基于MeanShift的短波跳频信号快速盲检测

doi:10.11959/j.issn.1000-436x.2022118

通信学报 ›› 2022, Vol. 43 ›› Issue (6): 200-210.doi: 10.11959/j.issn.1000-436x.2022118

基于MeanShift的短波跳频信号快速盲检测

朱政宇¹^,²^,³, 林宇¹, 王梓晅¹, 巩克现¹, 陈鹏飞¹, 王忠勇¹, 梁静¹^,³

¹ 郑州大学电气与信息工程学院，河南郑州 450001
² 郑州大学电子材料与系统国际联合研究中心，河南郑州 450001
³ 河南省智能网络和数据分析国际联合实验室，河南郑州 450001

修回日期:2022-05-24 出版日期:2022-06-01 发布日期:2022-06-01
作者简介:朱政宇（1988- ），男，河南周口人，博士，郑州大学副教授，主要研究方向为无线通信与信号处理、智能反射表面技术、物理层安全技术等
林宇（1997- ），男，福建莆田人，郑州大学硕士生，主要研究方向为短波信号处理
王梓晅（1998- ），男，河南周口人，郑州大学博士生，主要研究方向为通信信号处理、多源信息融合等
巩克现（1976- ），男，山东泰安人，博士，郑州大学教授、博士生导师，主要研究方向为无线通信信号分析与处理、信道编码、无线接入、目标监测及电子对抗等
陈鹏飞（1998- ），男，河南南阳人，郑州大学硕士生，主要研究方向为深度学习、短波协议识别
王忠勇（1965- ），男，江西遂川人，博士，郑州大学教授、博士生导师，主要研究方向为通信信号处理、嵌入式系统等
梁静（1981- ），女，河南兰考人，博士，郑州大学教授、博士生导师，主要研究方向为演化计算的研究及应用等
基金资助:
国家重点研发计划基金资助项目(2019QY0302);国家重点研发计划基金资助项目(2019YFB1803200);国家自然科学基金资助项目(61922072);国家自然科学基金资助项目(61901417);中国博士后科学基金资助项目(2020M682345);河南省博士后经费资助项目(202001015);河南省高校科技创新人才支持计划资助项目(23HASTIT020)

Fast blind detection of short-wave frequency hopping signal based on MeanShift

Zhengyu ZHU¹^,²^,³, Yu LIN¹, Zixuan WANG¹, Kexian GONG¹, Pengfei CHEN¹, Zhongyong WANG¹, Jing LIANG¹^,³

¹ School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
² National Center for International Joint Research of Electronic Materials and Systems, Zhengzhou University, Zhengzhou 450001, China
³ Joint International Laboratory of Intelligent Network and Data Analysis in Henan Province, Zhengzhou 450001, China

Revised:2022-05-24 Online:2022-06-01 Published:2022-06-01
Supported by:
The National Key Research and Development Program of China(2019QY0302);The National Key Research and Development Program of China(2019YFB1803200);The National Natural Science Foundation of China(61922072);The National Natural Science Foundation of China(61901417);China Postdoctoral Science Foundation Funded Project(2020M682345);Henan Postdoctoral Foundation Funded Project(202001015);Program for Science and Technology Innovation Talents in Universities of Henan Province(23HASTIT020)

摘要/Abstract

摘要：

在复杂的短波信道环境下，为了降低各种干扰信号和噪声对跳频信号的影响，实现低信噪比下跳频信号盲检测，结合时频分析技术，提出一种基于 MeanShift 算法的连通域标记跳频信号快速盲检测算法。首先，对信道环境灰度时频图进行二次灰度形态学滤波得到二值化时频图。其次，通过连通域标记算法，计算信号最大持续时长。再次，利用 MeanShift 算法对信号最大持续时长进行聚类分析。最后，结合自适应双门限对聚类结果进行二次判决。仿真结果表明，在无任何先验信息的情况下，所提算法能够在低信噪比下快速分离各种干扰信号与尖锐噪声，实现跳频信号快速盲检测，检测概率较高，在短波信道环境下抗干扰能力较强，计算复杂度较低，具有较高的工程实用价值。

关键词: 连通域标记, 跳频信号, 快速盲检测, MeanShift, 时频分析

Abstract:

In the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly, the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly, the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then, the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally, the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio, and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability, strong anti-interference ability in short-wave channel environment, low computational complexity and high engineering practical value.

Key words: connected domain labeling, frequency hopping signal, fast blind detection, MeanShift, time-frequency analysis

中图分类号:

TN92

朱政宇, 林宇, 王梓晅, 巩克现, 陈鹏飞, 王忠勇, 梁静. 基于MeanShift的短波跳频信号快速盲检测[J]. 通信学报, 2022, 43(6): 200-210.

Zhengyu ZHU, Yu LIN, Zixuan WANG, Kexian GONG, Pengfei CHEN, Zhongyong WANG, Jing LIANG. Fast blind detection of short-wave frequency hopping signal based on MeanShift[J]. Journal on Communications, 2022, 43(6): 200-210.

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参考文献 27

[1]	贾宏雷, 江桦 . 基于形态学处理的短波跳频信号宽带时频检测算法[J]. 信息工程大学学报, 2013,14(2): 173-179.
	JIA H L , JIANG H . Wideband time-frequency detection algorithm of short-wave frequency hopping signals based on morphology processing[J]. Journal of Information Engineering University, 2013,14(2): 173-179.
[2]	高潘, 胡世安, 吴钦 . 一种基于频谱能量统计的短波信号检测算法[J]. 数字技术与应用, 2013(10): 124-125.
	GAO P , HU S A , WU Y . A short wave signal detection algorithm based on spectrum energy statistics[J]. Digital technology and Application, 2013(10): 124-125.
[3]	吉磊, 樊小琴 . 基于形态滤波功率谱分析的短波信号检测技术[J]. 通信技术, 2018,51(7): 1561-1565.
	JI L , FAN X Q . Short-wave signal detection technology based on morphological filtering power spectrum analysis[J]. Communications Technology, 2018,51(7): 1561-1565.
[4]	李波 . 基于形态学预处理的短波猝发信号检测算法[J]. 现代电子技术, 2015,38(9): 32-34.
	LI B . Shortwave burst signal detection algorithm based on morphology pre-processing[J]. Modern Electronics Technique, 2015,38(9): 32-34.
[5]	布刚刚, 罗明 . 基于数字信道化的跳频信号频率测量研究[J]. 舰船电子对抗, 2015,38(1): 62-64.
	BU G G , LUO M . Frequency measurement study of frequency hopping signal based on digital channelization[J]. Shipboard Electronic Countermeasure, 2015,38(1): 62-64.
[6]	张东伟, 郭英, 霍文俊 ,等. 一种改进的跳频信号信道化检测方法[J]. 火力与指挥控制, 2012,37(8): 58-61,65.
	ZHANG D W , GUO Y , HUO W J ,et al. An improved channelized detection mothod of frequencyhopping signals[J]. Fire Control ＆Command Control, 2012,37(8): 58-61,65.
[7]	吕乐群, 易云清, 卢圆圆 . 基于重叠滑窗时频分析的跳频信号检测技术[J]. 电子信息对抗技术, 2020,35(2): 25-29,88.
	LV L Q , YI Y Q , LU Y Y . Detection of short-wave frequency hopping signal based on overlapped-sliding time-frequency analysis[J]. Electronic Information Warfare Technology, 2020,35(2): 25-29,88.
[8]	陈增茂, 程功, 孙志国 ,等. 基于短时傅里叶变换的跳频信号频谱感知性能分析[J]. 哈尔滨工程大学学报, 2021,42(6): 902-907.
	CHEN Z M , CHENG G , SUN Z G ,et al. Performance analysis of spectrum sensing of frequency-hopping signals under fading channels[J]. Journal of Harbin Engineering University, 2021,42(6): 902-907.
[9]	LI A , HUAN H , TAO R ,et al. Implementation of mixing sequence optimized modulated wideband converter for ultra-wideband frequency hopping signals detection[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020,56(6): 4698-4710.
[10]	李硕, 李天昀 . 短波信道下的跳频信号检测[J]. 电子学报, 2019,47(3): 623-629.
	LI S , LI T Y . Frequency hopping signal detection over the short-wave channel[J]. Acta Electronica Sinica, 2019,47(3): 623-629.
[11]	张盛魁, 姚志成, 范志良 ,等. 基于局部自适应阈值的跳频信号提取和检测[J]. 电光与控制, 2020,27(1): 68-72.
	ZHANG S K , YAO Z C , FAN Z L ,et al. Frequency hopping signal extraction and detection based on local adaptive threshold[J]. Electronics Optics ＆ Control, 2020,27(1): 68-72.
[12]	LEE K G , OH S J . Detection of frequency-hopping signals with deep learning[J]. IEEE Communications Letters, 2020,24(5): 1042-1046.
[13]	LEE K G , OH S J . Detection of fast frequency-hopping signals using dirty template in the frequency domain[J]. IEEE Wireless Communications Letters, 2019,8(1): 281-284.
[14]	LIU F , MARCELLIN M W , GOODMAN N A ,et al. Compressive sampling for detection of frequency-hopping spread spectrum signals[J]. IEEE Transactions on Signal Processing, 2016,64(21): 5513-5524.
[15]	张萌, 王文, 任俊星 ,等. 基于 HOG-SVM 的跳频信号检测识别算法[J]. 信息安全学报, 2020,5(3): 62-77.
	ZHANG M , WANG W , REN J X ,et al. Detection and recognition algorithm for frequency hopping signals based on HOG-SVM[J]. Journal of Cyber Security, 2020,5(3): 62-77.
[16]	东润泽, 郭英, 于欣永 ,等. 基于稀疏重构的跳频信号检测方法[J]. 空军工程大学学报(自然科学版), 2018,19(3): 77-82.
	DONG R Z , GUO Y , YU X Y ,et al. A frequency hopping signal detection method based on sparse reconstruction[J]. Journal of Air Force Engineering University (Natural Science Edition), 2018,19(3): 77-82.
[17]	罗巧 . 低信噪下跳频信号的检测与提取的研究[D]. 成都:电子科技大学, 2018.
	LUO Q . Research on detection and extraction of frequency hopping signal with low SNR[D]. Chengdu:University of Electronic Science and Technology of China, 2018.
[18]	刘旭波 . 基于功率谱分段对消算法的跳频信号检测[J]. 自动化技术与应用, 2017,36(11): 69-73.
	LIU X B . Frequency hopping signal detection based on power spectrum cancellation algorithm[J]. Techniques of Automation and Applications, 2017,36(11): 69-73.
[19]	刘佳敏, 赵知劲, 曹越飞 ,等. 基于时频分析的多跳频信号盲检测[J]. 信号处理, 2021,37(5): 763-771.
	LIU J M , ZHAO Z J , CAO Y F ,et al. Blind detection of multi-frequency hopping signals based on time-frequency analysis[J]. Journal of Signal Processing, 2021,37(5): 763-771.
[20]	古培, 王斌 . 基于二次灰度形态学滤波的跳频信号盲检测[J]. 信息工程大学学报, 2015,16(1): 79-83,128.
	GU P , WANG B . Blind detection method of FH signals based on twice gray-level morphological filtering[J]. Journal of Information Engineering University, 2015,16(1): 79-83,128.
[21]	侯范, 姚志成, 杨剑 ,等. 一种基于 K-Means 聚类的跳频信号快速检测方法[J]. 电讯技术, 2022,62(2): 199-205.
	HOU F , YAO Z C , YANG J ,et al. A fast detection method of frequency hopping signal based on K-Means clustering[J]. Telecommunication Engineering, 2022,62(2): 199-205.
[22]	YE J Q , ZOU J , GAO J ,et al. A new frequency hopping signal detection of civil UAV based on improved K-Means clustering algorithm[J]. IEEE Access, 2021,9: 53190-53204.
[23]	李红光, 郭英, 齐子森 ,等. 复杂电磁环境下多跳频信号盲检测[J]. 华中科技大学学报(自然科学版), 2020,48(7): 13-19.
	LI H G , GUO Y , QI Z S ,et al. Blind detection of multi-frequency hopping signals under complex electromagnetic environment[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2020,48(7): 13-19.
[24]	吕晨杰, 王斌 . 采用纹理特征的跳频信号盲检测算法[J]. 信号处理, 2015,31(4): 453-460.
	LV C J , WANG B . Blind detection algorithm for frequency hopping signals using texture feature[J]. Journal of Signal Processing, 2015,31(4): 453-460.
[25]	郑洋, 陈西豪, 朱锐 . 改进的最优小波基选取方法与跳频信号检测研究[J]. 火力与指挥控制, 2019,44(5): 102-106.
	ZHENG Y , CHEN X H , ZHU R . Research on improved optimal wavelet base selection method and frequency hopping signal detection[J]. Fire Control ＆ Command Control, 2019,44(5): 102-106.
[26]	XIAO Z L , YAN Z Y . Radar emitter identification based on novel time-frequency spectrum and convolutional neural network[J]. IEEE Communications Letters, 2021,25(8): 2634-2638.
[27]	GUO P C , LIU Z , WANG J J . Radar group target recognition based on HRRPs and weighted mean shift clustering[J]. Journal of Systems Engineering and Electronics, 2020,31(6): 1152-1159.

算法	时频分析	预处理	数据集个数	聚类分析
本文算法	MN	MN	n	O(n ²d₁)
文献[21]算法	MN	MN	N	O(kNd ₂)
文献[23]算法	(MN)²	MN	2n	O(k2nd ₃)

基于MeanShift的短波跳频信号快速盲检测

Fast blind detection of short-wave frequency hopping signal based on MeanShift

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