基于分布式组网雷达的弹道目标三维进动特征提取

doi:10.3969/j.issn.0372-2112.2012.06.002

电子学报

基于分布式组网雷达的弹道目标三维进动特征提取

罗迎¹, 张群^1,2, 李松³, 梁颖¹

1. 空军工程大学电讯工程学院,陕西西安 710077;
2. 复旦大学波散射与遥感信息国家教育部重点实验室,上海 200433;
3. 空军工程大学导弹学院,陕西三原 713800

收稿日期:2011-04-25 修回日期:2011-08-26 出版日期:2012-06-25
- 作者简介:
- 罗迎 男,1984年8月出生于湖南益阳,现为空军工程大学电讯工程学院博士生,已在《IEEE Transactions on Geoscience and Remote Sensing》、《电子学报》等国内外学术期刊和会议录上发表和录用论文50余篇.研究方向:雷达成像与目标识别. E-mail:luoying2002521@163.com
- 基金资助:
- 国家自然科学基金 (No.60971100,No.61172169); 国家自然科学青年基金 (No.61102109)

Three-Dimensional Precession Feature Extraction of Ballistic Targets in Distributed Radar Networks

LUO Ying¹, ZHANG Qun^1,2, LI Song³, LIANG Ying¹

1. Telecommunication Engineering Institute,Air Force Engineering University,Xi’an,Shaanxi 710077,China;
2. Key Laboratory of Wave Scattering and Remote Sensing Information (Ministry of Education),Fudan University,Shanghai 200433,China;
3. Missile Institute,Air Force Engineering University,Sanyuan,Shaanxi 713800,China

Received:2011-04-25 Revised:2011-08-26 Online:2012-06-25 Published:2012-06-25
- Supported by:
- National Natural Science Foundation of China (No.60971100, No.61172169); Youth Fund of National Natural Science Foundation of China (No.61102109)

摘要/Abstract

摘要： 弹道目标微动特征提取是当前研究的一个热点,但在单基雷达中,由于视角限制,仅能提取目标在雷达视线方向上的微动分量,难以获得目标的真实三维微动参数.本文基于分布式组网雷达,利用组网雷达的多视角特性,提出了有翼弹道目标三维进动特征提取方法.首先基于目标锥顶散射点的微多普勒特征参数实现了目标空间三维锥旋矢量的重构,在此基础上,通过分析锥底边缘散射点的进动特征与微多普勒曲线的关系,提取了目标的进动周期、自旋周期、进动角、锥底半径、自旋轴与锥旋轴的交点位置等特征,并实现了目标长度的估计.仿真实验验证了算法的有效性,并进一步利用仿真实验分析了算法的鲁棒性.

关键词: 微多普勒, 分布式组网雷达, 弹道目标, 自动目标识别

Abstract: The micro-motion feature extraction for ballistic target has attracted great attention in recent years.Because of the limitation of the angle of view,only the characteristics of micro-motion projected in the line-of-sight (LOS) could be extracted in monostatic radars.In the paper,the distributed radar networks are utilized to obtain the three-dimensional micro-motion features of ballistic targets with empennages.Profited from the multi-view of distributed radar networks,the 3-D coning vector of target is reconstructed from the micro-Doppler parameters of the scatterer on the cone apex of ballistic target,and then the precession period,spinning period,precession angle,the radius of cone bottom,and the intersection location of the spinning axis and the conning axis are solved by analyzing the relationship between the micro-Doppler curves and the precession motion of the scatterers on edge of the cone bottom.The length of target is also estimated.Simulations validate the effectiveness of the algorithm,and the robustness of the algorithm is also analyzed.

Key words: micro-Doppler (m-D), distributed radar networks, ballistic target, auto target recognition (ATR)

中图分类号:

TN957

罗迎, 张群, 李松, 梁颖. 基于分布式组网雷达的弹道目标三维进动特征提取[J]. 电子学报, DOI: 10.3969/j.issn.0372-2112.2012.06.002.

LUO Ying, ZHANG Qun, LI Song, LIANG Ying. Three-Dimensional Precession Feature Extraction of Ballistic Targets in Distributed Radar Networks[J]. Acta Electronica Sinica, DOI: 10.3969/j.issn.0372-2112.2012.06.002.

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基于分布式组网雷达的弹道目标三维进动特征提取

Three-Dimensional Precession Feature Extraction of Ballistic Targets in Distributed Radar Networks

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