Spatial Correlation for DoA Characterization Using Von Mises, Cosine, and Gaussian Distributions | Zendy

Wamberto J. L. Queiroz | Zendy; Francisco Madeiro | Zendy; Waslon T. A. Lopes | Zendy; Marcelo S. Alencar | Zendy

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Spatial Correlation for DoA Characterization Using Von Mises, Cosine, and Gaussian Distributions

Author(s) -

Wamberto J. L. Queiroz,

Francisco Madeiro,

Waslon T. A. Lopes,

Marcelo S. Alencar

Publication year - 2011

Publication title -

international journal of antennas and propagation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.282

H-Index - 37

eISSN - 1687-5877

pISSN - 1687-5869

DOI - 10.1155/2011/540275

Subject(s) - von mises yield criterion , von mises distribution , trigonometric functions , bessel function , gaussian , mathematics , coupling (piping) , spatial correlation , direction of arrival , antenna (radio) , mathematical analysis , physics , geometry , finite element method , computer science , engineering , telecommunications , statistics , mechanical engineering , quantum mechanics , thermodynamics

This paper presents mathematical expressions forthe spatial correlation between elements of linear and circularantenna arrays, considering cosine, Gaussian, and Von Mises distributions,for the direction of arrival (DoA) of the electromagneticwaves at the receiver antenna. The expressions obtained for theVon Mises distribution can include or not the mutual couplingeffect between the elements and are simpler than those obtainedfor the cosine and the Gaussian distributions of the angle ofarrival. The Von Mises distribution produces spatial correlationexpressions in terms of Bessel and trigonometric functions. Anexact expression for the spatial correlation, taking into accountthe mutual coupling, for the circular and linear arrays and anarbitrary number of elements are presented. It can be verified,by numerical evaluation of the expressions, that the couplingbetween the elements correlates the electromagnetic field, and aseparation of half wavelength could not be enough to decorrelatethem

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