Suppression of Antenna's Radiation Sidelobes Using Particle Swarm Optimisation (original) (raw)
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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.
Sidelobe level suppression is a typical circular array (CA) optimization problem. Many conventional techniques are proposed in the due course of time which are computationally complexed and time consuming. As an alternative, several evolutionary and heuristics approaches have evolved for solving such problems. In this paper, a novel accelerated particle swarm optimization (APSO) is considered for solving circular array optimization problem. The APSO is implemented for CA synthesis with the objective of SLL suppression. The objective is achieved under scanned and unscanned beam conditions. A very low SLL of -25dB is observed when the main beam positioned at 00,150 and 300 . In all the cases the efficiency of the APSO is evaluated by the comparing the generated radiation patterns with those obtained from uniform CA.
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.
Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 2017
This paper presents the optimization performance of non-uniform linear antenna array with optimized inter-element spacing and excitation amplitude using Particle Swarm Optimization (PSO). The aim of the proposed algorithm is to obtain the optimum values for inter-element spacing and excitation amplitude for a linear antenna array in a given radiation pattern with suppressed Side Lobe Level (SLL), minimum Half Power Beamwidth (HPBW), improved directivity and placement of nulls in the desired direction. A variety of design examples are considered and the obtained results using PSO are validated by benchmarking with results obtained using other nature-inspired meta-heuristic algorithms such as the Real-coded Genetic Algorithm (RGA) and the Biogeographic Based Optimization (BBO) algorithm. The comparative results are shown that optimization of linear antenna array using the PSO provides considerable enhancement in the SLL, the HPBW, the directivity and the null control in the desired direction.
Sidelobe Level Reduction in Linear Array Pattern Synthesis Using Particle Swarm Optimization
Journal of Optimization Theory and Applications, 2011
The design of nonuniformly spaced linear array antennas using Particle Swarm Optimization method is considered. The purpose is to match a desired radiation pattern and improve the performance of these arrays in terms of sidelobe level. This performance criterion determines how well the system is suitable for wireless communication applications and interference reduction. Two approaches are considered: in the first, the design of element placement with the constraint of array length being imposed is performed. The second is based on element position perturbation starting from a uniform element distribution. Many examples are treated to show the effectiveness of the designs and the effect some other parameters might have on the overall performance of the array.
Particle Swarm Optimization of Antenna Arrays with Efficiency Constraints
Progress In …, 2011
Phased array antennas are a viable solution to a number of problems related to radio communications applications. In this work, the multi-objective stochastic MOPSO algorithm is used to optimize the spatial configuration of a symmetric phased linear array. The defined optimization goals were the suppression of the radiation pattern sidelobes at a specified maximum scan angle as well as the minimization of the induced voltages correlation at the receiver frontend in order to maximize diversity performance. Non-linear constraints were enforced on the solution set, related to the multi-antenna system aperture efficiency and related to the mismatching when the array is scanned. The obtained optimized configurations for an array composed of 16 dipoles resulted in reducing the sidelobes up to 2.5 dB, when scanned 60 • away from broadside, compared to a linear array with elements spaced λ/2 apart. Furthermore, the optimized dipole arrays were characterized by a maximum element correlation of 0.12 to 0.43. The performance of obtained configurations was shown to be tolerant to feed phase variations that appear in realistic implementations. The arrays were analyzed employing the Method of Moments (MoM).
Microwave and Optical Technology Letters, 2007
A particle swarm optimization based technique is applied on linear antenna arrays used by broadcasting base stations. Both the geometry and the excitation of the antenna array are optimized by a suitable algorithm under the constraints of the maximum possible gain at the desired direction and the desired value of side lobe level. The matching condition of the elements of the antenna array is also required by the algorithm. The technique has been applied to antenna arrays composed of collinear wire dipoles and seems to be very promising for improving radiation patterns of base station antenna arrays in many practical applications. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 1690–1698, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22505
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...
Optimization of circular antenna arrays using particle swarm optimization
2016
This article presents a study of circular antenna array design and optimization using the cuckoo search (CS) algorithm. The goal of optimization is to minimize the maximum sidelobe level with and without null steering. The CS algorithm is used to determine the parameters of the array elements that produce the desired radiation pattern. We illustrated the effectiveness of the CS in the design and optimization of circular antenna arrays by means of extensive numerical simulations. We compared our results with other methods from the literature whenever possible. We presented numerous examples that show the excellent performance and robustness of the CS algorithm and the results reveal that the design of circular antenna arrays using the CS algorithm provides acceptable enhancement compared with the uniform array or the design obtained using other optimization methods.