theorem by Caratheodory, it is shown that, for a given number of elements, there exists a distribution of element positions which, for uncorrelated sources, results in superior spatial spectrum estimators than are otherwise achievable. The improvement is obtained by constructing an augmented covariance matrix, made possible by the choice of element positions, with dimension greater than the number of array elements. The augmented matrix is then used in any of the known spectrum estimation methods in conjunction with a correspondingly augmented search pointing vector. Examples are given to show the superior detection capability, the larger dynamic range for spectral peak to background level, the lower sidelobes, and the relatively low bias values, when one of the known spectrum estimation techniques based on eigenstructure is used.

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U2 - 10.1109/PROC.1985.13324

DO - 10.1109/PROC.1985.13324

M3 - Article

AN - SCOPUS:0022136860

SN - 0018-9219

VL - 73

SP - 1522

EP - 1524

JO - Proceedings of the IEEE

JF - Proceedings of the IEEE

IS - 10

ER -