Synthesis of Planar Arrays Using a Modified Particle Swarm Optimization Algorithm by Introducing a Selection Operator and Elitism

Diego, Marta Lanza; López, Jesús Ramón Pérez; Basterrechea, J.

doi:10.2528/pier09041303

Cited by 28 publications

(12 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Opposite to a large body of literature wherein a number of different global optimization procedures are used to synthesize shaped patterns by means of uniformly spaced arrays [4][5][6][7][8], deterministic and straightforward synthesis procedures have been discussed herein. In particular, in case of linear array a not very well known synthesis strategy, already available since [1], has been briefly reviewed and discussed.…”

Section: Discussionmentioning

confidence: 99%

“…Such a problem deserves indeed interest for a number of reasons, the main one being that while a large number of contributions exists in the literature wherein this kind of problems is solved by means of global optimization techniques [4][5][6][7][8], this is not actually needed in a number of cases (as we are going to see below).…”

Section: Introduction and Motivationsmentioning

confidence: 99%

See 1 more Smart Citation

On the Optimal Synthesis of Ring Symmetric Shaped Patterns by Means of Uniformly Spaced Planar Arrays

Morabito¹,

Laganà²,

Isernia³

2010

PIER B

View full text Add to dashboard Cite

Abstract-By taking inspiration from [1], a synthesis strategy is proposed for the case of planar arrays and ring shaped patterns which does not require the exploitation of global optimization procedures. In particular, the approach is able to determine a priori (that is, without solving the overall design problem) whether the given power pattern design constraints can be fulfilled or not, and, in the adfirmative case, to determine the needed excitation coefficients in a fast deterministic manner. Although the approach does not apply to generic planar arrays and generic constraints, it applies to a large number of problems of actual interest, and outperforms some recently published synthesis procedures. Moreover, it may serve both as a reference solution for more general synthesis procedures, and as an elementary brick for more cumbersome synthesis problems.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introduction and Motivationsmentioning

confidence: 99%

On the Optimal Synthesis of Ring Symmetric Shaped Patterns by Means of Uniformly Spaced Planar Arrays

Morabito¹,

Laganà²,

Isernia³

2010

PIER B

View full text Add to dashboard Cite

show abstract

“…But, this case also represents an appropriate example to compare both Taguchi's and SADE methods. In other papers as well, excitation synthesis using global optimizers like PSO [28] has been used for comparison purposes between different algorithms.…”

Section: Optimize Element Amplitudes (I N )mentioning

confidence: 99%

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

Dib¹,

Goudos²,

Muhsen³

2010

PIER

101

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

“…In recent years, the evolutionary algorithms (EAs) for array synthesis have been extensively studied [1,[3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Several global optimization algorithms such as differential evolution (DE) [3][4][5], genetic algorithm (GA) [6][7][8], ant colony optimization (ACO) [9], and particle swarm optimization (PSO) [10][11][12][13][14][15] are used in antenna array pattern. However, these methods appear certain drawbacks to the possibility of premature convergence to a local optimum when achieving the global optimum.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Unequally Spaced Antenna Arrays by Using Inheritance Learning Particle Swarm Optimization

Liu

Feng²,

Wang³

et al. 2011

PIER

View full text Add to dashboard Cite

Abstract-In this paper, synthesis of unequally spaced linear antenna arrays based on an inheritance learning particle swarm optimization (ILPSO) is presented. In order to improve the optimization efficiency of the PSO algorithm, we propose an inheritance learning strategy that can be applied to different topology of different PSO algorithms. In ILPSO algorithm, each cycle contains several PSO optimization processes, and uniform initial particle positions, part of which inherited from the good results in pre-cycles, are adopted in post-cycles. ILPSO enhances the exploration ability of PSO algorithm significantly, and can escape from the trap of local optimum areas with greater probability. The results demonstrate good performance of the ILPSO in solving a set of eight 30-D benchmark functions when compared to nine other variants of the PSO. The novel proposed algorithm has been applied in 32-element position-only array synthesis with three different constraints, simulation results show that ILPSO obtains better synthesis results reliably and efficiently.

show abstract

Synthesis of Planar Arrays Using a Modified Particle Swarm Optimization Algorithm by Introducing a Selection Operator and Elitism

Cited by 28 publications

References 25 publications

On the Optimal Synthesis of Ring Symmetric Shaped Patterns by Means of Uniformly Spaced Planar Arrays

On the Optimal Synthesis of Ring Symmetric Shaped Patterns by Means of Uniformly Spaced Planar Arrays

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

Synthesis of Unequally Spaced Antenna Arrays by Using Inheritance Learning Particle Swarm Optimization

Contact Info

Product

Resources

About