电子学报 ›› 2014, Vol. 42 ›› Issue (3): 602-606.DOI: 10.3969/j.iss.0372-2012-2014.03.028

• 科研通信 • 上一篇    下一篇

一种基于S变换的高频地波雷达瞬态干扰抑制方法

徐兴安, 吴雄斌, 陈骁锋, 沈志奔   

  1. 武汉大学电子信息学院, 湖北武汉 430072
  • 收稿日期:2012-11-24 修回日期:2013-10-08 出版日期:2014-03-25
    • 作者简介:
    • 徐兴安 男,1987年生于新疆拜城,武汉大学电子信息学院在读博士研究生.主要研究方向为高频超视距雷达信号处理.E-mail:iamxxa@whu.edu.cn
    • 基金资助:
    • 国家自然科学基金 (No.60571065); ‘十二五’863计划 (No.2012AA091701); 中央高校基本科研业务费专项资金 (No.2012212020207)

An Instantaneous Interference Suppression Approach Based on S Transforms

XU Xing-an, WU Xiong-bin, CHEN Xiao-feng, SHEN Zhi-ben   

  1. School of Electronics & Information, Wuhan University, Wuhan, Hubei 430072, China
  • Received:2012-11-24 Revised:2013-10-08 Online:2014-03-25 Published:2014-03-25
    • Supported by:
    • National Natural Science Foundation of China (No.60571065); National High Technology Research and Development Program of China  (863 Program) during the 12th Five-year Plan (No.2012AA091701); Fundamental Research Funds for the Central Universities (No.2012212020207)

摘要: 针对高频地波雷达中出现的瞬态干扰问题,提出了基于S变换(Stockwell transforms)的瞬态干扰抑制方法.首先分析了两次FFT信号处理机制下瞬态干扰的时频特征;然后应用S变换对雷达信号进行时频分析,利用瞬态干扰在时频维扩展性不同的特点,实现瞬态干扰的检测;最后应用三层BP(Back Propagation)神经网络对海洋回波信号进行预测和恢复.该方法避免了海杂波抑制的步骤,具有计算量小、信号损失小的优点.现场实测数据分析表明,该方法能够有效抑制瞬态干扰,使回波多普勒谱信噪比提高达10dB,有效提高了雷达的抗干扰能力.

关键词: 高频地波雷达, 瞬态干扰抑制, S变换, BP神经网络

Abstract: A new method based on S tansforms is proposed to suppress instantaneous interference for high frequency surface wave radar (HFSWR) application.The characteristics of instantaneous interference in time and Doppler domain were discussed within the twice-FFT signal processing framework;then S transforms was applied to outline the characteristics of instantaneous interference in time-frequency domain for interference detection and excision;finally,BP neural network was used to recover the sea echo signals.Experiment results show that the anti-interference ability is enhanced by this method,and the SNR of Doppler spectrum is improved for about 10dB.

Key words: high frequency surface wave radar, instantaneous interference suppression, S transforms, time-frequency analysis, BP neural network

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