基于微多普勒的空间锥体目标微动分类

doi:10.13700/j.bh.1001-5965.2016.0500

北京航空航天大学学报 ›› 2017, Vol. 43 ›› Issue (7): 1387-1394.doi: 10.13700/j.bh.1001-5965.2016.0500

基于微多普勒的空间锥体目标微动分类

束长勇¹, 张生俊², 黄沛霖¹, 姬金祖¹

1. 北京航空航天大学航空科学与工程学院, 北京 100083;
2. 试验物理与计算数学国家重点实验室, 北京 100076

收稿日期:2016-06-12 修回日期:2016-09-30 出版日期:2017-07-20 发布日期:2016-11-14
通讯作者: 姬金祖,E-mail:jijinzu@buaa.edu.cn E-mail:jijinzu@buaa.edu.cn
作者简介:束长勇男,博士研究生。主要研究方向:雷达信号处理及目标识别;张生俊男,博士,研究员。主要研究方向:新型光电材料与器件、等离子体技术研究、隐身预研研究;黄沛霖男,博士,副教授。主要研究方向:飞行器隐身设计、飞行器总体设计;姬金祖男,博士,讲师。主要研究方向:飞行器隐身设计、电磁计算和测试。

Micro-motion classification of spatial cone target based on micro-Doppler

SHU Changyong¹, ZHANG Shengjun², HUANG Peilin¹, JI Jinzu¹

1. School of Aeronautic Science and Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
2. National Key Laboratory on Test Physics & Numerical Mathematics, Beijing 100076, China

Received:2016-06-12 Revised:2016-09-30 Online:2017-07-20 Published:2016-11-14

摘要/Abstract

摘要： 空间锥体目标在飞行时存在多种微动，具体可分为章动、进动及自旋，准确获取目标微动形式是弹道目标微动及结构参数估算的前提。首先分析了3种微动形式下锥体目标锥顶及锥底滑动型散射源微多普勒及其频谱分布特性，发现自旋锥体目标散射源微多普勒为0 Hz，章动锥体目标任意散射源微多普勒谱的峰值非等间距分布，进动锥体目标任意散射源微多普勒谱的峰值等间距分布。据此提出利用微多普勒阈值识别自旋、利用微多普勒谱峰值是否等间距分布识别章动和进动的分类方法。最后通过仿真说明了本文分类方法的有效性，可为空间锥体目标微动分类提供一定的参考。

关键词: 空间锥体目标, 微动分类, 微多普勒谱, 强散射源, 特征提取

Abstract: There are many kinds of micro-motion in the spatial cone target in flight, which can be divided into nutation, precession and spinning. Accurate acquisition of the target's micro-motion form is the premise for the estimation of the micro-motion and the structural parameters of the ballistic target. First, the micro-Doppler distribution characteristics and the spectrum distribution characteristics of the cone target's cone node and cone bottom slip-type scattering source under the three micro-motions are analyzed, and it is found out that the micro-Doppler of spinning cone target's scattering source is 0 Hz, the micro-Doppler spectrum's peak value of nutation cone target's arbitrary scattering source is non-equidistantly distributed, and the micro-Doppler spectrum's peak value of precession cone target's arbitrary scattering source is equidistantly distributed. Base on this, the paper proposes the classification method, which recognizes the spinning cone target by the threshold of micro-Doppler and recognizes the nutation or precession cone target by judging whether micro-Doppler spectrum's peak value is equidistantly distributed or non-equidistantly distributed. Finally, the validity of the classification method is illustrated by simulation, which can provide reference for the micro-motion classification of spatial cone target.

Key words: spatial cone target, micro-motion classification, micro-Doppler spectrum, strong scattering sources, feature extraction

中图分类号:

TN953

束长勇, 张生俊, 黄沛霖, 姬金祖. 基于微多普勒的空间锥体目标微动分类[J]. 北京航空航天大学学报, 2017, 43(7): 1387-1394.

SHU Changyong, ZHANG Shengjun, HUANG Peilin, JI Jinzu. Micro-motion classification of spatial cone target based on micro-Doppler[J]. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2017, 43(7): 1387-1394.

参考文献

[1] 韩勋,杜兰,刘宏伟,等.窄带雷达观测下的锥体目标参数估计方法[J].西安电子科技大学学报,2015,42(6):43-48.HAN X,DU L,LIU H W,et al.Parameter estimation method for the cone-shaped target under narrow-band radar observation [J].Journal of Xidian University,2015,42(6):43-48(in Chinese).
[2] 杨有春,童宁宁,冯存前,等.利用最强散射点信息的平动补偿与微多普勒提取[J].西安电子科技大学学报,2012,39(6):147-153.YANG Y C,TONG N N,FENG C Q,et al.Translation compensation and micro-Doppler extraction by using the information on the strongest scatter[J].Journal of Xidian University,2012,39(6):147-153(in Chinese).
[3] 宁超,黄璟,黄培康.基于HRRP的进动锥体目标特征参数求解方法[J].系统工程与电子技术,2014,36(4):650-655.NING C,HUANG J,HUANG P K.Solution for characteristic parameters of precession cone-shaped target using HRRP[J].Systems Engineering and Electronics,2014,36(4):650-655(in Chinese).
[4] 黄璟,宁超,朱勇.基于最优路径的弹道目标径向长度提取方法[J].系统工程与电子技术,2015,37(7):1499-1503.HUANG J,NING C,ZHU Y.Estimation method for ballistic target range profile length based on the optimal route algorithm[J].Systems Engineering and Electronics,2015,37(7):1499-1503(in Chinese).
[5] 邵长宇,杜兰,韩勋,等.基于双视角距离像序列的空间锥体目标参数估计方法[J].电子与信息学报,2015,37(11):2735-2741.SHAO C Y,DU L,HAN X,et al.Estimation method for space coning target parameters based on two-aspect range profile sequences [J].Journal of Electronics & Information Technology,2015,37(11):2735-2741(in Chinese).
[6] 洪灵,戴奉周,刘宏伟.基于三维重构的空间目标进动参数估计方法[J].电波科学学报,2015,30(2):237-243.HONG L,DAI F Z,LIU H W.Precession parameters estimation for space target based on 3D reconstruction[J].Chinese Journal of Radio Science,2015,30(2):237-243(in Chinese).
[7] WANG Z L,YAN F X,HE F,et al.Missile target automatic recognition from its decoys based on image time-series[J].Pattern Recognition,2010,43(6):2157-2164.
[8] 金光虎,高勋章,黎湘,等.基于ISAR像序列的弹道目标进动特征提取[J].电子学报,2010,6(6):1-6.JIN G H,GAO X Z,LI X,et al.Precession feature extraction of ballistic targets based on dynamic image sequence[J].Acta Electronica Sinica,2010,6(6):1-6(in Chinese).
[9] 高红卫,谢良贵,文树梁,等.弹道导弹目标微动特性的微多普勒分析与仿真研究[J].系统仿真学报,2009,21(4):954-961.GAO H W,XIE L G,WEN S L,et al.Micro-Doppler analysis and simulation study of micro-motion performance of ballistic missile targets[J].Journal of System Simulation,2009,21(4):954-961(in Chinese).
[10] 高红卫,谢良贵,文树梁,等.基于微多普勒特征的真假目标雷达识别研究[J].电波科学学报,2008,23(4):775-780.GAO H W,XIE L G,WEN S L,et al.Research on radar target identification of warhead and decoys based on micro-Doppler signature[J].Chinese Journal of Radio Science,2008,23(4):775-780(in Chinese).
[11] 韩勋,杜兰,刘宏伟,等.基于时频分布的空间锥体目标微动形式分类[J].系统工程与电子技术,2013,35(4):684-691.HAN X,DU L,LIU H W,et al.Classification of micro-motion form of space cone-shaped objects based on time-frequency distribution[J].Systems Engineering and Electronics,2013,35(4):684-691(in Chinese).
[12] 关永胜,左群声,刘宏伟,等.空间锥体目标微动特性分析与识别方法[J].西安电子科技大学学报,2011,38(2):105-111.GUAN Y S,ZUO Q S,LIU H W,et al.Micro-motion characteristic analysis and recognition of cone-shaped targets[J].Journal of Xidian University,2011,38(2):105-111(in Chinese).
[13] 关永胜,左群声,刘宏伟.基于微多普勒特征的空间锥体目标识别[J].电波科学学报,2011,26(2):209-215.GUAN Y S,ZUO Q S,LIU H W.Micro-Doppler signature based cone-shaped target recognition[J].Chinese Journal of Radio Science,2011,26(2):209-215(in Chinese).
[14] 关永胜,左群声.基于特征谱的空间锥体目标识别方法[J].中国电子科学研究院学报,2014,9(2):161-168.GUAN Y S,ZUO Q S.Eigenvalue spectrum signature based cone-shaped target recognition[J].Journal of CAEIT,2014,9(2):161-168(in Chinese).
[15] 王竹溪,郭敦仁.特殊函数概论[M].北京:北京大学出版社,2012:260-264.WANG Z X,GUO D R.Introduction to special function [M].Beijing:Peking University Press,2012:260-264(in Chinese).

基于微多普勒的空间锥体目标微动分类

Micro-motion classification of spatial cone target based on micro-Doppler

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	谭治学, 钟诗胜, 林琳. 多源数据融合的民航发动机修后性能预测[J]. 北京航空航天大学学报, 2019, 45(6): 1106-1113.
[2]	王星, 呙鹏程, 田元荣, 王玉冰. 基于BDS-GD的低截获概率雷达信号识别[J]. 北京航空航天大学学报, 2018, 44(3): 583-592.
[3]	黄洁, 姜志国, 张浩鹏, 姚远. 基于卷积神经网络的遥感图像舰船目标检测[J]. 北京航空航天大学学报, 2017, 43(9): 1841-1848.
[4]	王文哲, 吴华, 王经商, 张强. 基于CEEMDAN的雷达信号脉内细微特征提取法[J]. 北京航空航天大学学报, 2016, 42(11): 2532-2539.
[5]	唐荻音, 于劲松, 陈雄姿, 王宏伦. 一种全局的无关线性图嵌入故障特征提取算法[J]. 北京航空航天大学学报, 2013, 39(3): 411-415.
[6]	薛斌党, 邢艳琦. 基于菲涅耳变换的不变矩提取及目标识别方法[J]. 北京航空航天大学学报, 2012, 38(8): 1001-1004,1063.
[7]	崔桂磊, 唐永华. 基于时频分析的运载火箭故障特征提取技术[J]. 北京航空航天大学学报, 2012, 38(6): 741-744,749.
[8]	赵慧洁, 蔡辉, 李娜. 基于多重分形参数的高光谱数据特征提取[J]. 北京航空航天大学学报, 2012, 38(10): 1317-1320.
[9]	董超, 赵慧洁. 基于局部线性嵌入的高光谱影像特征提取算法[J]. 北京航空航天大学学报, 2010, 36(8): 957-960.
[10]	诸彤宇,郭胜敏,吕卫锋. 基于SVM的浮动车行驶模式判断模型[J]. 北京航空航天大学学报, 2008, 34(8): 976-980.
[11]	唐葆君, 刘小龙, 邱菀华. 基于极大熵聚类的工程项目风险预警模型[J]. 北京航空航天大学学报, 2008, 34(7): 812-815.
[12]	席平, 孙肖霞. 基于CAD模型的涡轮叶片误差检测系统[J]. 北京航空航天大学学报, 2008, 34(10): 1159-1162.
[13]	张少辉, 沈晓蓉, 范耀祖. 一种基于图像特征点提取及匹配的方法[J]. 北京航空航天大学学报, 2008, 34(05): 516-519.
[14]	孙凯鹏,李新军. 复杂背景下单个运动物体的实时视觉追踪算法[J]. 北京航空航天大学学报, 2008, 34(03): 344-347.
[15]	彭俊毅,陈桓,戴树岭. 多通道投影图像的几何自动拼接技术[J]. 北京航空航天大学学报, 2007, 33(12): 1444-1447.