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EN
Low peak sidelobe level (PSLL) and antenna arrays with high directivity are needed nowadays for reliable wireless communication systems. Controlling the PSLL is a major is sue in designing effective antenna array systems. In this paper, a nature inspired technique, namely accelerating Gaussian mutated cat swarm optimization (AGMCSO) that attributes global search abilities, is proposed to control PSLL in the radiation pattern. In AGM-SCO, Gaussian mutation with an acceleration parameter is used in the position-updated equa tion, which allows the algorithm to search in a systematic way to prevent premature convergence and to enhance the speed of convergence. Experiments concerning several benchmark multimodal problems have been conducted and the obtained results illustrate that AGMCSO shows excellent performance concerning evolutionary speed and accuracy. To validate the overall efficacy of the algorithm, a sensitivity analysis was per formed for different AGMCSO parameters. AGMCSO was researched on numerous linear, unequally spaced antenna ar rays and the results show that in terms of generating low PSLL with a narrow first null beamwidth (FNBW), AGMCSO out performs conventional algorithms.
EN
A simulation-based optimization approach to design of phase excitation tapers for linear phased antenna arrays is presented. The design optimization process is accelerated by means of Surrogate-Based Optimization (SBO); it uses a coarse-mesh surrogate of the array element for adjusting the array’s active reflection coefficient responses and a fast surrogate of the antenna array radiation pattern. The primary optimization objective is to minimize side-lobes in the principal plane of the radiation pattern while scanning the main beam. The optimization outcome is a set of element phase excitation tapers versus the scan angle. The design objectives are evaluated at the high fidelity level of description using simulations of the discrete electromagnetic model of the entire array so that the effects of element coupling and other possible interaction within the array structure are accounted for. At the same time, the optimization process is fast due to SBO. Performance and numerical cost of the approach are demonstrated by optimizing a 16-element linear array of microstrip antennas. Experimental verification has been carried out for a manufactured prototype of the optimized array. It demonstrates good agreement between the radiation patterns obtained from simulations and from physical measurements (the latter constructed through superposition of the measured element patterns).
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