An Improved Taguchi Algorithm Based on Fitting and Prediction for Linear Antenna Array Synthesis

In this paper, a Taguchi method based on fitting and prediction is proposed to accelerate the optimization process in antenna array synthesis. The implementation procedure combines the normal Taguchi method and the curve fitting technique. A possible solution is determined by prediction based on fitting curves. Specifically, the fitting curves are obtained by using the dynamic points calculated and updated as the Taguchi method progress and recorded in the response table necessarily produced in the procedure. Test functions are used for conducting some confirmation experiments, and the results verify the validity of the proposed method. In order to illustrate its good practicability, two linear antenna arrays with a null controlled pattern and a flat top pattern, respectively, are successfully optimized by using both of the normal Taguchi method and the proposed one. Some comparisons and discussions of their results are given in the paper, which proves that the proposed method has a better practicability, not only because it inherits the global optimization characteristics of the normal Taguchi method but also because it accelerates the convergence process.

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A Comparison of Swarm-Based Optimization Algorithms in Linear Antenna Array Synthesis

10.21203/rs.3.rs-233415/v1 ◽

2021 ◽

Author(s):

Ali Durmus ◽

Rifat KURBAN ◽

Ercan KARAKOSE

Keyword(s):

Antenna Array ◽

Radiation Pattern ◽

Antenna Arrays ◽

Heuristic Algorithms ◽

Beam Width ◽

Side Lobe ◽

Side Lobe Level ◽

Linear Antenna ◽

Half Power ◽

Antenna Array Synthesis

Abstract Today, the design of antenna arrays is very important in providing effective and efficient wireless communication. The purpose of antenna array synthesis is to obtain a radiation pattern with low side lobe level (SLL) at a desired half power beam width (HPBW) in far-field. The amplitude and position values of the array elements can be optimized to obtain a radiation pattern with suppressed SLLs. In this paper swarm-based meta-heuristic algorithms such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Mayfly algorithm (MA) and Jellyfish Search (JS) algorithms are compared to realize optimal design of linear antenna arrays. Extensive experiments are conducted on designing 10, 16, 24 and 32-element linear arrays by determining the amplitude and positions. Experiments are repeated 30 times due to the random nature of swarm-based optimizers and statistical results show that performance of the novel algorithms, MA and JS, are better than well-known methods PSO and ABC.

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Position only Antenna Array Synthesis using Normal Distributed Invasive Weed Optimization

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.b6641.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 3277-3280

Keyword(s):

Antenna Array ◽

Antenna Arrays ◽

Stochastic Approach ◽

Side Lobe ◽

Linear Antenna ◽

Invasive Weed Optimization ◽

Convergence Properties ◽

Invasive Weed ◽

Linear Antenna Array ◽

Antenna Array Synthesis

Nowadays, low-side lobe antenna arrays are used in many communications systems such as satellite, cellular, radar and wireless communications. The antenna array with low side lobe rates should be designed to avoid noisy contact. A new stochastic approach to synthesize a linear antenna array to suppress normal distributed invasive weed optimization (NDIWO) is proposed in this paper synthesize a linear antenna array to suppress the side lobe levels. NDIWO is applied for optimization of the positions of the antenna elements. A 28-element linear array is designed and synthesized by using the proposed and other popular evolutionary algorithms. The acquired radiation designs are gathered with the calculations like particle swarm optimization (PSO) and differential evolution (DE). The numerical results illustrate that the NDIWO optimized antenna array performs superior over PSO and DE optimized arrays in terms of low PSLL and convergence properties.

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Pattern Synthesis of Linear Antenna Array Using Improved Differential Evolution Algorithm with SPS Framework

Sensors ◽

10.3390/s20185158 ◽

2020 ◽

Vol 20 (18) ◽

pp. 5158

Author(s):

Ruimeng Zhang ◽

Yan Zhang ◽

Jinping Sun ◽

Qing Li

Keyword(s):

Differential Evolution ◽

Antenna Array ◽

Antenna Arrays ◽

Optimization Problem ◽

Differential Evolution Algorithm ◽

Linear Antenna ◽

Pattern Synthesis ◽

De Algorithm ◽

Improved Differential Evolution Algorithm ◽

Linear Antenna Arrays

In this paper, an improved differential evolution (DE) algorithm with the successful-parent-selecting (SPS) framework, named SPS-JADE, is applied to the pattern synthesis of linear antenna arrays. Here, the pattern synthesis of the linear antenna arrays is viewed as an optimization problem with excitation amplitudes being the optimization variables and attaining sidelobe suppression and null depth being the optimization objectives. For this optimization problem, an improved DE algorithm named JADE is introduced, and the SPS framework is used to solve the stagnation problem of the DE algorithm, which further improves the DE algorithm’s performance. Finally, the combined SPS-JADE algorithm is verified in simulation experiments of the pattern synthesis of an antenna array, and the results are compared with those obtained by other state-of-the-art random optimization algorithms. The results demonstrate that the proposed SPS-JADE algorithm is superior to other algorithms in the pattern synthesis performance with a lower sidelobe level and a more satisfactory null depth under the constraint of beamwidth requirement.

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Optimized hyper beamforming of receiving linear antenna arrays using Firefly algorithm

International Journal of Microwave and Wireless Technologies ◽

10.1017/s175907871300086x ◽

2013 ◽

Vol 6 (2) ◽

pp. 181-194 ◽

Cited By ~ 18

Author(s):

Gopi Ram ◽

Durbadal Mandal ◽

Rajib Kar ◽

Sakti Prasad Ghoshal

Keyword(s):

Antenna Array ◽

Antenna Arrays ◽

Firefly Algorithm ◽

Beam Width ◽

Linear Antenna ◽

Linear Antenna Array ◽

Heuristic Search Method ◽

Real Coded Genetic Algorithm ◽

Beam Patterns ◽

Linear Antenna Arrays

In this paper, an optimized hyper beamforming method is presented based on a hyper beam exponent parameter for receiving linear antenna arrays using a new meta-heuristic search method based on the Firefly algorithm (FFA). A hyper beam is derived from the sum and difference beam patterns of the array, each raised to the power of a hyper beam exponent parameter. As compared to the conventional hyper beamforming of the linear antenna array, FFA applied to the hyper beam of the same array can achieve much more reduction in sidelobe level (SLL) and improved first null beam width (FNBW), keeping the same value of the hyper beam exponent. As compared to the uniformly excited linear antenna array with inter-element spacing of λ/2, conventional non-optimized hyper beamforming and optimal hyper beamforming of the same obtained by real-coded genetic algorithm, particle swarm optimization and Differential evolution, FFA applied to the hyper beam of the same array can achieve much greater reduction in SLL and same or less FNBW, keeping the same value of the hyper beam exponent parameter. The whole experiment has been performed for 10-, 14-, and 20-element linear antenna arrays.

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Design of Wideband Multifunction Antenna Array Based on Multiple Interleaved Subarrays

International Journal of Antennas and Propagation ◽

10.1155/2016/1320726 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7

Author(s):

Longjun Li ◽

Buhong Wang

Keyword(s):

Fourier Transform ◽

Antenna Array ◽

Antenna Arrays ◽

Linear Antenna ◽

Energy Distributions ◽

Low Sidelobe ◽

Pattern Similarity ◽

The Fourier Transform ◽

The Relationship ◽

Linear Antenna Arrays

A new Modified Iterative Fourier Technique (MIFT) is proposed for the design of interleaved linear antenna arrays which operate at different frequencies with no grating lobes, low-sidelobe levels, and wide bandwidths. In view of the Fourier transform mapping between the element excitations and array factor of uniform linear antenna array, the spectrum of the array factor is first acquired with FFT and its energy distributions are investigated thoroughly. The relationship between the carrier frequency and the element excitation is obtained by the density-weighting theory. In the following steps, the element excitations of interleaved subarrays are carefully selected in an alternate manner, which ensures that similar patterns can be achieved for interleaved subarrays. The Peak Sidelobe Levels (PSLs) of the interleaved subarrays are further reduced by the iterative Fourier transform algorithm. Numerical simulation results show that favorable design of the interleaved linear antenna arrays with different carrier frequencies can be obtained by the proposed method with favorable pattern similarity, low PSL, and wide bandwidths.

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A Novel Modified Sparrow Search Algorithm with Application in Side Lobe Level Reduction of Linear Antenna Array

Wireless Communications and Mobile Computing ◽

10.1155/2021/9915420 ◽

2021 ◽

Vol 2021 ◽

pp. 1-25

Author(s):

Qiankun Liang ◽

Bin Chen ◽

Huaning Wu ◽

Chaoyi Ma ◽

Senyou Li

Keyword(s):

Antenna Array ◽

Antenna Arrays ◽

Search Algorithm ◽

Side Lobe ◽

Side Lobe Level ◽

Linear Antenna ◽

Test Functions ◽

Linear Antenna Array ◽

Benchmark Test Functions ◽

Modified Algorithm

Antenna arrays play an increasingly important role in modern wireless communication systems. However, how to effectively suppress and optimize the side lobe level (SLL) of antenna arrays is critical for communication performance and communication capabilities. To solve the antenna array optimization problem, a new intelligent optimization algorithm called sparrow search algorithm (SSA) and its modification are applied to the electromagnetics and antenna community for the first time in this paper. Firstly, aimed at the shortcomings of SSA, such as being easy to fall into local optimum and limited convergence speed, a novel modified algorithm combining a homogeneous chaotic system, adaptive inertia weight, and improved boundary constraint is proposed. Secondly, three types of benchmark test functions are calculated to verify the effectiveness of the modified algorithm. Then, the element positions and excitation amplitudes of three different design examples of the linear antenna array (LAA) are optimized. The numerical results indicate that, compared with the other six algorithms, the modified algorithm has more advantages in terms of convergence accuracy, convergence speed, and stability, whether it is calculating the benchmark test functions or reducing the maximum SLL of the LAA. Finally, the electromagnetic (EM) simulation results obtained by FEKO also show that it can achieve a satisfactory beam pattern performance in practical arrays.

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Antenna Array Weight Synthesis for Low Side Lobe Levels using Window Functions

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a1664.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 3074-3081

Keyword(s):

Antenna Array ◽

Radiation Pattern ◽

Antenna Arrays ◽

Side Lobe ◽

Optimization Techniques ◽

Side Lobe Level ◽

Linear Antenna ◽

Window Functions ◽

Linear Antenna Arrays ◽

Array Weight

A lot of research is being carried out to reduce side lobe levels (SSLs) in the radiation pattern of antenna arrays. A number of novel optimization techniques have been developed over the years and adapted for this purpose. In this paper, a number of window functions are applied to suppress the maximum side lobe level (MSLL) in linear antenna arrays. The window functions Bartlett, Taylor, Hanning, Barthann, Hamming, Gaussian, Blackman, Chebyshev, Blackman-Harris and Kaiser are considered in the simulation. The optimized pattern for a 10 element linear antenna array and corresponding normalized window tappers for every window are presented. Finally the efficiency of all windows is compared in terms of their computed parameters.

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