Synthesis of large‐scale thinned arrays based on a multiagent genetic algorithm

• Published in: International journal of RF and microwave computer-aided engineering Vol. 31; no. 2
• Main Authors: Yang, Xu, Yang, Feng, Hong, Yanhong, Ma, Yankai, Yang, Shiwen
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.02.2021
• Subjects: Antenna arrays; Arrays; Computing costs; Cost function; Exploitation; genetic algorithm; Genetic algorithms; multiagent system; Multiagent systems; Optimization; Synthesis; thinned array synthesis
• ISSN: 1096-4290; 1099-047X
• DOI: 10.1002/mmce.22522

Advanced array synthesis problems are usually nonconvex regarding the cost functions, which are rather difficult to solve. A numerical stochastic optimization approach based on the multiagent genetic algorithm (MAGA) is proposed for the synthesis of highly thinned arrays in this article. In particular, two modified techniques are introduced into the traditional MAGA, named as improved MAGA (I‐MAGA), to obtain the balance between exploration and exploitation ability. The proposed approach is utilized in some advanced antenna array synthesis problems, including the synthesis of sum and difference patterns and synthesis of several highly thinned planar arrays with different apertures. Numerical results indicate that the proposed I‐MAGA has an attractive exploration and exploitation ability in the synthesis of highly thinned arrays. Besides, owing to the independent multiagent system, the I‐MAGA is also able to obtain better solutions with a much smaller population size and less computational cost.