Sidelobe Level Reduction in Linear Array Pattern Synthesis Using Particle Swarm Optimization (original) (raw)
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Linear antenna array synthesis for wireless communications using particle swarm optimization
In this paper, the synthesis of linear antenna array for wireless communications is described using particle swarm optimization (PSO). PSO is applied to optimize amplitude excitations for performance improvement such as minimum side lobe level and null control with periodic spacing between the elements. Two design examples are considered and results are illustrated. In comparison with the conventional linear array antenna radiation pattern, this approach yields lower side lobe levels and advanced null control.
Array Antenna Pattern Synthesis using Improved Particle Swarm Optimization (IPSO) Algorithm
ECTI Transactions on Electrical Engineering, Electronics, and Communications
Antenna arrays are used in many different systems, including radar, military systems, and wireless communications. The design of the antenna array has a significant impact on how well the communication system performs. The large number of pieces and the large sidelobe levels provide the biggest design hurdles for such arrays. The antenna arrays have recently been heavily thinned using optimization approaches that take advantage of evolutionary algorithms in order to lower power consumption and enhance the radiation pattern by lowering sidelobe levels. A global optimum for this kind of algorithm is not guaranteed, though, because of the stochastic nature of the resolution techniques. This work characterizes the optimal pattern synthesis of a linear array antenna using the Improved Particle Swarm Optimization (IPSO) algorithm. The main aim is to obtain a low Side Lobe Level (SLL) that avoids interference and a narrow beam width for acquiring high directivity to obtain the optimal solu...
Linear Antenna Array Synthesis Using Improved Particle Swarm Optimization
International Conference on Emerging Applications of Information Technology, 2011
In this paper the synthesis of linear array geometry with minimum sidelobe level using a new class of Particle Swarm Optimization technique namely Improved Particle Swarm Optimization (IPSO) is described. The IPSO algorithm is a newly proposed, high-performance evolutionary algorithm capable of solving general N-dimensional, linear and nonlinear optimization problems. Compared to other evolutionary methods such as genetic algorithms and
Optimal design of a linear antenna array using particle swarm optimization
An optimal design of a linear antenna array is presented. The antenna array is optimized using a particle swarm optimization based method in order to produce a radiation pattern that has the minimum possible side lobe level and the maximum possible gain at the desired direction. The method has been applied to collinear wire-dipole arrays and seems to be suitable for improving the radiation patterns in many practical applications.
Minimization of Side Lobe Level for Linear Antenna Arrays Using Improved Particle Swarm Optimization
2017
The present paper describes minimization of side lobe levels of an linear array antenna using strong evolution algorithm is of particle swarm optimization (PSO). For linear, non linear optimizations and to solve general dimensional problems with high performance a newly discovered PSO used. The implementation and mathematical preprocessing of PSO is easy to analyze when compared with other evolutionary algorithms like simulated annealing and genetic algorithm. The synthesis is based on minimization of side lobe levels in required directions with optimum amplitude distributions for properly arranged antenna array using PSO. Two design examples are considered with even and odd number of elements for the synthesis with required goal.
DESIGN OF NON-UNIFORM CIRCULAR ANTENNA ARRAYS USING PARTICLE SWARM OPTIMIZATION
2008
In this paper, the design of non-uniform circular antenna arrays with optimum side lobe level reduction is presented. The particle swarm optimization (PSO) method, which represents a new approach for optimization problems in electromagnetics, is used in the optimization process. The method of particle swarm optimization is used to determine an optimum set of weights and antenna element separations that provide a radiation pattern with maximum side lobe level reduction with the constraint of a fixed major lobe beamwidth. The results show that the design of non-uniform circular antenna arrays using PSO method provides a side lobe level reduction better than that obtained using genetic algorithms.
Procedia Computer Science, 2015
This paper describes the comparison of the performance of Circular array (CA) and Hexagonal Array (HA) of uniformly excited isotropic antennas which can generate directive beam with minimum relative Side Lobe Level (SLL). The Improved Particle Swarm Optimization (IPSO) method, which represents a novel approach for optimization problems in electromagnetic, is used in the optimization process. Two examples has been presented and solved. In first example, the IPSO is used to determine an optimal set of 'ON-OFF' elements in an 12 element thinned array, and in second example, IPSO is used to determine an optimal set of amplitude distributions in an 18 element array that provide a radiation pattern with maximum SLL reduction. This paper is basically concerned with the comparison of the performance of thinned CA and HA in terms of SLL by fixing the other array design variable. Numerical results for synthesizing two different array geometries demonstrated the superiority of Hexagonal Array over the Circular Array for both the examples.
Suppression of Antenna's Radiation Sidelobes Using Particle Swarm Optimisation
The presence of large sidelobe radiation beam levels of an antenna is undesirable as the antenna performance and efficiency will be greatly degraded. Antenna structures especially in array arrangements have the capability to provide interference reduction, improvement of the channel capacity and expanding the range of a signal's coverage. In this paper, Particle Swarm Optimization (PSO) is utilized to optimize the inter-element position of even-element linear antenna arrays (LAA). The objective is to produce as close to desired radiation pattern as possible that exhibits sidelobe level (SLL) suppression. The PSO algorithm can be successfully used to locate the optimum element positions based on symmetric and even-element LAAs of isotropic radiators. The results obtained showed that the PSO algorithm is capable of finding the optimal solution in most cases with superior performance over conventional method.
Linear antenna array synthesis using cat swarm optimization
AEU - International Journal of Electronics and Communications, 2014
In this paper, the synthesis of linear antenna array for wireless communications is described using particle swarm optimization (PSO). PSO is applied to optimize amplitude excitations for performance improvement such as minimum side lobe level and null control with periodic spacing between the elements. Two design examples are considered and results are illustrated. In comparison with the conventional linear array antenna radiation pattern, this approach yields lower side lobe levels and advanced null control.