航空学报 > 2016, Vol. 37 Issue (6): 1963-1973   doi: 10.7527/S1000-6893.2016.0054

基于混合体制雷达网的弹道目标微特征及外形参数提取

李靖卿1,2, 冯存前1, 孙宏伟2, 贺思三1   

  1. 1. 空军工程大学 防空反导学院, 西安 710051;
    2. 中国人民解放军 93764部队, 包头 075000
  • 收稿日期:2015-07-13 修回日期:2016-02-29 出版日期:2016-06-15 发布日期:2016-03-04
  • 通讯作者: 冯存前 男,博士,教授,博士生导师。主要研究方向:雷达信号处理、雷达电子战新技术。Tel:029-84789131 E-mail:fengcunqian@sina.com E-mail:fengcunqian@sina.com
  • 作者简介:李靖卿 男,硕士研究生。主要研究方向:雷达信号处理。Tel:029-84789420 E-mail:lijingqing_1025@126.com;孙宏伟 男,博士,高级工程师。主要研究方向:雷达系统、电子对抗技术。E-mail:liuyanhui1999@126.com;贺思三 男,博士,讲师。主要研究方向:雷达信号处理、复杂运动目标成像。E-mail:hesisan@163.com
  • 基金资助:

    国家自然科学基金(61372166,61501495);陕西省自然科学基础研究计划资助项目(2014JM8308)

Micro-motion feature and shape parameters extraction based on hybrid-scheme radar network for ballistic targets

LI Jingqing1,2, FENG Cunqian1, SUN Hongwei2, HE Sisan1   

  1. 1. Air and Missile Defense College, Air Fore Engineering University, Xi'an 710051, China;
    2. No. 93764 Unit, People's Liberation Army of China, Baotou 075000, China
  • Received:2015-07-13 Revised:2016-02-29 Online:2016-06-15 Published:2016-03-04
  • Supported by:

    National Natural Science Foundation of China ( 61372166, 61501495): The Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (2014JM8308)

摘要:

针对弹道中段目标微特征难以识别与分辨的问题,提出了一种基于低分辨雷达和高分辨雷达相结合的混合体制雷达网的有翼弹道目标微特征及外形参数提取方法。依据非线性信号参量可分离模型,利用非线性最小二乘估计方法解算出有翼弹道目标群各散射中心的幅相参数,结合不同雷达提取的微特征的关联性,利用散射中心关联处理实现了各类散射中心的分离。在此基础上,利用弹道目标的微特征,结合弹道目标各散射中心的相对位置关系,重构出各目标的三维微特征及各散射中心的三维位置矢量,进而估计出目标的进动特征和结构参数。仿真结果表明:当信噪比(SNR)为5 dB时,该方法的重构精度保持在92%左右。

关键词: 微特征, 混合体制雷达网, 匹配, 特征提取, 弹道目标

Abstract:

Aiming at the complexity of recognition and resolution on ballistic mid-course target, a method for three-dimensional reconstruction of ballistic target based on hybrid-scheme radar network combined low-resolution radar with high-resolution radar is proposed. Based on the separable model of nonlinear signal parameter, the amplitude-phase parameters of each scattering center on the ballistic target group with empennages are calculated by nonlinear least squares estimation method. Combined with the relationship of micro-motion features between radars, various scattering centers are separated by association processing between scattering centers. Ultimately, the three-Dimensional micro-motion features and the three-Dimensional position vectors are reconstructed by utilizing both the micro-Doppler characteristics and the relative position relation of each scattering center of ballistic target, and then the precession feature and structural parameters are estimated. Simulation results validate that the reconstruction precision of three-dimensional features has been maintained at about 92% when the signal noise ratio (SNR) is 5 dB.

Key words: micro-motion feature, hybrid-scheme radar network, matching, feature extraction, ballistic target

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