Radiation Pattern Correction of Faulty Planar Phased Array using Genetic Algorithm

The probability of antenna array failure or malfunctioning cannot be ruled out, and hardware replacement of faulty elements is not always a viable solution. Therefore, academic and industrial interest in self-healing phased arrays are on the rise. In this work, the phase-only genetic algorithm (GA)...

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Bibliographic Details
Published inAdvanced electromagnetics Vol. 13; no. 2
Main Authors R. A. B. Saleem, A. A. Shah, H. Munsif, A. I. Najam, S. Khattak, I. Ullah
Format Journal Article
LanguageEnglish
Published Advanced Electromagnetics 01.07.2024
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ISSN2119-0275

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Summary:The probability of antenna array failure or malfunctioning cannot be ruled out, and hardware replacement of faulty elements is not always a viable solution. Therefore, academic and industrial interest in self-healing phased arrays are on the rise. In this work, the phase-only genetic algorithm (GA) optimization flow for the radiation pattern correction of a 4 × 4 phase faulty planar antenna array is proposed. Initially, a reference array pattern at the desired scan angle is generated. Then random phase faults are introduced across the 1 × 4 antenna elements in any one of 4 sub-arrays to produce maximum distortion in the reference radiation pattern of 4 × 4 planar array. The proposed GA re-computes the new excitation weights for the remaining non-faulty 3 sub-arrays to correct the overall radiation pattern of 4 × 4 array. This is achieved by calculating the array output power for reference and GA computed weights. The GA corrected patterns fairly follow the desired array patterns in terms of peak gain and reducing sidelobe levels for the desired scan angle. The efficiency of the optimized radiation patterns was evaluated in full-wave HFSS model and measurements validation. In this way, maintenance cost can be reduced with recovery of acceptable level of radiation pattern using software instead of physically replacing faulty antenna elements in the array.
ISSN:2119-0275