Design of ultra-wideband multilayer slant linear polarizer using a genetic algorithm

2001 ◽  
Vol 30 (2) ◽  
pp. 119-122 ◽  
Author(s):  
Y. Purushottam ◽  
R. V. Hara Prasad ◽  
V. C. Misra
Keyword(s):  
Genetic Algorithm ◽  
Ultra Wideband ◽  
Linear Polarizer

Design of a small ultra wideband antenna using a genetic algorithm approach

2015 ◽  
Author(s):  
Mohammed H. Miry ◽  
Ghaida A. Al-Suhail ◽  
Fathi Abdussalam ◽  
M. B. Child ◽  
R. A. Abd-Alhameed
Keyword(s):  
Genetic Algorithm ◽  
Ultra Wideband ◽  
Wideband Antenna ◽  
Genetic Algorithm Approach

scholarly journals Evolutionary Computing based Neuron-Computational Model for Microstrip Patch Antenna Design Optimization

2021 ◽  
Vol 13 (03) ◽  
pp. 15-40
Author(s):  
Rohini Saxena ◽  
Mukesh Kumar ◽  
Shadman Aslam
Keyword(s):  
Genetic Algorithm ◽  
Patch Antenna ◽  
Evolutionary Computing ◽  
Microstrip Patch Antenna ◽  
Ultra Wideband ◽  
Antenna Design ◽  
Design Parameters ◽  
Adaptive Genetic Algorithm ◽  
Microstrip Patch ◽  
Depth Analysis

In this paper, a novel Evolutionary Computing named Adaptive Genetic Algorithm (AGA) based ANN model is developed for rectangular MPA (Microstrip patch antenna). Considering at-hand and Nextgeneration Ultra wideband application demands, the emphasis has been made on retaining optimal lowcost design with desired cut-off frequency. The proposed method employs multiple sets of theoreticallydriven training instances or patch antenna design parameters which have been processed for normalization and sub-sampling to achieve a justifiable and reliable sample size for further design parameter prediction. Procedurally, the input design parameters were processed for normalization followed by sub-sampling to give rise to a sufficient set of inputs to perform knowledge-driven (designparameter) prediction. Considering limitations of the major at-hand machine learning methods which often undergo local minima and convergence while training, we designed a state-of-art new Adaptive Genetic Algorithm based neuro-computing model (AGA-ANN), which helped to predict the set of optimal design parameters for rectangular microstrip patch antenna. The predicted patch antenna length and width values were later used for verification which achieved the expected frequency. The depth analysis revealed that a rectangular patch antenna with width 14.78 mm, length 11.08mm, feed-line 50 Ω can achieve the cut-off frequency of 8.273 GHz, which can be of great significance for numerous UWB applications.

scholarly journals On-line Optimal Ranging Sensor Deployment for Robotic Exploration

2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Mobile Agents ◽  
Ultra Wideband ◽  
Sensor Deployment ◽  
Positioning System ◽  
Mobile System ◽  
Robotic Exploration ◽  
On Line ◽  
Geometric Dilution Of Precision

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

scholarly journals On-line Optimal Ranging Sensor Deployment for Robotic Exploration

2021 ◽  
Author(s):  
Luca Santoro ◽  
Davide Brunelli ◽  
daniele fontanelli
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Mobile Agents ◽  
Ultra Wideband ◽  
Sensor Deployment ◽  
Positioning System ◽  
Mobile System ◽  
Robotic Exploration ◽  
On Line ◽  
Geometric Dilution Of Precision

<div>Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user's threshold, using the Geometric Dilution of Precision (GDoP).</div>

Genetic Algorithm Based Equalizer for Ultra-Wideband Wireless Communication Systems

2010 ◽  
Vol E93-B (10) ◽  
pp. 2725-2734 ◽  
Author(s):  
Nazmat SURAJUDEEN-BAKINDE ◽  
Xu ZHU ◽  
Jingbo GAO ◽  
Asoke K. NANDI ◽  
Hai LIN
Keyword(s):  
Genetic Algorithm ◽  
Wireless Communication ◽  
Communication Systems ◽  
Ultra Wideband ◽  
Wireless Communication Systems ◽  
Wideband Wireless Communication
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