基于改进Dijkstra算法与时频域滤波的雷达目标识别

doi:10.12305/j.issn.1001-506X.2022.10.12

Abstract

Abstract:

An identification method of radar targets based on improved Dijkstra algorithm with time-frequency domain filtering is proposed to solve the problem that the accuracy of micro-Doppler feature extraction of radar targets in the middle of the trajectory is not high, resulting in low target recognition rates. The improved Dijkstra algorithm is used for extracting the instantaneous Doppler features of the strongest component in the multi-component echo signal. Then the strongest component is filtered through the time-frequency domain filter. So the instantaneous Doppler features of the multi-component signal can be extracted in proper sequence, and features are applied to identify radar targets in the middle of the trajectory. The simulation results demonstrate that this method is suitable for a variety of micro-motion forms, the micro-Doppler features of the echo signal have higher accuracy, and the average recognition rate of radar targets in the middle of the trajectory is increased effectively.

Key words: radar automatic target recognition (RATR), micro-Doppler, Dijkstra algorithm, time-frequency domain filtering

CLC Number:

TN957

Caiyun WANG, Chen YAO, Yida WU, Jianing WANG, Xiaofei LI, Panpan HUANG. Radar target recognition based on improved Dijkstra algorithm with time-frequency domain filtering[J]. Systems Engineering and Electronics, 2022, 44(10): 3090-3095.

Figures/Tables 6

Table 1

Fig.1

Fig.2

Table 2

Fig.3

Fig.4

References 23

1	CHEN V C. Analysis of radar micro-Doppler signature with time-frequency transform[C]//Proc. of the IEEE Workshop on Statistica Signaland Array Processing, 2000: 463-466.
2	JIAN M, LU Z Z, CHEN V C. Experimental study on radar Micro-Doppler signatures of unmanned aerial vehicles[C]//Proc. of the IEEE Radar Conference, 2017: 854-857.
3	王义哲, 冯存前, 李靖卿, 等. 弹道中段多目标微多普勒分离方法[J]. 北京航空航天大学学报, 2017, 43 (1): 113- 120.
	WANG Y Z , FENG C Q , LI J Q , et al. Micro-Doppler separation method for multi-targets in the middle of the trajectory[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43 (1): 113- 120.
4	邵长宇, 杜兰, 李飞, 等. 基于多目标跟踪的空间锥体目标微多普勒频率提取方法[J]. 电子与信息学报, 2012, 34 (12): 2972- 2977.
	SHAO C Y , DU L , LI F , et al. Micro-Doppler frequency extraction method of space cone target based on multi-target trac-king[J]. Journal of Electronics and Information Technology, 2012, 34 (12): 2972- 2977.
5	SHAO C Y, DU L, HAN X. Multiple target tracking based separation of micro-Doppler signals from coning target[C]//Proc. of the IEEE Radar Conference, 2014: 130-133.
6	李飞, 纠博, 邵长宇, 等. 目标微动参数估计的曲线跟踪算法[J]. 电波科学学报, 2013, 28 (2): 278- 284. 278-284, 295
	LI F , JIU B , SHAO C Y , et al. Curve tracking algorithm for estimating target micro-motion parameters[J]. Chinese Journal of Radio Science, 2013, 28 (2): 278- 284. 278-284, 295
7	KHAN N A , BOASHASH B . Multi-component instantaneous frequency estimation using locally adaptive directional time frequency distributions[J]. International Journal of Adaptive Control & Signal Processing, 2016, 30 (3): 429- 442.
8	王兆云, 张兴敢, 柏业超. 基于微多普勒的锥体目标进动和结构参数估计[J]. 南京大学学报(自然科学), 2014, 50 (2): 148- 153.
	WANG Z Y , ZHANG X G , BO Y C . Precession and structure parameter estimation of cone target based on micro-Doppler[J]. Journal of Nanjing University (Natural Science), 2014, 50 (2): 148- 153.
9	KANG W W, ZHANG Y H, DONG X. Micro-Doppler feature extraction forinter ferometric radar based on Viterbi algorithm and intrinsic chirp component decomposition[C]//Proc. of the 22nd International Microwave and Radar Conference, 2018, 22: 508-511.
10	赵雅琴, 聂雨亭, 吴龙文, 等. 基于脊路跟踪的变分非线性调频模态分解方法[J]. 浙江大学学报(工学版), 2020, 54 (10): 1874- 1882. doi: 10.3785/j.issn.1008-973X.2020.10.002
	ZHAO Y Q , NIE Y T , WU L W , et al. Multi-component signal separation using variational nonlinear chirp mode decomposition based on ridge tracking[J]. Journal of Zhejiang University (Engineering Science Edition), 2020, 54 (10): 1874- 1882. doi: 10.3785/j.issn.1008-973X.2020.10.002
11	CHEN S Q , DONG X J , XING G P , et al. Separation of overlapped nonstationary signals by ridge path regrouping and intrinsic chirp component decomposition[J]. IEEE Sensors Journal, 2017, 17 (18): 5994- 6005. doi: 10.1109/JSEN.2017.2737467
12	CHEN S Q , PENG Z K , YANG Y , et al. Intrinsic chirp component decomposition by using Fourier series representation[J]. Signal Process, 2017, 137, 319- 327. doi: 10.1016/j.sigpro.2017.01.027
13	WANG Y Z , ZHANG Y S , FENG C Q , et al. Micro-Doppler separation of multi-target based on ACO in midcourse[J]. The Journal of Engineering, 2019, 2019 (19): 5967- 5970.
14	陈帅, 冯存前, 许旭光. 基于Viterbi算法和ROMP的多弹道目标分离与特征提取[J]. 火力与指挥控制, 2020, 45 (3): 22- 27.
	CHEN S , FENG C Q , XU X G . Multi-ballistic target separation and feature extraction based on Viterbi and ROMP algorithm[J]. Fire Power and Command Control, 2020, 45 (3): 22- 27.
15	JI J Z , JIANG J X , ALLANN A A , et al. Nutation and geometrical parameters estimation of cone-shaped target based on micro-Doppler effect[J]. Optik International Journal for Light and Electron Optics, 2017, 150, 1- 10.
16	HE S S, ZHOU J X, ZHAO H Z. Estimating the precession angle of ballistic targets in midcourse based on HRRP squence[C]//Proc. of the IEEE Radar Conference, 2008: 1006-1009.
17	MICHAL D , KONATANTY J S , ZBIGNIEW L . Bundling all shortest paths[J]. Discrete Applied Mathematics, 2020, 277 (3): 82- 91.
18	宋泽林. 基于时频域滤波的亮点特征提取及识别研究[D]. 哈尔滨: 哈尔滨工程大学, 2019.
	SONG Z L. Research on highlight feature extraction and recognition based on time frequency domain filtering[D]. Harbin: Harbin Engineering University, 2019.
19	CAI Z H , ZHANG M , WANG J K , et al. A Reassigned bilinear transformation and Gaussian kernel function-based approach for detecting weak targets in sea clutter[J]. International Journal of Remote Sensing, 2016, 37 (23): 5668- 5686.
20	王彩云, 黄盼盼, 李晓飞, 等. 基于AEPSO-SVM算法的雷达HRRP目标识别[J]. 系统工程与电子技术, 2019, 41 (9): 1984- 1989.
	WANG C Y , HUANG P P , LI X F , et al. Radar HRRP target recognition based on AEPSO-SVM algorithm[J]. Systems Engineering and Electronics, 2019, 41 (9): 1984- 1989.
21	TANG W, YU L, WEI Y, et al. Radar target recognition of ballistic missile in complex scene[C]//Proc. of the IEEE International Conference on Signal, Information and Data Processing, 2019.
22	束长勇, 张生俊, 黄沛霖, 等. 基于微多普勒的空间锥体目标微动分类[J]. 北京航空航天大学学报, 2017, 43 (7): 1387- 1394.
	SHU C Y , ZHANG S J , HUANG P L , et al. Micro-motion classification of space cone targets based on micro-Doppler[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43 (7): 1387- 1394.
23	黎湘, 刘永祥, 李康乐. 雷达目标微动特性[M]. 北京: 科学出版社, 2016.
	LI X , LIU Y X , LI K L . Micro-motion characteristics of radar targets[M]. Beijing: Science Press, 2016.

微动形式	φ/(°)	θ/(°)	f_φ/Hz	f_θ/Hz
章动	0~360	5~20	0.3~1.5	0.5~1.5
进动	0~360	5~20	0.3~1.5	-
翻滚	0~360	-	1.5~3.5	0.5~1.5
摆动	0~180	5~20	-	0.5~1.5

微多普勒特征提取算法	识别率				平均识别率
微多普勒特征提取算法	翻滚诱饵	摆动诱饵	章动弹头	进动弹头	平均识别率
Spline插值^[22]	0.845 0	0.835 0	0.775 0	0.875 0	0.832 5
WAFA^[23]	0.835 0	0.800 0	0.895 0	0.785 0	0.828 8
最大峰值算法^[7]	0.845 0	0.825 0	0.865 0	0.790 0	0.831 3
霍夫变换^[8]	0.915 0	0.905 0	0.945 0	0.930 0	0.925 0
维特比算法^[9]	0.940 0	0.920 0	0.950 0	0.935 0	0.936 3
本文算法	0.965 0	0.950 0	0.985 0	0.960 0	0.965 0

[1]	Yiheng ZHOU, Jun YANG, Saiqiang XIA, Mingjiu LYU. Estimation method of micro-motion parameters for rotor targets under flashing [J]. Systems Engineering and Electronics, 2022, 44(1): 54-63.
[2]	Weijie ZHAN, Xianrong WAN, Jianxin YI, Deqiang XIE, Feng CHENG, Yunhua RAO. Experimental study on micro-Doppler effect of target blades in passive radar [J]. Systems Engineering and Electronics, 2021, 43(6): 1468-1476.
[3]	Weiting FENG, Qing LIANG, Jing GU. Micro-motion parameters extraction for rotating targets based on FMCW radar [J]. Systems Engineering and Electronics, 2021, 43(12): 3564-3570.
[4]	Yifan ZHANG, Shuanghui ZHANG, Yongxiang LIU, Feng JING. Radar HRRP sequence target recognition method of attention mechanism based stacked LSTM network [J]. Systems Engineering and Electronics, 2021, 43(10): 2775-2781.
[5]	Yang ZHOU, Daping BI, Aiguo SHEN. Micro-motion target detection algorithm of IRT based large dynamic reflection coefficient [J]. Systems Engineering and Electronics, 2020, 42(9): 1935-1944.
[6]	Wang LU, Yasheng ZHANG, Can XU, Caiyong LIN. HRRP target recognition method based on bispectrum-spectrogram feature and deep convolutional neural network [J]. Systems Engineering and Electronics, 2020, 42(8): 1703-1709.
[7]	LI Jianzhou, LIU Xiangwei, FAN Chaoqun, LIU Lu, QI Yutao. Geometric modeling and scattering characteristics analysis of multi-degree-of-freedom flying targets [J]. Systems Engineering and Electronics, 2019, 41(11): 2401-2407.
[8]	SUN Yuxue, LUO Ying, ZHANG Qun, HU Jian. Time-varying three dimensional imaging for space rotating targets with stepped-frequency chirp signal [J]. Systems Engineering and Electronics, 2018, 40(1): 23-31.
[9]	SHU Changyong, ZHANG Shengjun, HUANG Peilin, JI Jinzu. Characteristic parameters estimation of procession cone#br# target based on micro-Doppler [J]. Systems Engineering and Electronics, 2017, 39(1): 15-20.
[10]	HU Xiaowei, TONG Ningning, He Xingyu, Jiang Dong, WANG Yuchen. Threedimensional imaging of precession targets with unsymmetrical appendixes based on micro-motion parameters estimation [J]. Systems Engineering and Electronics, 2016, 38(3): 501-505.
[11]	SHU Chang-yong, HUANG Pei-lin, JI Jin-zu. Translation compensation and micro-Doppler extraction of the precessional cone target [J]. Systems Engineering and Electronics, 2016, 38(2): 259-264.
[12]	WAN Xian-, SHAO Qi-hong, XIA Peng, DAN Yang-peng. Experimentation on micro-Doppler effect with passive radar based on digital terrestrial multimedia broadcasting [J]. Systems Engineering and Electronics, 2016, 38(11): 2499-2504.
[13]	LI Jing-qing, FENG Cun-qian, ZHANG Dong. Multi-target separation and extraction based on adaptive vision cluster matching [J]. Systems Engineering and Electronics, 2015, 37(9): 1974-1979.
[14]	HU Xiao-wei, TONG Ning-ning, HU Guo-ping, WANG Yu-chen. Multi-ballistic targets resolution based on micro-Doppler [J]. Systems Engineering and Electronics, 2015, 37(8): 1734-1740.
[15]	YANG Qiu, ZHANG Qun, WANG Min, SUN Li. Doppler feature analysis of ship based on airborne narrow band radar [J]. Systems Engineering and Electronics, 2015, 37(12): 2733-2738.

Radar target recognition based on improved Dijkstra algorithm with time-frequency domain filtering

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 23

Related Articles 15

Recommended Articles

Metrics

Comments