TY - GEN
T1 - Sparse Conformal Array Synthesis Based on Multiagent Genetic Algorithm
AU - Liu, Ganyu
AU - Zhu, Hailiang
AU - Wang, Kai
AU - Mou, Jinchao
AU - Zheng, Pei
AU - Wei, Gao
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, multiagent genetic algorithm (MAGA) is firstly applied to tackle the synthesis of conformal sparse array, a constrained multi-objective optimization problem. Moreover, a model considered low peak sidelobe level (PSLL) is given for conformal sparse array synthesis. For the antenna array deployed on a quadric surface, the PSLL can be reduced by obtaining the optimal antenna element arrangement. An example of 256-element array synthesis with a 56% sparse rate proves MAGA as an effective optimization tool for conformal sparse arrays in low computational cost.
AB - In this paper, multiagent genetic algorithm (MAGA) is firstly applied to tackle the synthesis of conformal sparse array, a constrained multi-objective optimization problem. Moreover, a model considered low peak sidelobe level (PSLL) is given for conformal sparse array synthesis. For the antenna array deployed on a quadric surface, the PSLL can be reduced by obtaining the optimal antenna element arrangement. An example of 256-element array synthesis with a 56% sparse rate proves MAGA as an effective optimization tool for conformal sparse arrays in low computational cost.
UR - https://www.scopus.com/pages/publications/85151998811
U2 - 10.1109/APCAP56600.2022.10069223
DO - 10.1109/APCAP56600.2022.10069223
M3 - 会议稿件
AN - SCOPUS:85151998811
T3 - 2022 IEEE 10th Asia-Pacific Conference on Antennas and Propagation, APCAP 2022 - Proceedings
BT - 2022 IEEE 10th Asia-Pacific Conference on Antennas and Propagation, APCAP 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2022
Y2 - 4 November 2022 through 7 November 2022
ER -