J4 ›› 2012, Vol. 39 ›› Issue (6): 147-153.doi: 10.3969/j.issn.1001-2400.2012.06.024

• 研究论文 • 上一篇    下一篇

利用最强散射点信息的平动补偿与微多普勒提取

杨有春1,2;童宁宁1;冯存前1;程冬3;沈堤1   

  1. (1. 空军工程大学 防空反导学院,陕西 西安  710000;
    2. 中国人民解放军94994部队,江苏 南京  210000;
    3. 西安电子科技大学 雷达信号处理国家重点实验室,陕西 西安  710071)
  • 收稿日期:2011-07-22 出版日期:2012-12-20 发布日期:2013-01-17
  • 通讯作者: 杨有春
  • 作者简介:杨有春(1986-),男,空军工程大学硕士研究生,E-mail: kj-yyc@163.com.
  • 基金资助:

    国家自然科学基金资助项目(61102109);陕西省自然科学基金资助项目(2010JQ8007)

Translation compensation and micro-Doppler extraction by using the information on the strongest scatter

YANG Youchun1,2;TONG Ningning1;FENG Cunqian1;CHENG Dong3;SHEN Di1   

  1. (1. Air Defence and Anti-misille Insi., Air Force Eng. Univ., Xi'an  710071, China;
    2. Unit 94994, PLA, Nanjing  210000, China
    3. National Key Lab. of Radar Signal Processing, Xidian Univ., Xi'an  710071, China)
  • Received:2011-07-22 Online:2012-12-20 Published:2013-01-17
  • Contact: YANG Youchun

摘要:

为了解决强噪声和平动调制下多散射点微多普勒提取问题,提出了一种基于最强散射点瞬时多普勒信息的平动补偿和微多普勒提取方法.该方法利用Viterbi算法提取最强散射点瞬时多普勒,根据多普勒率与微多普勒关系提取最强散射点的平动多普勒;通过对平动多普勒的多项式回归得到平动参数,进而重构平动信号,并对回波信号进行平动补偿;通过对补偿后信号时频面进行Hough变换正弦检测来提取各散射点的微多普勒参数.仿真实验结果验证了该方法的有效性和精确性.

关键词: 弹道目标, 微动, 微多普勒, Viterbi算法, 多普勒率, Hough变换

Abstract:

In order to extract the micro-Doppler of multi-scatters when the echo is subject to strong noise and translation modification, a method based on the instantaneous Doppler of the strongest scatter is proposed. The instantaneous Doppler of the strongest scatter is obtained by the Viterbi algorithm. The translation Doppler is extracted according to the relation between Doppler rate and micro-Doppler. Translation parameters, on the basis of which the translation signal is reconstructed, are estimated by polynomial regression. Then translation modification is compensated and Micro-Doppler parameters of every scatter are extracted by Hough transform. Simulation results indicate that the method is valid and accurate.

Key words: ballistic target, micro-motion, micro-Doppler, Viterbi algorithm, Doppler rate, Hough transform

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