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76897

Classification of Reconstructed SAR Images Based on Convolutional Neural Network

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Last updated: 04 Jan 2025

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Abstract

Synthetic aperture radar (SAR) is a very important radar imaging type in which the utilization of antenna movement with respect to the target to be detected is considered. Detecting of target existence through noisy received images is a very critical and challenging point. Classification through deep learning presented in the form of Convolutional Neural Network (CNN) is a very good choice to enhance the decision performance reducing the error rate and false alarms. The main aim of this paper is to use a reliable classification technique in order to detect target existence through noisy received SAR images. Training data set for CNN is collected through a simulation in which realistic SAR images can be generated and used for SAR Automatic Target Recognition (ATR). CNNs are performed on images to classify the existence of targets. The accuracy of this approach is 100%.  

DOI

10.21608/mjeer.2019.76897

Keywords

Convolutional neural network (CNN), Radar imaging, SAR imaging, range Doppler algorithm (RDA), Image Reconstruction, Image classification, Automatic Target Recognition (ATR)

Authors

First Name

Alaa M.

Last Name

El-Ashkar

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-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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First Name

Ahmed

Last Name

Sedik

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-

Affiliation

Department of The Robotics and intelligent Mschines, Faculty of Artificial Intelligence, Kafrelsheikh University, Kafr El-Sheikh, Egypt

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First Name

H.

Last Name

Shendy

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-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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First Name

Taha El Sayed

Last Name

Taha

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-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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First Name

Adel S.

Last Name

El-Fishawy

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-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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First Name

Mohamed

Last Name

Abd El-Nabi

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-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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First Name

Ashraf A. M

Last Name

. Khalaf

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Affiliation

Electronics and Communications Engineering Department, Faculty of Engineering Minya University Minya, Egypt

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First Name

GH. M.

Last Name

El-Banby

MiddleName

-

Affiliation

Industrial Electronics andd Automatic Control Engineering Department Faculty of Electronic Engineering,Manoufia University: Menouf,Egypt

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First Name

Fathi E.

Last Name

Abd El-Samie

MiddleName

-

Affiliation

Communications and Electronics Department Faculty of Electronic Engineering, Menoufia University Menouf, Egypt

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Volume

28

Article Issue

ICEEM2019-Special Issue

Related Issue

9704

Issue Date

2019-12-01

Receive Date

2020-03-11

Publish Date

2019-12-01

Page Start

122

Page End

125

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_76897.html

Detail API

https://mjeer.journals.ekb.eg/service?article_code=76897

Order

44

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Classification of Reconstructed SAR Images Based on Convolutional Neural Network

Details

Type

Article

Created At

22 Jan 2023