Volume 2 (1), June 2019, Pages 64-74

Pallavi Mitra1, Durbadal Mandal1, Rajib Kar1, Pragnan Chakravorty2

1National Institute of Technology Durgapur-713209, India, This email address is being protected from spambots. You need JavaScript enabled to view it., This email address is being protected from spambots. You need JavaScript enabled to view it.

2Clique for Applied Research in Electronic Technology, India, This email address is being protected from spambots. You need JavaScript enabled to view it.


The advent of complex engineering systems has made computation intensive design processes inevitable. Unfortunately, such processes require larger resources, i.e., larger memory, parallel processing, etc., and time than usual. As a result, the high performance issues like managing these processes to run within limited resource pools has become ever more challenging. This paper reports an application of intelligent computing in the specific area of antenna arrays and implicitly shows how a computationally intensive process can improve its performance within a limited available resource by judiciously combining different algorithms. Failures in radiating elements in an antenna array usually increase the undesired side lobe radiation, thereby distorting the original radiation pattern. Here, restoration of the original pattern has been attempted by restricting the side lobe levels (SLLs) to the desired threshold using a meta-heuristic optimization technique named Improved Particle Swarm Optimization with Wavelet Mutation (IPSOWM). Also, as a reference, the performance of this algorithm has been compared with Improved Particle Swarm Optimization (IPSO) technique. Results show that IPSOWM yields a better solution to the existing problem as compared to IPSO.


Antenna Array, Particle Swarm Optimization, Wavelet Mutation, Side Lobe Level.




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