Evolutionary algorithms for optimal synthesis of thinned multiple concentric circular array antenna with constraints

ABSTRACT

The novel implementation of three evolutionary optimisation algorithms, namely quantum particle swarm optimisation (QPSO), teaching-learning based optimisation (TLBO) and symbiotic organism search (SOS) for thinning of multiple concentric circular array antenna with isotropic array elements for the simultaneous optimisation of the sidelobe levels (SLLs) as well as peak directivity is presented in this work. The performance studies as cases 1 and 2 are made with two control parameters: interring radii and number of switched ‘on–off’ elements in each ring. The comparative study of the three algorithms has been carried out using common parameters. Finally, experimental results show that case 2 outperforms case 1 with regard to SLL and directivity. Apart from this, the results of SOS have been shown to be better than the other two state of art meta-heuristic optimisation after comparing their effectiveness based on SLL, peak directivity, mean value, and standard deviation along with best cost. For statistical validation of both cases, t-test has been done for testing the stability of SOS over QPSO and TLBO.

KEYWORDS:

• Concentric circular array antenna
• quantum particle swarm optimisation (QPSO)
• symbiotic organism search (SOS)
• teaching-learning based optimisation (TLBO)
• thinning

Acknowledgments

This publication is an outcome of the R&D work undertaken under the Visveswaraya PhD Scheme of Ministry of Electronics and Information Technology, Government of India, being implemented by Digital India Corporation.

Disclosure Statement

No potential conflict of interest was reported by the authors.