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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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 |
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Image processing Linear programming Array elements Gain optimization Goal programming LMS algorithms Optimization criteria Optimization techniques Reference patterns Uniform linear arrays Multiobjective optimization |
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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 |
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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. |
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56272534200 |
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56272534200 Nagi F. |
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Conference paper |
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Nagi F. |
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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 |
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Linear array beampattern gain optimization techniques |
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Linear array beampattern gain optimization techniques |
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linear array beampattern gain optimization techniques |
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IEEE Computer Society |
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2023 |
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1806424182255255552 |