基于时频图像和高次频谱特征的雷达信号识别

doi:10.11959/j.issn.1000-0801.2022024

Abstract

Abstract:

Aiming at improving the accuracy of radar signal recognition under a low signal-to-noise ratio, a radar signal recognition algorithm based both on time-frequency image and high-order spectrum feature was proposed.Firstly, the time-frequency image was obtained by Choi-Williams distribution (CWD) transform, based on which the time-frequency image was preprocessed and the texture features were extracted by gray level co-occurrence matrix (GLCM) in sequence.Meanwhile, the symmetrical holder coefficient was used to extract the high-order spectral features of the signal.Then, the texture features and high-order spectrum features were form a new set of joint feature vectors.Finally, with the proposed feature vector the classification and recognition of radar signals were implemented by a support vector machine.The algorithm was verified on the data set with eight typical radar signals.Experimental results show that the recognition accuracy of different radar signals can achieve higher than 90% when the signal-to-noise ratio is -8 dB.

Key words: radar signal recognition, high order spectrum, Choi-Williams time frequency distribution, support vector machine

CLC Number:

TP393

Shitong LI, Daying QUAN, Zeyu TANG, Yun CHEN, Xiaofeng WANG, Xiaoping JIN. Time-frequency image and high-order spectrum characteristics based radar signal recognition[J]. Telecommunications Science, 2022, 38(2): 84-91.

Figures/Tables 8

References 17

[1]	王俊岭, 黄琰璟 . 基于序列关联的参差信号分选算法[J]. 电子与信息学报, 2021,43(4): 1145-1153.
	WANG J L , HUANG Y J . Stagger pulse repetition interval pulse train deinterleaving algorithm based on sequence association[J]. Journal of Electronics ＆ Information Technology, 2021,43(4): 1145-1153.
[2]	黄颖坤, 金炜东, 葛鹏 ,等. 基于多尺度信息熵的雷达辐射源信号识别[J]. 电子与信息学报, 2019,41(5): 1084-1091.
	HUANG Y K , JIN W D , GE P ,et al. Radar emitter signal identification based on multi-scale information entropy[J]. Journal of Electronics ＆ Information Technology, 2019,41(5): 1084-1091.
[3]	周文辉 . 基于积分特征的雷达信号调制识别[J]. 舰船电子工程, 2021,41(1): 46-49.
	ZHOU W H . Modulation recognition of radar signal based on integral feature[J]. Ship Electronic Engineering, 2021,41(1): 46-49.
[4]	孟凡杰, 唐宏, 王义哲 ,等. 基于时频图像纹理特征的雷达辐射源信号识别[J]. 弹箭与制导学报, 2017,37(3): 152-156.
	MENG F J , TANG H , WANG Y Z ,et al. Radar emitter signal recognition based on texture feature of time-frequency image[J]. Journal of Projectiles,Rockets,Missiles and Guidance, 2017,37(3): 152-156.
[5]	白航, 赵拥军, 胡德秀 ,等. 基于Choi-Williams时频图像特征的雷达辐射源识别[J]. 数据采集与处理, 2012,27(4): 480-485.
	BAI H , ZHAO Y J , HU D X ,et al. Radar emitter recognition based on image feature of Choi-Williams time-frequency distribution[J]. Journal of Data Acquisition and Processing, 2012,27(4): 480-485.
[6]	肖祺, 陈茂洋 . 多维时频图像特征组合的电磁辐射源信号识别[J]. 通信技术, 2020,53(6): 1364-1368.
	XIAO Q , CHEN M Y . Electromagnetic emitter signal recognition based on multidimensional time-frequency image feature combination[J]. Communications Technology, 2020,53(6): 1364-1368.
[7]	刘歌, 张国毅, 汪洪艳 . 基于特征融合的雷达信号脉内调制类型识别[J]. 航天电子对抗, 2016,32(3): 36-41.
	LIU G , ZHANG G Y , WANG H Y . Intra-pulse modulation recognition of radar signal based on features fusion[J]. Aerospace Electronic Warfare, 2016,32(3): 36-41.
[8]	关欣, 朱杭平, 张玉虎 . 基于 FRFT 的雷达辐射源信号特征分析及提取[J]. 探测与控制学报, 2018,40(2): 71-76.
	GUAN X , ZHU H P , ZHANG Y H . Analysis and extraction of radar emitter signal feature based on fractional Fourier transform[J]. Journal of Detection ＆Control, 2018,40(2): 71-76.
[9]	苑军见, 陈世文, 刘智鑫 ,等. 基于高次频谱对称 Holder 系数的雷达信号分选方法[J]. 信号处理, 2020,36(10): 1775-1783.
	YUAN J J , CHEN S W , LIU Z X ,et al. Radar signal sorting method based on the symmetric holder coefficients of high- order spectrum[J]. Journal of Signal Processing, 2020,36(10): 1775-1783.
[10]	杨兴宇, 阮怀林 . 基于时频图像 Zernike 矩特征的欺骗干扰识别[J]. 现代雷达, 2018,40(2): 91-95.
	YANG X Y , RUAN H L . A recognition method of deception jamming based on image Zernike moment feature of time- frequency distribution[J]. Modern Radar, 2018,40(2): 91-95.
[11]	刘燕平, 王冲, 夏海云 . 时频分析在激光雷达中的应用进展[J]. 激光与光电子学进展, 2018,55(12): 68-83.
	LIU Y P , WANG C , XIA H Y . Application progress of time-frequency analysis for lidar[J]. Laser ＆ Optoelectronics Progress, 2018,55(12): 68-83.
[12]	刘歌, 张国毅, 于岩 . 基于随机森林的雷达信号脉内调制识别[J]. 电信科学, 2016,32(5): 69-76.
	LIU G , ZHANG G Y , YU Y . Intra-pulse modulation recognition of radar signal based on random forest[J]. Telecommunications Science, 2016,32(5): 69-76.
[13]	WU F , YANG W X , XIAO L M ,et al. Adaptive Wiener filter and natural noise to eliminate adversarial perturbation[J]. Electronics, 2020,9(10): 1634.
[14]	高程程, 惠晓威 . 基于灰度共生矩阵的纹理特征提取[J]. 计算机系统应用, 2010,19(6): 195-198.
	GAO C C , HUI X W . GLCM-based texture feature extraction[J]. Computer Systems ＆ Applications, 2010,19(6): 195-198.
[15]	王海华, 沈晓峰 . 基于对称Holder系数的雷达辐射源信号特征分析[J]. 空间电子技术, 2010,7(3): 55-59.
	WANG H H , SHEN X F . Feature analysis of radar emitter signals based on symmetrical holder coefficient[J]. Space Electronic Technology, 2010,7(3): 55-59.
[16]	陈昌孝, 何明浩, 徐璟 ,等. 基于模糊函数相像系数的雷达辐射源信号分选[J]. 电波科学学报, 2014,29(2): 260-264.
	CHEN C X , HE M H , XU J ,et al. Radar emitter signal sorting based on resemblance coefficient of ambiguity function[J]. Chinese Journal of Radio Science, 2014,29(2): 260-264.
[17]	王功明, 陈世文, 黄洁 ,等. 基于分数阶 Fourier 变换的雷达信号分选识别[J]. 计算机应用研究, 2020,37(S1): 126-128,131.
	WANG G M , CHEN S W , HUANG J ,et al. Radar signal sorting and recognition based on fractional Fourier transform[J]. Application Research of Computers, 2020,37(S1): 126-128,131.

Metrics

Recommended 0

No Suggested Reading articles found!

Time-frequency image and high-order spectrum characteristics based radar signal recognition

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 17

Related Articles 15

Metrics

Recommended 0

[1]	Yajie LI,Yongli ZHAO,Shoudong LIU,Jie ZHANG. Overview of research on fiber nonlinear equalization algorithm based on artificial intelligence [J]. Telecommunications Science, 2020, 36(3): 61-70.
[2]	Rongfang ZHANG,Dandan XU,Yuanguang WANG,Siyu PAN,Zhengmao LI. Application of machine learning in the fake user identification of IoT [J]. Telecommunications Science, 2019, 35(7): 136-144.
[3]	LEI Yuxiao,LI Gengfeng,HUANG Yuxiong,BIE Zhaohong. Support vector machine based fast Monte Carlo reliability evaluation method for composite power system [J]. Telecommunications Science, 2019, 35(6): 15-24.
[4]	Yaguan QIAN,Xiaohui GUAN,Shuhui WU,NBensheng YU,Dongxiao REN. A novel perturbation attack on SVM by greedy algorithm [J]. Telecommunications Science, 2019, 35(1): 81-89.
[5]	Chuangchuang LI,Guangyue LU,Hanglong WANG. SVM classifier for telecom user arrears based on boundary samples-based under-sampling approaches [J]. Telecommunications Science, 2017, 33(9): 85-91.
[6]	Xiao WANG,Rong ZHANG,Lijun GUO. Robust tampering detection and localization of composite image [J]. Telecommunications Science, 2017, 33(8): 120-129.
[7]	Zhenhong HE. Iris recognition based on generalized Gaussian distribution FDCT_Wrap and FSVM [J]. Telecommunications Science, 2016, 32(7): 126-131.
[8]	Ge LIU,Guoyi ZHANG,Yan YU. Intra-pulse modulation recognition of radar signal based on random forest [J]. Telecommunications Science, 2016, 32(5): 69-78.
[9]	Yaguan QIAN,Xiaohui GUAN,Bensheng YUN,Qiong LOU,Pengfei MA. Internet traffic classification using SVM with flexible feature space [J]. Telecommunications Science, 2016, 32(5): 105-113.
[10]	Zhenhong HE. Iris recognition algorithm based on feature weighting fast discrete Curvelet transform and fuzzy LS-SVM [J]. Telecommunications Science, 2016, 32(3): 92-98.
[11]	Hui Cheng,Jinglong Fang,Daquan Wang,Xingqi Wang. Performance Analysis of Simplification of Hyperplane Support Vector Machine [J]. Telecommunications Science, 2015, 31(8): 78-83.
[12]	Hao Dong,Hua Qu,Jihong Zhao,Liangjun Chen,Huijun Dai. Service-Aware Algorithm Based on DT-KSVM [J]. Telecommunications Science, 2015, 31(11): 67-71.
[13]	Jiyuan Lu,Chenghui Huang,Fang Hou,Bin Li. Image Classification and Annotation Based on Hadoop Cloud Computing Platform [J]. Telecommunications Science, 2014, 30(2): 65-69.
[14]	Ruitong Cao,Xu Cao. A Scheme of QoS Evaluation Based on Support Vector Machine [J]. Telecommunications Science, 2014, 30(2): 123-126.
[15]	Yuan Xu,Huaxiang Lu,Xu Chen. A SVM Based Spectrum Prediction Scheme for Cognitive Radio [J]. Telecommunications Science, 2014, 30(11): 87-92.