白晓惠,
郭子薰,
水鹏朗
西安电子科技大学雷达信号处理国家重点实验室 西安 710071
基金项目:国家自然科学基金(61871303)，电波环境特性及模化技术重点实验室基金(6142403180204)，111引智计划(B18039)
详细信息
作者简介:许述文(1985–)，男，安徽黄山人，博士，副教授，博士生导师，加拿大 Mcmaster 大学访问****，入选陕西省青年人才托举计划。2011 年在西安电子科技大学获得博士学位，现就职于西安电子科技大学电子工程学院雷达信号处理国家重点实验室。主要研究方向为雷达目标检测、机器学习、时频分析和 SAR 图像处理。E-mail: swxu@mail.xidian.edu.cn
白晓惠(1998–)，女，陕西宝鸡人，西安电子科技大学博士生。主要研究方向为雷达目标检测、机器学习和海杂波信号处理。E-mail: xhbai@stu.xidian.edu.cn
郭子薰(1994–)，女，陕西西安人，西安电子科技大学博士生。主要研究方向为雷达目标检测、机器学习和海杂波信号处理。E-mail: zxguo_724@stu.xidian.edu.cn
水鹏朗(1967–)，男，陕西西安人，博士，教授。1999年在西安电子科技大学获得博士学位，现担任西安电子科技大学电子工程学院雷达信号处理国家重点实验室教授、硕导、博导。主要研究方向为海杂波建模、雷达目标检测和图像处理。E-mail: plshui@xidian.edu.cn
通讯作者:许述文 swxu@mail.xidian.edu.cn
责任主编：关键 Corresponding Editor: GUAN Jian中图分类号:TN95
计量
文章访问数:2385
HTML全文浏览量:1012
PDF下载量:517
被引次数:0
出版历程
收稿日期:2020-06-25
修回日期:2020-08-14
网络出版日期:2020-08-28
Status and Prospects of Feature-based Detection Methods for Floating Targets on the Sea Surface (in English)
XU Shuwen,,BAI Xiaohui,
GUO Zixun,
SHUI Penglang
National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (61871303), The Foundation of National Key Laboratory of Electromagnetic Environment (6142403180204), The Foreign Scholars in University Research and Teaching Programs (the 111 Project) (B18039)
More Information
Author Bio:XU Shuwen was born in Huangshan city in Anhui, China. He received his B.Eng. and Ph.D. degrees, both in electronic engineering, from Xidian University, Xi’an, China, in 2006 and 2011, respectively. Subsequently, he worked at the National Laboratory of Radar Signal Processing, Xidian University. He worked as a visiting professor in McMaster University, Canada in 2018. He is currently a professor with the National Laboratory of Radar Signal Processing, Xidian University. His research interests are in the fields of radar target detection, statistical learning, and SAR image processing. E-mail: swxu@mail.xidian.edu.cn
BAI Xiaohui was born in Baoji, Shaanxi province in 1998. She is now a Ph.D. student in Xidian University. Her main research fields are radar target detection, machine learning, and sea clutter signal processing. E-mail: xhbai@stu.xidian.edu.cn
GUO Zixun was born in Xi’an, Shaanxi province in 1994. She is now a Ph.D. student in Xidian University. Her main research fields are radar target detection, machine learning, and sea clutter signal processing. E-mail: zxguo_724@stu.xidian.edu.cn
SHUI Penglang was born in Xi’an, Shaanxi province in 1967. He received his Ph.D. degree in electronic engineering from Xidian University, Xi’an, China, in 1999. He is now a professor, PhD supervisor at the Radar Signal Processing National Key Lab of Electronic Engineering from Xidian University. His main research fields are sea clutter modeling, radar target detection, and image processing. E-mail: plshui@xidian.edu.cn
Corresponding author:XU Shuwen, swxu@mail.xidian.edu.cn
摘要
摘要:海杂波背景下的雷达目标检测对民用和军事都有着重要的意义。随着海面目标的小型化和隐身化，海面慢速、漂浮小目标已经成为了雷达警戒的重点对象。关于此类小目标的检测一直以来都是海杂波背景下目标检测中的难题。通常，漂浮小目标的雷达散射横截面积(RCS)微弱，并且运动速度慢，常常在时域和频域均存在“超杂波检测”的困难。传统目标检测方法对漂浮小目标的检测存在明显的性能瓶颈。对于海面漂浮小目标的检测，采用高多普勒和高距离分辨体制(“双高”体制)是从雷达体制上解决这个问题的有效途径。在双高体制下，雷达接收的目标回波提供了更多的可用信息。然而，如何将这些更加精细化的信息转化为探测性能的提升，一直以来都是雷达届关注的难点，相关科研成果也一直在不断地推陈出新。近些年，在双高雷达体制下，****们提出了多种基于特征的目标检测方法，作为对海智能检测的人工特征工程阶段，这些方法缓解了仅依靠能量信息较难检测小目标的困难局面，极大程度地改善了对漂浮小目标的检测性能。为了更好地让相关雷达从业者了解该领域这些年的发展和未来的趋势，该文首先总结了对海检测的难点和常用的目标检测方法，然后分析了特征检测的原理和通用框架以及国内外几种典型的基于特征的检测方法，最后对特征检测方法发展趋势进行了展望。
关键词:海杂波/
漂浮小目标/
雷达目标检测/
特征提取/
特征检测
Abstract:Radar target detection in sea clutter is of significance to both the civil and military applications. With the miniaturization and invisibility of sea targets, Small Floating Targets (SFTs) with slow speed have become the focus of radar detection. However, the detection of SFTs in the background of sea clutter has always been a challenging problem. SFTs usually have a weak Radar Cross Section (RCS) and slow speed, making them difficult to be detected in sea clutter. Traditional target detection methods exhibit poor performance in the detection of SFTs. For the detection of small and weak targets on the sea surface, a high Doppler resolution and high range resolution system (double-high system) is an effective approach to solve this problem. In the double-high system, the target echo received by the radar provides readily available and sufficient information. However, how to transform and refine this information to improve detection performance has always been a challenge to the radar industry. In recent years, as an artificial feature engineering stage for intelligent radar target detection, scholars have proposed various feature-based target detection methods based on the double-high system to alleviate the difficulty of SFT detection when relying only on energy information and to considerably improve the detection performance. To ensure that relevant radar practitioners better understand the development of this field in recent years and the future trend, this paper summarizes the difficulties of sea target detection and common target detection methods, analyzes the principle and general framework of feature detection and several typical feature-based detection methods, and explores the development trend of feature-based detection methods.
Key words:Sea clutter/
Floating small targets/
Radar target detection/
Features extraction/
Feature-based detection
PDF全文下载地址:
https://plugin.sowise.cn/viewpdf/198_4f47f9a7-35a9-4841-91db-bbffa3d8dbda_R20084
