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科技导报
| 专题论文 2017, 35(20): 19-27
雷达低可观测动目标精细化处理及应用
全屏
陈小龙1 , 关键1 , 黄勇1 , 于晓涵2 , 刘宁波2 , 董云龙2 , 何友2
作者信息
1. 海军航空大学电子信息工程系, 烟台 264001;
2. 海军航空大学信息融合研究所, 烟台 264001
Radar refined processing and its applications for low-observable moving target
Affiliations
出版时间: 2017-10-28
doi: 10.3981/j.issn.1000-7857.2017.20.002
文章导航
雷达探测环境复杂、探测对象特征多样,回波具有低可观测性,雷达探测性能难以满足实际需求,面临着复杂环境下微弱目标检测难题。本文论述了低可观测动目标的内涵、特征、雷达探测面临的挑战以及精细化处理的关键技术,结合雷达实测数据给出了工程应用的途径,并展望了对精细化处理的发展方向。
雷达动目标检测
/
低可观测目标
/
精细化处理
/
特征提取
/
稀疏表示
/
目标识别
As the main equipment of target detection and surveillance, the radar plays an important role in the air and sea target monitoring, early warning detection and other public and defense security applications. Due to the complex detection environment and the variety of the targets, the echo has a low observability. It is dificult for the radar detection performance to meet the actual demand, and we face the weak target detection problem in a complex environment. In recent years, with the development of the radar system and the radar signal processing technology, the radar gains the ability to obtain fine target characteristics, and by extending the signal dimension, a new way is provided for the radar target detection and recognition. This paper reviews the connotation and the characteristics of the low observable moving target, the challenge of the radar detection and the key technology of fine processing, focusing on the engineering applications based on the measured data of the radar. Finally, the development direction of fine processing is discussed.
radar moving target detection
/
low-observable target
/
refined processing
/
feature extraction
/
sparse representation
/
target recognition
陈小龙, 关键, 黄勇, 于晓涵, 刘宁波, 董云龙, 何友.
雷达低可观测动目标精细化处理及应用.
科技导报,
2017
, 35
(20)
: 19
-27
.
DOI: 10.3981/j.issn.1000-7857.2017.20.002
CHEN Xiaolong, GUAN Jian, HUANG Yong, YU Xiaohan, LIU Ningbo, DONG Yunlong, HE You.
Radar refined processing and its applications for low-observable moving target[J].
Science & Technology Review ,
2017
, 35
(20)
: 19
-27
.
DOI: 10.3981/j.issn.1000-7857.2017.20.002
2017年第35卷第20期
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文章信息
doi: 10.3981/j.issn.1000-7857.2017.20.002
接收时间:2017-09-25
首发时间:2017-10-31
出版时间:2017-10-28
收稿日期:2017-09-25
修回日期:2017-10-12
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2017.20.002
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 Genus 种数 Number of species 占总种数比例 Percentage of total species (%) 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
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