scholarly journals Optimum design of non-uniform symmetrical linear antenna arrays using a novel modified invasive weeds optimization

2016 ◽  
Vol 65 (1) ◽  
pp. 5-18 ◽  
Author(s):  
El Hadi Kenane ◽  
Farid Djahli
Keyword(s):  
Antenna Arrays ◽  
Optimization Technique ◽  
Optimization Method ◽  
Good Alternative ◽  
Side Lobe ◽  
Good Choice ◽  
Side Lobe Level ◽  
Invasive Weeds ◽  
Linear Antenna ◽  
Linear Antenna Arrays

Abstract This paper presents a new modified method for the synthesis of non-uniform linear antenna arrays. Based on the recently developed invasive weeds optimization technique (IWO), the modified invasive weeds optimization method (MIWO) uses the mutation process for the calculation of standard deviation (SD). Since the good choice of SD is particularly important in such algorithm, MIWO uses new values of this parameter to optimize the spacing between the array elements, which can improve the overall efficiency of the classical IWO method in terms of side lobe level (SLL) suppression and nulls control. Numerical examples are presented and compared to the existing array designs found in the literature, such as ant colony optimization (ACO), particle swarm optimization (PSO), and comprehensive learning PSO (CLPSO). Results show that MIWO method can be a good alternative in the design of non-uniform linear antenna array.

scholarly journals A Hybrid GA/GE Beamforming Technique for Side Lobe Cancellation of Linear Antenna Arrays

2021 ◽  
Vol 10 (2) ◽  
pp. 67-77
Author(s):  
S. I. Abdelrahman ◽  
A. H. Hussein ◽  
A. E. A. Shaalan
Keyword(s):  
Antenna Arrays ◽  
Optimization Technique ◽  
Side Lobe ◽  
Main Beam ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Gauss Elimination ◽  
Half Power ◽  
Beamforming Technique ◽  
Linear Antenna Arrays

Side lobe level reduction is one of the most critical research topics in antenna arrays beamforming as it mitigates the interfering and jamming signals. In this paper, a hybrid combination between the Genetic algorithm (GA) optimization technique and the gauss elimination (GE) equation solving technique is utilized for the introduction of the proposed GA/GE beamforming technique for linear antenna arrays. The proposed technique estimates the optimum excitation coefficients and the non-uniform inter-elements spacing for a specific side lobe (SL) cancellation without disturbing the half power beamwidth (HPBW) of the main beam. Different size Chebychev linear antenna arrays are taken as simulation targets. The simulation results revealed the effectiveness of the proposed technique

scholarly journals The optimal synthesis of scanned linear antenna arrays

2020 ◽  
Vol 10 (2) ◽  
pp. 1477
Author(s):  
Anas A. Amaireh ◽  
Asem S. Al-Zoubi ◽  
Nihad I. Dib
Keyword(s):  
Antenna Arrays ◽  
Firefly Algorithm ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Symbiotic Organisms Search ◽  
Optimization Parameters ◽  
Antlion Optimization ◽  
Symbiotic Organisms ◽  
Linear Antenna Arrays

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA).

A Crossover Improved Genetic Algorithm and Its Application in Non-Uniform Linear Antenna Arrays

2017 ◽  
Vol 16 (04) ◽  
pp. 1750027 ◽  
Author(s):  
Bhargav Appasani ◽  
Rahul Pelluri ◽  
Vijay Kumar Verma ◽  
Nisha Gupta
Keyword(s):  
Genetic Algorithm ◽  
Antenna Arrays ◽  
Optimization Technique ◽  
Beam Width ◽  
Side Lobe ◽  
Optimization Techniques ◽  
Linear Antenna ◽  
Improved Genetic Algorithm ◽  
Element Array ◽  
Linear Antenna Arrays

Genetic Algorithm (GA) is a widely used optimization technique with multitudinous applications. Improving the performance of the GA would further augment its functionality. This paper presents a Crossover Improved GA (CIGA) that emulates the motion of fireflies employed in the Firefly Algorithm (FA). By employing this mimicked crossover operation, the overall performance of the GA is greatly enhanced. The CIGA is tested on 14 benchmark functions conjointly with the other existing optimization techniques to establish its superiority. Finally, the CIGA is applied to the practical optimization problem of synthesizing non-uniform linear antenna arrays with low side lobe levels (SLL) and low beam width, both requirements being incompatible. However, the proposed CIGA applied for the synthesis of a 12 element array yields an SLL of [Formula: see text]29.2[Formula: see text]dB and a reduced beam width of 19.1[Formula: see text].

scholarly journals Synthesis and Failure Correction of Flattop and Cosecant Squared Beam Patterns in Linear Antenna Arrays

2017 ◽  
Vol 4 ◽  
pp. 25-30 ◽  
Author(s):  
Hemant Patidar ◽  
Gautam Kumar Mahanti ◽  
Ramalingam Muralidharan
Keyword(s):  
Antenna Arrays ◽  
Firefly Algorithm ◽  
Recovery Process ◽  
Side Lobe ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Successful Employment ◽  
The Individual ◽  
Beam Patterns ◽  
Linear Antenna Arrays

This paper deals with the synthesis of flattop and cosecant squared beam patterns using the firefly algorithm which is based on metaheuristics. This synthesis is followed by the correction of the radiation patterns when unfortunate malfunctioning of the individual elements in the array occurs. The necessary attention is given to the recovery process, with due emphasis on reduction of side lobe level, ripple and the reflection coefficient. Simulation in Matlab shows a successful employment of the firefly algorithm in producing voltage excitations of the good elements necessary for the recovered patterns. The performance of the firefly algorithm in failure correction is validated by duly comparing it with a standard benchmark.

scholarly journals A Feeding Network with Chebyshev Distribution for Designing Low Side-lobe Level Antenna Arrays

2017 ◽  
Author(s):  
Toan The Tang ◽  
Tran Minh Nguyen ◽  
Giang Truong Vu Bang
Keyword(s):  
Antenna Arrays ◽  
Linear Array ◽  
Side Lobe ◽  
Power Divider ◽  
Side Lobe Level ◽  
Linear Antenna ◽  
Sidelobe Level ◽  
Weighting Method ◽  
Low Sidelobe ◽  
Linear Antenna Arrays

This paper proposes a feeding networking to gain low sidelobe levels for microstrip linear antenna arrays. The procedure to design a feeding network using Chebyshev weighting method will be proposed and presented. As a demonstration, a feeding network for 8×1 elements linear array with Chebyshev distribution weights (preset sidelobe level of -25 dB) has been designed. An unequal T-junction power divider has been applied in designing the feeding network to guarantee the output powers the same as Chebyshev weights. The obtained results of the amplitudes at each output port have been validated with theory data. The phases of output signals are almost equal at all ports. The proposed feeding network, therefore, can be a good candidate for constructing a low sidelobe level linear array antenna.

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