论文信息 - A Quantized Invasive Weed Optimization Based Antenna Array Synthesis with Digital Phase Control

A Quantized Invasive Weed Optimization Based Antenna Array Synthesis with Digital Phase Control

The design of antenna arrays aims at minimizing side-lobe levels far as practicable. So a major concern of designer is to optimize the side lobes to increase directivity, gain, and efficiency. Invasive Weed Optimization (IWO) is a recently developed, ecologically inspired metaheuristic algorithm that has already found some major applications in electromagnetic research. In this article the synthesis of array antenna pattern by digital phase shifters is accomplished with a modified version of the IWO algorithm called QIWO (Quantized Invasive Weed Optimization. The proposed algorithm searches for optimal solution of the fitness function, which contains the SLL value and the interference suppression keeping the main beam unchanged. The results obtained from this algorithm are better than that of QPSO (Quantized Particle Swarm Optimization) and BPSO (Binary Particle Swarm Optimization). In this paper the array factor is expressed mathematically by a linear transform, which is similar to Discrete Cosine Transform (DCT). This proposed algorithm is also found to be efficient in computing for large arrays.

[1] Giacomo Oliveri,et al. Synthesis of monopulse sub-arrayed linear and planar array antennas with optimized sidelobes , 2009 .

[2] Randy L. Haupt,et al. Phase-only adaptive nulling with a genetic algorithm , 1997 .

[3] Caro Lucas,et al. A novel numerical optimization algorithm inspired from weed colonization , 2006, Ecol. Informatics.

[4] Taisir H Ismail,et al. Array Pattern Synthesis Using Digital Phase Control by Quantized Particle Swarm Optimization , 2010, IEEE Transactions on Antennas and Propagation.

[5] H. Steyskal,et al. Methods for null control and their effects on the radiation pattern , 1986 .

[6] Y. Rahmat-Samii,et al. Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Binary, Single-Objective and Multiobjective Implementations , 2007, IEEE Transactions on Antennas and Propagation.

[7] G. Rassweiler,et al. Adaptive sidelobe nulling using digitally controlled phase-shifters , 1976 .

[8] Russell C. Eberhart,et al. A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.