A Neural Network-Based Microwave Imaging Method for Object Localization

A Neural Network-Based Microwave Imaging Method for Object Localization
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초록

This paper presents a new microwave imaging method using artificial neural networks to localize an object. The trained neural network reconstructs a tomographic image from the measured scattering data, such as a nonlinear electromagnetic inverse scattering solver. The appropriate number of hidden neurons is determined through the cross-entropy between network predictions and target values. To verify this method experimentally, we set up a testbed consisting of 16 antennas that transmit and receive 950 MHz microwaves underwater and used a metal rod with a diameter of 2 mm as a localizing target. The results show excellent imaging performance with fewer artifacts and less than a 2-mm localization error.

키워드

Artificial Neural Networks; Inverse Scattering; Microwave Imaging; Object Localization.
제목
A Neural Network-Based Microwave Imaging Method for Object Localization
제목 (타언어)
A Neural Network-Based Microwave Imaging Method for Object Localization
저자
손원형; 박원광; 손성호
DOI
10.26866/jees.2022.5.r.125
발행일
2022-09
유형
Article
저널명
Journal of Electromagnetic Engineering and Science
권
22
호
5
페이지
576 ~ 579