Statistically thinned array antennas are usually employed to form single-beam radiation patterns. In this work, the possibility to adopt such type of antennas to obtain multiple-beam patterns is successfully explored. In particular, two schemes are proposed and compared. In the first one, multiple-beam patterns are realized by considering each beam corresponding to a different feeding network. In the second scheme, multiple-beam behavior is achieved by a single feeding network. A key question addressed in this manuscript is given by the analysis of the statistical deviation of the synthesized radiation pattern, as compared to the reference one. To this end, the up-crossing method is employed. In particular, the assumption of symmetric thinned arrays leads to analytical results, but avoids the adoption of the simplified hypothesis which usually give inaccuracy. The proposed approach is verified by a Monte Carlo analysis, and shows very good agreement between empirical data and theoretical predictions.
Statistically Thinned Array Antennas for Simultaneous Multibeam Applications
Solimene R.
2022
Abstract
Statistically thinned array antennas are usually employed to form single-beam radiation patterns. In this work, the possibility to adopt such type of antennas to obtain multiple-beam patterns is successfully explored. In particular, two schemes are proposed and compared. In the first one, multiple-beam patterns are realized by considering each beam corresponding to a different feeding network. In the second scheme, multiple-beam behavior is achieved by a single feeding network. A key question addressed in this manuscript is given by the analysis of the statistical deviation of the synthesized radiation pattern, as compared to the reference one. To this end, the up-crossing method is employed. In particular, the assumption of symmetric thinned arrays leads to analytical results, but avoids the adoption of the simplified hypothesis which usually give inaccuracy. The proposed approach is verified by a Monte Carlo analysis, and shows very good agreement between empirical data and theoretical predictions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.