Very simple synthesis formulas for microcoplanar striplines

Yildiz, Celal; Kisioglu, Hakan

doi:10.1002/mop.27377

Cited by 2 publications

(2 citation statements)

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“…The ABC is one of the most recently emerged population‐based optimization algorithms finding near‐optimal solutions for the difficult optimization problems by motivation foraging behavior of honeybee swarm. In the ABC algorithm, three kinds of bee colony consisting of used, onlooker and scout are considered.…”

Section: Artificial Bee Colony Algorithmmentioning

confidence: 99%

“…To this end, three ISAR image scenarios containing two moving air target models with certain velocity and acceleration parameters were synthetically formed using the backscattered field data of the ideal point scatters by means of MATLAB®. To eliminate the inserted motion effects, the parameters accounting for blurring problem were then optimally determined with the help of artificial bee colony (ABC) which is a new and powerful optimization algorithm based on foraging behavior of the honeybee swarm. 2D image minimum entropy was used as an objective function in ABC algorithm to optimize the velocity and acceleration parameters.…”

Section: Introductionmentioning

confidence: 99%

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A powerful method based on artificial bee colony algorithm for translational motion compensation of ISAR image

Üstün

Özdemir

Akdağlı

et al. 2014

Micro & Optical Tech Letters

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Inverse synthetic aperture radar (ISAR) imaging is an efficient technique to generate two‐dimensional spatial distributions of radar cross‐section of a target. The received signal of ISAR contains interphase errors resulting in blurring problem in the images due to motion effects of the target. In this study, a simple, stable, and robust method based on artificial bee colony (ABC) algorithm has been proposed for motion compensation (MoComp) to overcome the blurring problem in ISAR images. The minimum entropy was used as objective function in the ABC algorithm for optimally determining the parameters of velocity and acceleration. The proposed method was implemented to four different scenarios based on the two air target models to show performance of the ABC algorithm. The radar signal of the target without MoComp was given as inputs to the ABC algorithm to determine velocity and acceleration values so as to provide the clearest ISAR image. The proposed method was compared with a suggestion reported elsewhere using particle swarm optimization (PSO), PSO with island model, genetic algorithm. It is pointed out that the proposed method is more successful, stable and efficient in terms of the image quality, entropy values, and standard deviation. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:2691–2698, 2014

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Section: Artificial Bee Colony Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%