An optimal circular antenna array design considering mutual coupling using heuristic approaches

Das, Avishek; Mandal, Durbadal; Kar, Rajib

doi:10.1002/mmce.22391

Cited by 14 publications

(8 citation statements)

References 32 publications

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“…For the last decades, meta-heuristic optimization algorithms have shown great potential as an efficient tool for solving challenging multiobjective antenna designs. [25][26][27][28] For determination of optimal variables of CERA elements, a meta-heuristic optimization algorithm honey bee mating optimization (HBMO) 17,29 is used. The cost function Cost mn for the (mn)th element of the 21 units given in Equation ( 2) is used to drive a meta-heuristic optimization algorithm to determine the φ mn =[R 1 , R 2 , g] to be equal to φ Reqmn for the operation band of f min = 10 GHz and f max = 12 GHz with step size of 1 GHz:…”

Section: Cera Designmentioning

confidence: 99%

See 1 more Smart Citation

3D EM data‐driven artificial network‐based design optimization of circular reflectarray antenna with semi‐elliptic rings for X‐band applications

Çalışkan

Güneş

2021

Micro & Optical Tech Letters

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In this work, the design and realization of a circular reflectarray antenna (CERA) with semi‐ elliptic rings are carried out for X‐band. In order to achieve a fast design optimization process, 3D EM simulated data‐driven multilayer perceptron neural network (MLP NN) model of the unit element is generated providing the unit reflection phase as a continuous function of the radii and gap of the ring for the width w = 0.5 mm on the FR4 with ∊r = 4.4, h = 1.5 mm. The proposed CERA consists of 148 unit cells taken symmetrical both in the Y and X‐axis. Thus, a meta‐heuristic optimization algorithm honey bee mating optimization (HBMO) is applied to 21 elements between 10 and 12 GHz to determine their optimal geometries for the required reflection angles according to the phasing scheme. The simulated and measured performances of the designed CERA have been found in good agreement and its performance is compared also with its counterpart designs in literature and resulted to exhibit superior performance.

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Section: Cera Designmentioning

confidence: 99%

“…For the last decades, meta‐heuristic optimization algorithms have shown great potential as an efficient tool for solving challenging multiobjective antenna designs 25–28 . For determination of optimal variables of CERA elements, a meta‐heuristic optimization algorithm honey bee mating optimization (HBMO) 17,29 is used.…”

Section: Cera Designmentioning

confidence: 99%

3D EM data‐driven artificial network‐based design optimization of circular reflectarray antenna with semi‐elliptic rings for X‐band applications

Çalışkan

Güneş

2021

Micro & Optical Tech Letters

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“…Our goal is now to achieve an array pattern with low SLL and minimum circumference. As illustrated in Figure 8, the obtained array patterns using dynamic IWO, COA [8], GA [21], GWO [24] are compared with the corresponding uniform circular array pattern. These results clearly show the accuracy and performances of the proposed algorithm compared to other algorithms of the literature.…”

Section: N Of Elements Sll (Db) Hpbw (mentioning

confidence: 99%

Nonuniform Circular Array Synthesis for Low Side Lobe Level Using Dynamic Invasive Weeds Optimization

Kenane¹,

Benmeddour²,

Djahli³

2021

PIER C

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The use of invasive weeds optimization in the synthesis of antenna arrays has become popular in the last few years. This optimization method is robust, simple and can be easily improved. Like other stochastic algorithms, IWO suffers from premature convergence and other drawbacks. To overcome these problems, a dynamic IWO is proposed and used for synthesizing two antenna array topologies (linear and circular array). This proposed method tries to achieve an optimal array pattern by acting on the amplitude excitation of elements in the nonuniform circular array and their positions on the array, to obtain an array pattern with deep nulls in some directions of interferences and low side lobe level. For the linear array, the nulls control can be achieved by acting on the relative amplitude excitation of each element in the array for an optimal inter-element spacing. This proposed method improves the performance greatly and allows to achieve a maximum reduction in side lobe level in band Nulls with an acceptable dynamic range ratio (DRR). To show the performance of the proposed method, for each topology, our results are compared to other results of the literature.

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“…Another factor that affects the efficiency of antenna arrays is the mutual coupling between the array elements. It abases the performance of the designed antenna array [8]. However, attempts are been made by researchers to reduce the effect of mutual coupling among the array elements by altering the element position and aperture length [9] [10].…”

Section: Introductionmentioning

confidence: 99%

Pattern Synthesis of Uniform and Sparse Linear Antenna Array Using Mayfly Algorithm

et al. 2021

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Pattern synthesis is a significant research focus in smart antennas due to its extensive use in several radar and communication systems. To improve the optimization performance of pattern synthesis of uniform and sparse linear antenna array, this paper presents an optimization method for solving the antenna array synthesis problem using the Mayfly Algorithm (MA). MA is a new heuristic algorithm inspired by the flight behavior as well as the mating process of mayflies, it has a unique velocity update system with great convergence. In this work, the MA was applied to linear antenna arrays (LAA) for optimal pattern synthesis in the following ways: by optimizing the antenna current amplitudes while maintaining uniform spacing and by optimizing the antenna positions while assuming a uniform excitation. Constraints of inter-element spacing and aperture length are imposed in the synthesis of sparse LAA. Sidelobe level (SLL) suppression with the placement of nulls in the specified directions is also implemented. The results gotten from this novel algorithm are validated by benchmarking with results obtained using other intelligent algorithms. In the synthesis of uniform 20-element LAA with nulls, MA achieved an SLL of -31.27 dB and the deepest null of -101.60 dB. Also, for sparse 20-element LAA, an SLL of -18.85 dB was attained alongside the deepest null of -87.37 dB. MA obtained an SLL of -35.73 dB and -23.68 dB for the synthesis of uniform and sparse 32-element LAA respectively. Finally, electromagnetism simulations are conducted using ANSYS Electromagnetics (HFSS) software, to evaluate the performance of MA for the beam pattern optimizations, taking into consideration the mutual coupling effects. The results prove that optimization of LAA using MA provides considerable enhancements in peak SLL suppression, null control, and convergence rate with respect to the uniform array and the synthesis obtained from other existing optimization techniques.

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An optimal circular antenna array design considering mutual coupling using heuristic approaches

Cited by 14 publications

References 32 publications

3D EM data‐driven artificial network‐based design optimization of circular reflectarray antenna with semi‐elliptic rings for X‐band applications

3D EM data‐driven artificial network‐based design optimization of circular reflectarray antenna with semi‐elliptic rings for X‐band applications

Nonuniform Circular Array Synthesis for Low Side Lobe Level Using Dynamic Invasive Weeds Optimization

Pattern Synthesis of Uniform and Sparse Linear Antenna Array Using Mayfly Algorithm

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