An effective compensating approach to the synthesis of sparse array with element-failures

The Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) Algorithm is used to compensate the failure of sparse array element. A fitness function is introduced to restrict the error between pre-failed pattern and measured pattern. To minimize the function we have introduced CMA-ES algorithm. S...

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Bibliographic Details
Published in:2019 International Applied Computational Electromagnetics Society Symposium - China (ACES) Vol. 1; pp. 1 - 2
Main Authors: Qin, Anqi, Sheng, Yijun
Format: Conference Proceeding
Language:English
Published: Applied Computational Electromagnetics Society 01.08.2019
Subjects:
Adaptive arrays
array failure compensation algorithm
Arrays
CMA-ES
Covariance matrices
failure of sparse array element
Gaussian distribution
Sociology
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Summary:The Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES) Algorithm is used to compensate the failure of sparse array element. A fitness function is introduced to restrict the error between pre-failed pattern and measured pattern. To minimize the function we have introduced CMA-ES algorithm. Several numerical results demonstrate the ability of this array failure compensation algorithm.
DOI:10.23919/ACES48530.2019.9060496