Target Classification Using Features Based on Fractional Fourier Transform

被引：13

作者：

Seok, Jongwon ^{[1
]}

Bae, Keunsung ^{[2
]}

机构：

[1] Changwon Natl Univ, Dept Informat & Commun, Chang Won 641773, South Korea

[2] Kyungpook Natl Univ, Sch Elect, Taegu 702701, South Korea

来源：

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2014年 / E97D卷 / 09期

关键词：

target; recognition; active sonar; pattern recognition; LFM; highlight model; fractional Fourier transform; NEURAL-NETWORKS;

D O I：

10.1587/transinf.2014EDL8003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：2518 / 2521

页数：4

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