Radar Waveform Recognition Based on Time-Frequency Analysis and Artificial Bee Colony-Support Vector Machine

被引：34

作者：

Liu, Lutao ^{[1
]}

Wang, Shuang ^{[1
]}

Zhao, Zhongkai ^{[1
]}

机构：

[1] Harbin Engn Univ, Coll Informat & Telecommun, Harbin 150001, Heilongjiang, Peoples R China

来源：

ELECTRONICS | 2018年 / 7卷 / 05期

基金：

中国国家自然科学基金;

关键词：

radar waveform recognition; electronic warfare; support vector machine; artificial bee colony;

D O I：

10.3390/electronics7050059

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

080201 [机械制造及其自动化];

摘要：

In this paper, a system for identifying eight kinds of radar waveforms is explored. The waveforms are the binary phase shift keying (BPSK), Costas codes, linear frequency modulation (LFM) and polyphase codes (including P1, P2, P3, P4 and Frank codes). The features of power spectral density (PSD), moments and cumulants, instantaneous properties and time-frequency analysis are extracted from the waveforms and three new features are proposed. The classifier is support vector machine (SVM), which is optimized by artificial bee colony (ABC) algorithm. The system shows well robustness, excellent computational complexity and high recognition rate under low signal-to-noise ratio (SNR) situation. The simulation results indicate that the overall recognition rate is 92% when SNR is -4 dB.

引用

页数：19

共 26 条

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