Correction of array failure using grey wolf optimizer hybridized with an interior point algorithm
We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelobe level (SLL) and null depth level (NDL), and nulls are damaged and shifted from th...
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| Main Authors: | , , |
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| Format: | Article |
| Published: |
Zhejiang University and Springer-Verlag GmbH Germany
2018
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/86589/ http://dx.doi.org/10.1631/FITEE.1601694 |
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| Summary: | We design a grey wolf optimizer hybridized with an interior point algorithm to correct a faulty antenna array. If a single sensor fails, the radiation power pattern of the entire array is disturbed in terms of sidelobe level (SLL) and null depth level (NDL), and nulls are damaged and shifted from their original locations. All these issues can be solved by designing a new fitness function to reduce the error between the preferred and expected radiation power patterns and the null limitations. The hybrid algorithm has been designed to control the array’s faulty radiation power pattern. Antenna arrays composed of 21 sensors are used in an example simulation scenario. The MATLAB simulation results confirm the good performance of the proposed method, compared with the existing methods in terms of SLL and NDL. |
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