Chebyshev-based array for beam steering and null positioning using modified ant lion optimization

2021 ◽  
pp. 1-15
Author(s):  
Hrudananda Pradhan ◽  
Biswa Binayak Mangaraj ◽  
Santanu Kumar Behera
Keyword(s):  
Beam Steering ◽  
Optimization Algorithms ◽  
Optimization Methods ◽  
Main Beam ◽  
Design Parameters ◽  
Sidelobe Level ◽  
Pattern Synthesis ◽  
Ant Lion Optimization ◽  
Array Pattern ◽  
Ant Lion

Abstract A modified ant lion optimization (MALO) algorithm is proposed in this article, for the synthesis of Chebyshev-based arrays by optimizing amplitudes and phases of excitations, and element spacings. Modification in ant lion optimization is achieved by hybridizing it with chaotic particle swarm optimization. The optimization process is employed to obtain an array pattern with the least possible sidelobe level. Close-in sidelobe level minimization for optimum pattern synthesis is suggested. Instead of only steering the main beam towards the desired direction presented by some popular optimization methods, the beam steering along with null positioning in other specified direction is also achieved employing MALO. Considering the arrays with the same design parameters and the results of other optimization algorithms, the performance of MALO is evaluated. The results show that MALO provides considerable improvements in an array pattern compared to the arrays optimized using other optimization algorithms and the uniform array.

Test scheduling of System-on-Chip using Dragonfly and Ant Lion optimization algorithms

2020 ◽  
pp. 1-13
Author(s):  
Gokul Chandrasekaran ◽  
P.R. Karthikeyan ◽  
Neelam Sanjeev Kumar ◽  
Vanchinathan Kumarasamy
Keyword(s):  
Ant Colony Optimization ◽  
Artificial Bee Colony ◽  
Optimization Algorithms ◽  
System On Chip ◽  
Test Time ◽  
Test Scheduling ◽  
Bee Colony ◽  
Ant Lion Optimization ◽  
Ant Lion ◽  
On Chip

Test scheduling of System-on-Chip (SoC) is a major problem solved by various optimization techniques to minimize the cost and testing time. In this paper, we propose the application of Dragonfly and Ant Lion Optimization algorithms to minimize the test cost and test time of SoC. The swarm behavior of dragonfly and hunting behavior of Ant Lion optimization methods are used to optimize the scheduling time in the benchmark circuits. The proposed algorithms are tested on p22810 and d695 ITC’02 SoC benchmark circuits. The results of the proposed algorithms are compared with other algorithms like Ant Colony Optimization, Modified Ant Colony Optimization, Artificial Bee Colony, Modified Artificial Bee Colony, Firefly, Modified Firefly, and BAT algorithms to highlight the benefits of test time minimization. It is observed that the test time obtained for Dragonfly and Ant Lion optimization algorithms is 0.013188 Sec for D695, 0.013515 Sec for P22810, and 0.013432 Sec for D695, 0.013711 Sec for P22810 respectively with TAM Width of 64, which is less as compared to the other well-known optimization algorithms.

Application of the Unit Circle Representation to Pattern Synthesis of Nonuniformly Spaced and Nonuniformly Excited Arrays based on the Teaching Learning Based Optimization

2019 ◽  
Vol 4 (1) ◽  
pp. 8-17
Author(s):  
Abdelmadjid RECIOUI
Keyword(s):  
Unit Circle ◽  
Antenna Array ◽  
Communication Systems ◽  
Sidelobe Level ◽  
Pattern Synthesis ◽  
Linear Arrays ◽  
Array Pattern ◽  
Teaching Learning Based Optimization ◽  
Null Placement ◽  
Teaching Learning

Pattern synthesis of Antenna array has gained much attention over the last years as they constitute an important role in the modern communication systems. Unit circle-based techniques such as Schelkunoff null placement method have proved their effectiveness to synthesize uniformly spaced linear arrays. Nonuniformly spaced antenna array pattern synthesis has been investigated and interesting results have been obtained. In this work, the unit circle representation approach is applied to synthesize nonuniformly spaced and nonuniformly excited linear arrays. The objective is to accurately place nulls in the desired directions while achieving the least possible sidelobe level. The problem is cast as an optimization problem that is solved using the Teaching Learning Based Optimization (TLBO). Examples are dealt with to prove the design approach effectiveness and flexibility for modern communication system applications.

scholarly journals Sidelobe Suppression in Array-Pattern Synthesis Using Periodic Leaky-Wave Antenna and Binomial Array

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Hicham Aziz ◽  
Mahmoud Moubadir ◽  
Abdelkrim Farkhsi ◽  
Naima Amar Touhami
Keyword(s):  
Antenna Array ◽  
Sidelobe Suppression ◽  
Sidelobe Level ◽  
Leaky Wave ◽  
Pattern Synthesis ◽  
Array Pattern ◽  
Leaky Wave Antenna ◽  
Wave Antenna ◽  
Measurement Results ◽  
Good Agreement

This paper presents the conception and realization of a 2D antenna array using periodic leaky-wave antenna (PLWA) and the binomial array (BA) at 6 GHz as the application of WLAN. The series array of periodic leaky-wave antenna was provided by an array of five rectangular Patches connected by cross lines. The nonuniform amplitudes of the binomial array are used to reduce the sidelobe level; in this way, the center source radiates strongly on the broadside. The prototype of the proposed 2D antenna array is designed, fabricated, and tested. A good agreement is obtained between simulated and measurement results.

scholarly journals Lowering the Sidelobe Level of a Two-Way Pattern in Shared Aperture Radar Arrays

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
John N. Sahalos
Keyword(s):  
Amplitude Distribution ◽  
Main Beam ◽  
Sidelobe Level ◽  
Array Pattern ◽  
A Minor ◽  
Receive Array ◽  
Aperture Radar

A study of lowering the peak SLL of shared aperture radar arrays is presented. A two-weight amplitude distribution for the elements of transmit and receive arrays is used. Imposing certain conditions, the relation of the number of elements of the arrays was found. One condition imposes the appearance of a minor lobe position of transmit or receive array pattern at a certain null of receive or transmit array pattern. A second condition imposes the equal sidelobe level of two consecutive minor lobes either near the main beam of the two-way array pattern or at certain positions of receive or transmit array pattern. The resulting peak SLL of the two-way radar array pattern depending on the conditions reaches from −47 dB up to less than −50 dB.

scholarly journals Array Pattern Synthesis Using Particle Swarm Optimization with Dynamic Inertia Weight

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Chuang Han ◽  
Ling Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Fitness Function ◽  
Particle Swarm ◽  
Main Beam ◽  
Pattern Synthesis ◽  
Swarm Optimization ◽  
Inertia Weight ◽  
Initial Space ◽  
Array Pattern ◽  
Dynamic Inertia Weight

A Feedback Particle Swarm Optimization (FPSO) with a family of fitness functions is proposed to minimize sidelobe level (SLL) and control null. In order to search in a large initial space and converge fast in local space to a refined solution, a FPSO with nonlinear inertia weight algorithm is developed, which is determined by a subtriplicate function with feedback taken from the fitness of the best previous position. The optimized objectives in the fitness function can obtain an accurate null level independently. The directly constrained SLL range reveals the capability to reduce SLL. Considering both element positions and complex weight coefficients, a low-level SLL, accurate null at specific directions, and constrained main beam are achieved. Numerical examples using a uniform linear array of isotropic elements are simulated, which demonstrate the effectiveness of the proposed array pattern synthesis approach.

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