Linear array beampattern gain optimization techniques

The work describes here uses optimization techniques to increase the gain of a uniform linear array's beampattern when some of its elements fails. The optimization criteria evaluates the weights of the remaining elements so as to restore the gain as closely as possible to the reference beampatt...

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Main Author: Nagi F.
Other Authors: 56272534200
Format: Conference paper
Published: IEEE Computer Society 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-299102023-12-28T16:58:11Z Linear array beampattern gain optimization techniques Nagi F. 56272534200 Image processing Linear programming Array elements Gain optimization Goal programming LMS algorithms Optimization criteria Optimization techniques Reference patterns Uniform linear arrays Multiobjective optimization The work describes here uses optimization techniques to increase the gain of a uniform linear array's beampattern when some of its elements fails. The optimization criteria evaluates the weights of the remaining elements so as to restore the gain as closely as possible to the reference beampattern. LMS and goal programming methods are used to evaluate the weights of the remaining array elements. In the LMS algorithm the error between the reference and the iterated beampattern is reduced. In the goal attaining algorithm the goal of optimization is set to the reference pattern. The comparison between the two techniques reveals that in general the goal programming algorithm perform better in terms of the SNR of the beampattern beamwidths. � 2001 IEEE. Final 2023-12-28T08:58:11Z 2023-12-28T08:58:11Z 2001 Conference paper 10.1109/ISSPA.2001.949793 2-s2.0-84904336868 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904336868&doi=10.1109%2fISSPA.2001.949793&partnerID=40&md5=e0091f2efac8db2c04dd54d215fcccf1 https://irepository.uniten.edu.my/handle/123456789/29910 1 949793 132 135 IEEE Computer Society Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Image processing
Linear programming
Array elements
Gain optimization
Goal programming
LMS algorithms
Optimization criteria
Optimization techniques
Reference patterns
Uniform linear arrays
Multiobjective optimization
spellingShingle Image processing
Linear programming
Array elements
Gain optimization
Goal programming
LMS algorithms
Optimization criteria
Optimization techniques
Reference patterns
Uniform linear arrays
Multiobjective optimization
Nagi F.
Linear array beampattern gain optimization techniques
description The work describes here uses optimization techniques to increase the gain of a uniform linear array's beampattern when some of its elements fails. The optimization criteria evaluates the weights of the remaining elements so as to restore the gain as closely as possible to the reference beampattern. LMS and goal programming methods are used to evaluate the weights of the remaining array elements. In the LMS algorithm the error between the reference and the iterated beampattern is reduced. In the goal attaining algorithm the goal of optimization is set to the reference pattern. The comparison between the two techniques reveals that in general the goal programming algorithm perform better in terms of the SNR of the beampattern beamwidths. � 2001 IEEE.
author2 56272534200
author_facet 56272534200
Nagi F.
format Conference paper
author Nagi F.
author_sort Nagi F.
title Linear array beampattern gain optimization techniques
title_short Linear array beampattern gain optimization techniques
title_full Linear array beampattern gain optimization techniques
title_fullStr Linear array beampattern gain optimization techniques
title_full_unstemmed Linear array beampattern gain optimization techniques
title_sort linear array beampattern gain optimization techniques
publisher IEEE Computer Society
publishDate 2023
_version_ 1806424182255255552