Title

Performance Of Radial-Basis Function Networks For Direction Of Arrival Estimation With Antenna Arrays

Authors

Authors

A. H. ElZooghby; C. G. Christodoulou;M. Georgiopoulos

Comments

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Abbreviated Journal Title

IEEE Trans. Antennas Propag.

Keywords

antenna arrays; direction of arrival estimation; Engineering, Electrical & Electronic; Telecommunications

Abstract

The problem of direction of arrival (DOA) estimation of mobile users using linear antenna arrays is addressed, To reduce the computational complexity of superresolution algorithms, e.g. multiple signal classification (MUSIC), the DOA problem is approached as a mapping which can be modeled using a suitable artificial neural network trained with input output pairs, This paper discusses the application of a three-layer radial-basis function neural network (RBFNN), which can learn multiple source-direction findings of a six-element array, The network weights are modified using the normalized cumulative delta rule, The performance of this network is compared to that of the MUSIC algorithm for both uncorrelated and correlated signals, It Is also shown that the RBFNN substantially reduced the CPU time for the DOA estimation computations.

Journal Title

Ieee Transactions on Antennas and Propagation

Volume

45

Issue/Number

11

Publication Date

1-1-1997

Document Type

Article

Language

English

First Page

1611

Last Page

1617

WOS Identifier

WOS:A1997YE07900006

ISSN

0018-926X

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