TY - GEN
T1 - Optimizing beam pattern of linear adaptive phase array antenna based on Particle Swarm Optimization
AU - Hsu, Chao Hsing
AU - Chen, Chun Hua
AU - Shyr, Wen Jye
AU - Kuo, Kun Huang
AU - Chung, Yi Nung
AU - Lin, Tsung Chih
PY - 2010/12/1
Y1 - 2010/12/1
N2 - In this paper, an innovative optimal radiation pattern of an adaptive linear array is derived by phase-only perturbations using a Particle Swarm Optimization (PSO) algorithm. An antenna array is often made as an adaptive antenna. An optimal radiation pattern design for an adaptive antenna system is not only to suppress interference by placing a null in the direction of the interfering source but also to derive the maximum power pattern in the direction of the desired signal. The Signal Interference Ratio (SIR) can be maximized. The PSO algorithm is a new methodology in this study area, which can handle adaptive radiation pattern of antenna array. In this paper, an optimal radiation pattern of linear array is derived by phase-only perturbations using a PSO algorithm. PSO algorithms will be stated and computed for this problem. Then, the optimal solution can be derived, and simulation results are also presented in this paper.
AB - In this paper, an innovative optimal radiation pattern of an adaptive linear array is derived by phase-only perturbations using a Particle Swarm Optimization (PSO) algorithm. An antenna array is often made as an adaptive antenna. An optimal radiation pattern design for an adaptive antenna system is not only to suppress interference by placing a null in the direction of the interfering source but also to derive the maximum power pattern in the direction of the desired signal. The Signal Interference Ratio (SIR) can be maximized. The PSO algorithm is a new methodology in this study area, which can handle adaptive radiation pattern of antenna array. In this paper, an optimal radiation pattern of linear array is derived by phase-only perturbations using a PSO algorithm. PSO algorithms will be stated and computed for this problem. Then, the optimal solution can be derived, and simulation results are also presented in this paper.
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U2 - 10.1109/ICGEC.2010.150
DO - 10.1109/ICGEC.2010.150
M3 - Conference contribution
AN - SCOPUS:79952540039
SN - 9780769542812
T3 - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
SP - 586
EP - 589
BT - Proceedings - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
T2 - 4th International Conference on Genetic and Evolutionary Computing, ICGEC 2010
Y2 - 13 December 2010 through 15 December 2010
ER -