Thinning and weighting of planar arrays by modified teaching–learning-based optimization algorithm

Abstract

Synthesizing antenna arrays with a minimum number of active elements is a problem of high importance in ultrasonic applications. This paper proposes a modified teaching–learning-based optimization (MTLBO) algorithm for thinning and weighting planar arrays to synthesize the desired antenna array factor. Not only the number of active elements and their corresponding excitation weights are optimized, but the peaks of side lobe level, main-lobe width, and current taper ratio are also minimized as objective functions in the multi-objective formulation. The optimization method for designing thinned planar arrays proposed in this work is easy to be implemented and requires few controlling parameters. The simulation cases demonstrate effectiveness of the proposed method, and it is proved that the MTLBO outperforms simulated annealing method and hybrid genetic algorithm through comparisons.

Keywords:

• teaching–learning-based optimization (TLBO)
• thinned arrays
• peak of side lobe level (PSLL)
• planar arrays
• modified TLBO

Additional information

Funding

Funding. The work was supported by the National Natural Science Foundation of China [grant number 51235005], [grant number 51121002]; the Research Fund for the Doctoral Program of Chinese Higher Education [grant number 20110142130010]; the Chinese Ministry of Public Security State Research Projects (2011ZDYJHJXY012), and the Chinese Ministry of Public Security Application Innovation Projects (2010YYCXHJXY127).