一种改进模糊C均值聚类的电离层杂波分类方法

doi:10.19665/j.issn1001-2400.2021.02.005

摘要/Abstract

摘要：

在高频地波超视距雷达系统中,电离层杂波作为一种时变、非均匀、非高斯的复杂杂波,其复杂性导致了单一杂波抑制算法无法有效地抑制电离层杂波。针对不同特性,将复杂的电离层杂波进行分类,可以有效地提升电离层杂波抑制性能。常规的杂波聚类方法由于仅在特征空间进行聚类,分类结果存在空间分布离散化的问题。针对该问题,结合电离层杂波特性与其邻域空间信息,提出了一种基于改进的模糊C均值距离的电离层杂波分类方法,利用仿真数据与高频地波雷达实测数据进行分析。该方法在不降低聚类性能的情况下,具有更符合实际物理意义的聚类结果,并具有更高的分类精度。

关键词: 高频地波超视距雷达, 杂波分类, 电离层杂波, 模糊C均值算法, 半监督聚类

Abstract:

The ionospheric clutter is a time-varying,non-stationary and non-Gaussian complex clutter in the high-frequency surface-wave radar(HFSWR) system and its suppression is a daunting task.Due to the complexity of the ionospheric clutter,the single clutter suppression algorithm cannot suppress the clutter effectively.Classification of the complex ionospheric clutter according to different characteristics can improve the performance of ionospheric clutter suppression significantly.After a complete analysis of the characteristics of ionospheric clutter,this paper proposes an improved ionospheric clutter classification method based on fuzzy C-means clustering.Experimental results show that the proposed method has a better performance than the traditional algorithm in clustering the ionospheric clutter.

Key words: high frequency surface wave radar, clutter classification, ionospheric clutter, fuzzy C-means, semi-supervised clustering

中图分类号:

TN95

周建宇,位寅生,许荣庆. 一种改进模糊C均值聚类的电离层杂波分类方法[J]. 西安电子科技大学学报, 2021, 48(2): 35-41.

ZHOU Jianyu,WEI Yinsheng,XU Rongqing. Improved ionospheric clutter classification method based on fuzzy C-means clustering[J]. Journal of Xidian University, 2021, 48(2): 35-41.

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参考文献 22

[1]	王谦喆, 何召阳, 宋博文, 等. 射频隐身技术研究综述[J]. 电子与信息学报, 2018,40(6):1505-1514.
	WANG Qianzhe, HE Zhaoyang, SONG Bowen, et al. Overview on RF Stealth Technology Research[J]. Journal of Electronics & Information Technology, 2018,40(6):1505-1514.
[2]	CHAN H C, HUNG E K L. An Investigation in Interference Suppression for HF Surface Wave Radar:DREO TR 2000- 028[R]. Ottawa:Defence Research Establishment Ottawa, 1999.
[3]	康勇, 杨子杰, 田建生, 等. 高频地波超视距雷达干扰源及其抗干扰技术综述[C]//第二十届全国电磁兼容学术会议论文集中国通信学会会议论文集. 北京: 中国电子学会电磁兼容分会、中国通信学会电磁兼容委员会, 2010: 216-222.
[4]	李雷. 高频雷达自适应抗干扰技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2007.
[5]	位寅生, 周建宇, 许荣庆. 基于杂波聚类与贪婪策略的电离层杂波智能处理方法[J]. 雷达学报, 2020,9(4):589-607.
	WEI Yinsheng, ZHOU Jianyu, XU Rongqing. Intelligent Suppression Method for Ionospheric Clutter Based on Clustering and Greedy Strategy[J]. Journal of Radars, 2020,9(4):589-607.
[6]	CHAN H C. Characterization of Ionospheric Clutter in HF Surface-Wave Radar:DRDC Ottawa TR 2003-114[R]. Ottawa:Defence Research Establishment Ottawa, 2003.
[7]	田文龙. 基于二维阵的高频地波雷达电离层杂波抑制[D]. 哈尔滨: 哈尔滨工业大学, 2012.
[8]	LI Y, HE M K, ZHANG N. An Ionospheric Clutter Recognition Method Based on Machine Learning[C]//Proceedings of the 2017 IEEE Antennas and Propagation Society International Symposium. Piscataway:IEEE, 2017: 1637-1638.
[9]	RAVAN M, RIDDOLLS R J, ADVE R S. Ionospheric and Auroral Clutter Models for HF Surface Wave and Over-the-Horizon Radar Systems[J]. Radio Science, 2012,47(3):RS3010.
[10]	杨旭光. 高频地波雷达电离层回波机理及应用研究[D]. 哈尔滨: 哈尔滨工业大学, 2019.
[11]	沈伟, 文必洋, 李自立, 等. 高频地波雷达的电离层杂波识别新试验[J]. 电波科学学报, 2008,23(1):1-5.
	SHEN Wei, WEN Biyang, LI Zili, et al. Ionospheric Measurement with HF Ground Wave Radar System[J]. Chinese Journal of Radio Science, 2008,23(1):1-5.
[12]	KNIGHT M F. Ionospheric Scintillation Effects on Global Positioning System Receivers[D]. Adelaide: University of Adelaide, 2000: 9-10.
[13]	吴敏. 高频地波雷达干扰与杂波抑制方法的研究[D]. 武汉: 武汉大学, 2011.
[14]	RAVAN M, RIDDOLLS R J, ADVE R S.. Ionospheric and Auroral Clutter Models for HF Surface Wave and Over-the-Horizon Radar Systems[J]. Radio Science, 2012, 47(3):RS3010.
[15]	周浩, 文必洋, 吴世才. 高频地波雷达中电离层杂波的时频特征[J]. 电波科学学报, 2009,24(3):14-18.
	ZHOU Hao, WEN Biyang, WU Shicai. Time-frequency Characteristics of the Ionospheric Clutters in High-frequency Surface Wave Radars[J]. Chinese Journal of Radio Science, 2009,24(3):14-18.
[16]	周浩, 文必洋. 高频地波雷达中电离层E_s层杂波分析及其抑制[J]. 华中科技大学学报:自然科学版, 2011,39(4):46-49.
	ZHOU Hao, WEN Biyang. Analysis and Suppression of Ionosphere Es Layer Clutters in High-frequency Surface Wave Radars[J]. Journal of Huazhong University of Science and Technology:Natural Science Edition, 2011,39(4):46-49.
[17]	SU Y, WEI Y, XU R, et al. Ionospheric Clutter Suppression Using Wavelet Oblique Projecting Filter[C]//Proceedings of the 2017 IEEE Radar Conference. Piscataway:IEEE, 2017: 1552-1556.
[18]	ZHOU J, LI G, XU R. Ionosphere Clutter Suppression Based on Sparse Space Spectrum Rebuild Beamforming[C]//Proceedings of the 2016 CIE International Conference on Radar. Piscataway:IEEE, 2016: 8059395.
[19]	ZHOU J, WEI Y, XU R. A Clutter Sample Selection-Based Generalized Sidelobe Canceller Algorithm for Ionosphere Clutter Suppression in HFSWR[C]//Proceedings of the 2018 IEEE International Conference on Radar. Piscataway:IEEE, 2018: 8557332.
[20]	张鑫. 基于多维联合的高频雷达杂波及干扰抑制方法研究[D]. 哈尔滨: 哈尔滨工业大学, 2015.
[21]	LI C, JIANG L, LI H, et al. Attribute Weighted Value Difference Metric[C]//Proceedings of the 2013 International Conference on Tools with Artificial Intelligence. Washington:IEEE Computer Society, 2013: 575-580.
[22]	DAVIES D L, BOULDIN D W. A Clustering Separation Measure[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979,1(2):224-227. pmid: 21868852

杂波类型	功率	方向性	空域同质性	距离域相关性	小波图像尺度
能量聚集型强方向性杂波	聚集	集中	同质	相关	与目标相异
点状杂波	聚集	分散	异质	非相关	与目标相似
空域同分布杂波	分散	分散	同质	非相关	与目标相异
距离域相关杂波	分散	分散	异质	相关	与目标相异
类目标杂波	分散	集中	异质	非相关	与目标相似

算法	分类准确率/%			DBI系数
算法	5%样本替换	7%样本替换	10%样本替换	5%样本替换	7%样本替换	10%样本替换
FCM	95.62	94.07	91.42	0.626 7	0.642 3	0.664 8
文中算法	99.64	99.39	99.08	0.644 8	0.647 2	0.691 2