Volume 9 Issue 4
Aug.  2020
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XU Shuwen, BAI Xiaohui, GUO Zixun, et al. Status and prospects of feature-based detection methods for floating targets on the sea surface[J]. Journal of Radars, 2020, 9(4): 684–714. doi: 10.12000/JR20084
Citation: XU Shuwen, BAI Xiaohui, GUO Zixun, et al. Status and prospects of feature-based detection methods for floating targets on the sea surface [J]. Journal of Radars, 2020, 9(4): 684–714. doi: 10.12000/JR20084
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Status and Prospects of Feature-based Detection Methods for Floating Targets on the Sea Surface (in English)

doi: 10.12000/JR20084

  • 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
  • Received Date: 2020-06-25
  • Rev Recd Date: 2020-08-14
    • Available Online: 2020-08-28
  • Publish Date: 2020-09-01
    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.

     

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