Title

A Neural Network-Based Smart Antenna For Multiple Source Tracking

Keywords

Direction-of-arrival estimation; Multibeam antennas; Neural networks

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 (DOA) 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. © 2000 IEEE.

Publication Date

12-1-2000

Publication Title

IEEE Transactions on Antennas and Propagation

Volume

48

Issue

5

Number of Pages

768-776

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/8.855496

Socpus ID

0034186876 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0034186876

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