Application of Electromagnetism-Like Algorithm to Phase-Only Syntheses of Antenna Arrays

Lee, Kun-Chou; Jhang, Jhen-Yan

doi:10.2528/pier08060402

Cited by 20 publications

(13 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The maximum SLL for the uniform array is −13.19 dB while the maximum SLL for the optimized array (obtained using both algorithms) is −16.24 dB. This shows that the maximum side lobe reduction is improved by 3 dB which is slightly better than that in [30] by about 0.1 dB. …”

Section: Optimize Element Phases (ϕ N )mentioning

confidence: 52%

“…Here, for comparison purposes, we consider several examples which are similar to those presented in [30]. Figure 12 shows the optimum array patterns for the phaseoptimized 20 elements LA, compared with uniform array.…”

Section: Optimize Element Phases (ϕ N )mentioning

confidence: 99%

“…The goal of the optimization is to adjust the phases of the array elements to reduce the maximum side lobe level and to impose nulls at specific angles. The fitness function is given as [30]:…”

Section: Optimize Element Phases (ϕ N )mentioning

confidence: 99%

See 2 more Smart Citations

Application of Taguchi's Optimization Method and Self-Adaptive Differential Evolution to the Synthesis of Linear Antenna Arrays

Dib¹,

Goudos²,

Muhsen³

2010

PIER

103

102

View full text Add to dashboard Cite

Abstract-In this paper, the problem of designing linear antenna arrays for specific radiation properties is dealt with. The design problem is modeled as a single optimization problem. The objectives of this work are to minimize the maximum side lobe level (SLL) and perform null steering for isotropic linear antenna arrays by controlling different parameters of the array elements (position, amplitude, and phase). The optimization is performed using two techniques: Taguchi's optimization method and the self-adaptive differential evolution (SADE) technique. The advantage of Taguchi's optimization technique is the ability of solving problems with a high degree of complexity using a small number of experiments in the optimization process Taguchi's method is easy to implement and converges to the desired goal quickly in comparison with gradient-based methods and particle swarm optimization (PSO) Results obtained using Taguchi's method are in very good agreement with those obtained using the SADE technique.

show abstract

Section: Optimize Element Phases (ϕ N )mentioning

confidence: 52%

Section: Optimize Element Phases (ϕ N )mentioning

confidence: 99%

See 1 more Smart Citation

Application of Taguchi's Optimization Method and Self-Adaptive Differential Evolution to the Synthesis of Linear Antenna Arrays

Dib¹,

Goudos²,

Muhsen³

2010

PIER

103

102

View full text Add to dashboard Cite

show abstract

“…Linear array thinning using iterative Fourier techniques is reported in [6]. Phase-only synthesis has been successfully used in [7,8] to get the desired radiation pattern. In [9] the authors presented hybrid near-field and far-field transformation algorithm which combines a Fast Fourier Transform pre-processing with the plane wave based fully probe corrected near-field transformation of low numerical complexity.…”

Section: Introductionmentioning

confidence: 99%

Pattern Synthesis Using Hybrid Fourier-Neural Networks for Ieee 802.11 Mimo Application

Ghayoula¹,

Ghayoula²,

Haj-Taieb³

et al. 2016

PIER B

View full text Add to dashboard Cite

Abstract-In this paper, the application of Artificial Neural Network (ANN) with back-propagation algorithm and weighted Fourier method are used for the synthesis of antenna arrays. The neural networks facilitate the modelling of antenna arrays by estimating the phases. The most important synthesis problem is to find the weights of the linear antenna array elements that are optimum to provide the radiation pattern with maximum reduction in the sidelobe level. This technique is used to prove its effectiveness in improving the performance of the antenna array. To achieve this goal, antenna array for Wi-Fi IEEE 802.11a with frequency at 2.4 GHz to 2.5 GHz is implemented using Hybrid Fourier-Neural Networks method. To verify the validity of the technique, several illustrative examples of uniform excited array patterns with the main beam are placed in the direction of the useful signal. The neural network synthesis method not only allows to establish important analytical equations for the synthesis of antenna array, but also provides a great flexibility between the system parameters in input and output which makes the synthesis possible due to the explicit relation given by them.

show abstract

“…Numerous applications are developed on the basis of this algorithm such as scheduling problems [147][148][149][150], course timetabling [151], PID controller [152], fuzzy system [153][154][155], vehicle routing problem [156], networking [157], inventory control [158], neural network [159,160], TSP [161,162], feature selection [163], antenna application [164], robotics application [165], flow path designing [166], and vehicle routing [167].…”

Section: Electromagnetism-like: Em Emmentioning

confidence: 99%

Physics-Inspired Optimization Algorithms: A Survey

Biswas

Mishra

Tiwari

et al. 2013

Journal of Optimization

109

View full text Add to dashboard Cite

Natural phenomenon can be used to solve complex optimization problems with its excellent facts, functions, and phenomenon. In this paper, a survey on physics-based algorithm is done to show how these inspirations led to the solution of well-known optimization problem. The survey is focused on inspirations that are originated from physics, their formulation into solutions, and their evolution with time. Comparative studies of these noble algorithms along with their variety of applications have been done throughout this paper.

show abstract

Application of Electromagnetism-Like Algorithm to Phase-Only Syntheses of Antenna Arrays

Cited by 20 publications

References 21 publications

Application of Taguchi's Optimization Method and Self-Adaptive Differential Evolution to the Synthesis of Linear Antenna Arrays

Application of Taguchi's Optimization Method and Self-Adaptive Differential Evolution to the Synthesis of Linear Antenna Arrays

Pattern Synthesis Using Hybrid Fourier-Neural Networks for Ieee 802.11 Mimo Application

Physics-Inspired Optimization Algorithms: A Survey

Contact Info

Product

Resources

About