A genetic algorithm for the level control of nulls and side lobes in linear antenna arrays

Goswami, Bipul; Mandal, Durbadal

doi:10.1016/j.jksuci.2012.06.001

Cited by 37 publications

(37 citation statements)

References 12 publications

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“…Considering 12 and 16 antenna array elements, the directivity and the SLL of linear antenna arrays have been improved by increasing the number of elements and controlling the inter-element spacing, the excitation amplitude. Another important application of linear array is null control [1], [5]- [6], [9]. The null control refers to control the radiation pattern in a way such that a relatively small amount of power is received/radiated in certain directions.…”

Section: Optimization Of Excitation Amplitude and Inter-element Spmentioning

confidence: 99%

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Analysis of Linear Antenna Array for minimum Side Lobe Level, Half Power Beamwidth, and Nulls control using PSO

Rahman

Cao

Ahmed

et al. 2017

J. Microw. Optoelectron. Electromagn. Appl.

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Section: Optimization Of Excitation Amplitude and Inter-element Spmentioning

confidence: 99%

“…by using the PSO and the GA [5]- [7]. The composite differential evaluation (CoDE) algorithm applied to optimize inter-element spacing, between two consecutive elements to minimize the SLL and to place nulls in the desired direction [8][9]. A multi-objective optimization approach has been used in Ref.…”

mentioning

confidence: 99%

Analysis of Linear Antenna Array for minimum Side Lobe Level, Half Power Beamwidth, and Nulls control using PSO

Rahman

Cao

Ahmed

et al. 2017

J. Microw. Optoelectron. Electromagn. Appl.

View full text Add to dashboard Cite

“…Hence, designing array antennas with a desired radiation pattern has been extensively studied over the last few decades [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. In these problems, we need to control parameters which depend on the structure of an antenna, and they are required in order to achieve the desired radiation characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…In these problems, we need to control parameters which depend on the structure of an antenna, and they are required in order to achieve the desired radiation characteristics. Among these parameters, we can refer to the number of elements [2][3][4][5], geometry of arrays [6][7][8], determination of the excitation of elements [9][10][11][12] and distance between the elements [13].…”

Section: Introductionmentioning

confidence: 99%

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Introducing Deeper Nulls and Reduction of Side-Lobe Level in Linear and Non-Uniform Planar Antenna Arrays Using Gravitational Search Algorithm

Hesari¹,

Ebrahimzadeh²

2017

PIER B

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Abstract-Array antennas synthesis is one of the most important problems in the optimization of antenna and electromagnetics. In this paper, a recently developed metaheuristic algorithm, known as the Gravitational Search Algorithm (GSA), is employed for the pattern synthesis of linear and nonuniform planar antenna arrays with desired pattern nulls in the interfering directions and minimum side lobe level (SLL) by position-only optimization. Like other nature-inspired algorithms, GSA is also a population-based method and uses a population of solutions to proceed to a global solution. The results of GSA are validated by comparing them with the results obtained using particle swarm optimization (PSO) and some other algorithms reported in literature for linear and planar array. The side-lobe level and null depth obtained from gravitational search algorithm for planar array are improved up to −30 dB and −200 dB, respectively. The results reveal the superior performance of GSA to the other techniques for the design of linear and planar antenna arrays.

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A multi‐objective optimization approach for beam pattern synthesis of UAV virtual rectangular antenna array

Mei,

Guo,

Kang

et al. 2024

Int J Numerical Modelling

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Virtual antenna array (VAA) formed by unmanned aerial vehicle (UAV) antenna units using collaborative beamforming (CB) technology plays an important role in the air communication system, and can be used in radar, military, disaster rescue and other places. However, there are still some issues with the beam pattern formed by this method, such as high sidelobe level (SLL), high cost and low efficiency. In this article, each UAV carries an omnidirectional antenna unit, and a large number of UAVs form a UAV virtual rectangular antenna array (UVRAA) to communicate with the ground base station (BS). We formulate an overhead minimization and efficient communication multi‐objective optimization problem (OMECMOP) which jointly optimize the excitation current weights of the UVRAA and reduce the number of UAVs in operation to improve the beam pattern, enhance the communication efficiency and decrease the overhead of UVRAA. In addition, we also propose an improved multi‐objective multi‐verse optimization algorithm based on the inverse decline curve type (ISDT‐MOMVO) which introduces a strategy optimization initialization solution with quasi‐opposition based learning (QBL) and a hybrid solution updating operators to solve the OMECMOP. The simulation results show that compared with other traditional swarm intelligence (SI) optimization algorithms the ISDT‐MOMVO algorithm produces better beam pattern and the thinning rate can reach 50%.

show abstract

A genetic algorithm for the level control of nulls and side lobes in linear antenna arrays

Cited by 37 publications

References 12 publications

Analysis of Linear Antenna Array for minimum Side Lobe Level, Half Power Beamwidth, and Nulls control using PSO

Analysis of Linear Antenna Array for minimum Side Lobe Level, Half Power Beamwidth, and Nulls control using PSO

Introducing Deeper Nulls and Reduction of Side-Lobe Level in Linear and Non-Uniform Planar Antenna Arrays Using Gravitational Search Algorithm

A multi‐objective optimization approach for beam pattern synthesis of UAV virtual rectangular antenna array

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