Target Classification Using Features Based on Fractional Fourier Transform
Summary :
This letter describe target classification from the synthesized active sonar returns from targets. A fractional Fourier transform is applied to the sonar returns to extract shape variation in the fractional Fourier domain depending on the highlight points and aspects of the target. With the proposed features, four different targets are classified using two neural network classifiers.
- Publication
- IEICE TRANSACTIONS on Information Vol.E97-D No.9 pp.2518-2521
- Publication Date
- 2014/09/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8003
- Type of Manuscript
- LETTER
- Category
- Pattern Recognition
Authors
Jongwon SEOK
Changwon National University
Keunsung BAE
Kyungpook National University
Keyword
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Jongwon SEOK, Keunsung BAE, "Target Classification Using Features Based on Fractional Fourier Transform" in IEICE TRANSACTIONS on Information,
vol. E97-D, no. 9, pp. 2518-2521, September 2014, doi: 10.1587/transinf.2014EDL8003.
Abstract: This letter describe target classification from the synthesized active sonar returns from targets. A fractional Fourier transform is applied to the sonar returns to extract shape variation in the fractional Fourier domain depending on the highlight points and aspects of the target. With the proposed features, four different targets are classified using two neural network classifiers.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8003/_p
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@ARTICLE{e97-d_9_2518,
author={Jongwon SEOK, Keunsung BAE, },
journal={IEICE TRANSACTIONS on Information},
title={Target Classification Using Features Based on Fractional Fourier Transform},
year={2014},
volume={E97-D},
number={9},
pages={2518-2521},
abstract={This letter describe target classification from the synthesized active sonar returns from targets. A fractional Fourier transform is applied to the sonar returns to extract shape variation in the fractional Fourier domain depending on the highlight points and aspects of the target. With the proposed features, four different targets are classified using two neural network classifiers.},
keywords={},
doi={10.1587/transinf.2014EDL8003},
ISSN={1745-1361},
month={September},}
Copy
TY - JOUR
TI - Target Classification Using Features Based on Fractional Fourier Transform
T2 - IEICE TRANSACTIONS on Information
SP - 2518
EP - 2521
AU - Jongwon SEOK
AU - Keunsung BAE
PY - 2014
DO - 10.1587/transinf.2014EDL8003
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E97-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 2014
AB - This letter describe target classification from the synthesized active sonar returns from targets. A fractional Fourier transform is applied to the sonar returns to extract shape variation in the fractional Fourier domain depending on the highlight points and aspects of the target. With the proposed features, four different targets are classified using two neural network classifiers.
ER -
English
