Statistical monitoring of linear antenna arrays

Harrou, Fouzi; Sun, Ying

doi:10.1016/j.jestch.2016.10.010

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…The method effectively detects array defects and is verified using numerical results. Harrou and Sun in [18,19] proposed a generalized likelihood ratio (GLR) test-based statistical fault detection method for potential faults in linear antenna arrays. Khan et al in [20] developed a hybrid method for fault detection in nonuniformly excited linear arrays, improving slow convergence of differential evolution-(DE-) based compressed sensing techniques.…”

Section: Patnaik Et Al Employed An Artificial Neural Network (Ann)mentioning

confidence: 99%

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

Mitra,

Chatterjee,

Chatterjee

et al. 2024

International Journal of RF and Microwave Computer-Aided Engine

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In this article, a novel method of fault detection in nonuniformly excited linear antenna array has been reported. This method uses an evolutionary algorithm-based technique to generate approximate radiation pattern in tune with reference faulty pattern for a nonuniformly excited linear antenna array. Based on the approximation, a binary sequence-based method of exact fault detection has been developed. In order to illustrate the effectiveness of the method, 12- and 20-element Dolph Tschebyscheff linear antenna array with amplitude fault has been considered. Superiority of the proposed method has been demonstrated through comparative study.

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Section: Patnaik Et Al Employed An Artificial Neural Network (Ann)mentioning

confidence: 99%