Title
Experimental validation of a neural network direction finder
Abstract
This paper discusses an experimental neural network based smart antenna capable of performing direction finding. A cylindrical eight-element phased array antenna is used to collect complex signals radiated by two sources. Three direction of arrival (DOA) estimation algorithms are applied to the measured data, namely, the Fourier transform, the MUSIC algorithm and the radial basis function neural network (RBFNN) algorithm. Comparisons show the superior performance of the RBFNN and its ability to overcome many limitations of the conventional and other superresolution techniques, specifically by reducing the computational complexity and the ability to deal with highly correlated sources.
Publication Date
1-1-1999
Publication Title
IEEE Antennas and Propagation Society International Symposium: Wireless Technologies and Information Networks, APS 1999 - Held in conjunction with USNC/URSI National Radio Science Meeting
Volume
3
Number of Pages
1592-1595
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/APS.1999.788249
Copyright Status
Unknown
Socpus ID
85006438704 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85006438704
STARS Citation
El Zooghby, A. H.; Southall, H. L.; and Christodoulou, C. G., "Experimental validation of a neural network direction finder" (1999). Scopus Export 1990s. 3783.
https://stars.library.ucf.edu/scopus1990/3783