A novel methodology for designing thinned arrays with controlled pattern features is presented. The optimization of the binary weighting coefficients of the array elements is carried out through a multi-step procedure. In a first stage, a Genetic Algorithm (GA) is used to determine the binary sequence whose autocorrelation function is closest to a target one. Then, the thinned array is constructed from one of its cyclic sequences which optimizes a given figure of merit. A preliminary numerical example is illustrated in order to show the potentialities of the proposed approach.
Thinned Array Design via Autocorrelation Matching Strategy / Oliveri, Giacomo; Poli, Lorenzo; Massa, Andrea. - STAMPA. - (2018), pp. 2117-2118. (Intervento presentato al convegno 2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting tenutosi a Boston, MA nel 8th-13th July 2018) [10.1109/APUSNCURSINRSM.2018.8608388].
Thinned Array Design via Autocorrelation Matching Strategy
Oliveri, Giacomo;Poli, Lorenzo;Massa, Andrea
2018-01-01
Abstract
A novel methodology for designing thinned arrays with controlled pattern features is presented. The optimization of the binary weighting coefficients of the array elements is carried out through a multi-step procedure. In a first stage, a Genetic Algorithm (GA) is used to determine the binary sequence whose autocorrelation function is closest to a target one. Then, the thinned array is constructed from one of its cyclic sequences which optimizes a given figure of merit. A preliminary numerical example is illustrated in order to show the potentialities of the proposed approach.File | Dimensione | Formato | |
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