Title

A neural network-based smart antenna for multiple source tracking

Authors

Authors

A. H. El Zooghby; C. G. Christodoulou;M. Georgiopoulos

Comments

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Abbreviated Journal Title

IEEE Trans. Antennas Propag.

Keywords

direction-of-arrival estimation; multibeam; antennas; neural networks; PERFORMANCE; ARRAYS; Engineering, Electrical & Electronic; Telecommunications

Abstract

This paper considers the problem of multiple-source tracking with neural network-based smart antennas for wireless terrestrial and satellite mobile communications. The neural multiple-source tracking (N-MUST) algorithm is based on an architecture of a family of radial basis function neural networks (RBFNN) to perform both detection and direction of arrival (DOG) estimation. The field of view of the antenna array is divided into spatial angular sectors, which are in turn assigned to a different pair of RBFNN's. When a network detects one or more sources in the first stage, the corresponding second stage network(s) are activated to perform the DOA estimation. Simulation results are performed to investigate the performance of the algorithm for various angular separations, with sources of random relative signal-to-noise ratio and when the system suffers from a doppler spread.

Journal Title

Ieee Transactions on Antennas and Propagation

Volume

48

Issue/Number

5

Publication Date

1-1-2000

Document Type

Article

Language

English

First Page

768

Last Page

776

WOS Identifier

WOS:000088410300016

ISSN

0018-926X

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