Synthesis of Interleaved Large Antenna Arrays With Mutual Exclusion Probability Model

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This paper introduces a novel approach for synthesizing interleaved large antenna arrays by employing a deformed Estimation of Distribution Algorithm (EDA). Initially, a mutually exclusive probability (MEP) model is devised to represent the topological characters of interleaved antenna arrays. Through training the MEP model, collaborative optimization of interleaved sub-arrays is realized. By integrating the iterative Fourier technique (IFT), this method (called mutually exclusive probability model based IFT, MEPIFT) efficiently addresses the challenge of large antenna arrays. In the synthesized interleaved antenna arrays, each sub-array functions as a sparse array with larger element spacing, resulting in narrower beams compared to conventional uniform arrays and thereby mitigating mutual coupling interference to some extant. After optimization, the sub-arrays could scan widely without grating lobes. Furthermore, the proposed algorithm ensures balanced performance between the sub-arrays without sacrificing one for the other. The proposed algorithm has been verified through some examples involving both linear and planar arrays.

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