基于自组织神经网络的EVD杂波抑制算法

doi:10.19665/j.issn1001-2400.20240602

Abstract

Abstract:

The subspace decomposition method is a common method for clutter suppression of slow moving targets in strong clutter environment.But the traditional subspace decomposition method has a poor adaptability.The SVD clutter suppression algorithm based on K-means clustering makes up for the above defects,but when the slow-moving target is close to the clutter Doppler or aliasing,the feature set discrimination decreases and the clustering results are unstable.Therefore,an eigenvalue-decomposition(EVD) clutter suppression algorithm based on self-organizing neural networks is proposed,with the differences between targets,clutter and noise analyzed deeply,and the features with high differentiation between slow-moving targets and clutter extracted to construct the feature set.Then,the self-organizing neural network,which is less affected by the initial value and has stable clustering results,is used for clustering,adaptive selection of clutter basis to construct clutter subspace.Finally,the clutter is suppressed by orthotropic subspace projection.Simulation and measured data are used to verify the performance of the algorithm.By combining with the target tracking algorithm,it is further verified that the algorithm has strong robustness and engineering practicability.

Key words: slow-moving target, clutter, eigen value decomposition(EVD), self-organizing neural network

CLC Number:

TN957.51

SHI Jiaqi, YANG Minglei, LIAN Hao, YE Zhou, XU Guanghui. EVD clutter suppression method based on the self-organizing neural network[J].Journal of Xidian University, 2024, 51(5): 46-57.

Figures/Tables 13

References 29

[1]	KRZYSZTOF S, MAREK C, ANNA K, et al. A Study on Using Different Kinds of Continuous-Wave Radars Operating in C-Band for Drone Detection[C]// Proceedings of the 22th International Microwave and Radar Conference(MIKON 2018).Piscataway:IEEE, 2018:521-526.
[2]	闫超, 涂良辉, 王聿豪, 等. 无人机在我国民用领域应用综述[J]. 飞行力学, 2022, 40(3):1-6,12.
	YAN Chao, TU Lianghui, WANG Yvhao, et al. Application of Unmanned Aerial Vehicle in Civil Field in China[J]. Flight Dynamics, 2022, 40(3):1-6,12.
[3]	万新燕. 复杂场景下小型无人机目标检测与跟踪算法研究[D]. 合肥: 中国科学技术大学, 2022.
[4]	杨勇, 王雪松. 基于杂波拖尾分布的雷达无人机检测性能分析[J]. 系统工程与电子技术, 2024, 46(1):113-120. doi: 10.12305/j.issn.1001-506X.2024.01.13
	YANG Yong, WANG Xuesong. Analysis of Radar Detection Performance for UAV Based on Clutter Tail Distribution[J]. Systems Engineering and Electronics, 2024, 46(1):113-120. doi: 10.12305/j.issn.1001-506X.2024.01.13
[5]	申露, 苏洪涛, 汪晋, 等. 基于注意力自相关机制的剩余杂波抑制方法[J]. 西安电子科技大学学报, 2024, 51(01):41-51.
	SHEN Lu, SU Hongtao, WANG Jin, et al. Attention Autocorrelation Mechanism-Based Residual Clutter Suppression Method[J]. Journal of Xidian University, 2024, 51(1):41-51.
[6]	SCHLEHER D C. MTI and Pulsed Doppler Radar with MATLAB[M]. Norwood: Artech House,1991.
[7]	董佳鑫. 雷达低慢小目标检测算法研究[D]. 西安: 西安电子科技大学, 2022.
[8]	李腾伟. X波段天气雷达地杂波滤波技术[D]. 长沙: 国防科技大学, 2016.
[9]	国强, 陈佳甜, 戚连刚, 等. 改进奇异值分解的海杂波抑制算法[J]. 西安电子科技大学学报, 2023, 50(02):188-196.
	GUO Qiang, CHEN Jiatian, QI Liangang, et al. Sea Clutter Suppression Algorithm Based on Improved Singular Value Decomposition[J]. Journal of Xidian University, 2024, 51(1):41-51.
[10]	QING J, YUN T W, WEI J L, et al. Subspace-Based Distributed Target Detection in Compound-Gaussian Clutter[J]. Digital Signal Processing, 2023, 140(9):104141.
[11]	WANG G, XIA X G, ROOT B T, et al. Manoeuvring Target Detection in Over-The-Horizon Radar Using Adaptive Clutter Rejection and Adaptive Chirplet Transform[J]. IEEE Proceedings:Radar,Sonar and Navigation, 2003, 150(4):292-298.
[12]	LU K, LIU X Z, LIU Y T. Ionospheric Decontamination and Sea Clutter Suppression for HF Skywave Radars[J]. IEEE Journal of Oceanic Engineering, 2005, 30(2):455-462.
[13]	CHENG Q, WU X, ZHANG X, et al. A Novel Sea Clutter Suppression Method Based On SVD‐FRFT At Low Signal‐to‐Clutter Ratio[J]. Electronics Letters, 2023, 59(14):e12874.
[14]	赵志国, 陈建文, 鲍拯, 等. 一种改进的OTHR自适应海杂波抑制方法[J]. 系统工程与电子技术, 2012, 34(5):909-914.
	ZHAO Zhiguo, CHEN Jianwen, BAO Zheng, et al. Modified Adaptive Ocean Clutter Suppression Approach In OTHR[J]. Systems Engineering and Electronics, 2012, 34(5):909-914. doi: 10.3969/j.issn.1001-506X.2012.05.10
[15]	RIAZ M M, GHAFOOR A. Through-Wall Image Enhancement Based on Singular Value Decomposition[J]. International Journal of Antennas and Propagation, 2012, 2012(4):175-195.
[16]	CHEN X, XUE S J, FENG D, et al. A New Wall Clutter Reduction Strategy for Through Wall Radar Imaging[C]// Proceedings of the 12th International Conference on Signal Processing(ICSP 2014).Piscataway:IEEE, 2014:2102-2105.
[17]	吴琳拥, 毛谨, 白渭雄. 基于奇异值分解的雷达微小目标检测方法[J]. 电子科技大学学报, 2019, 48(3):326-330.
	WU Linyong, MAO Jin, BAI Weixiong. Radar Small Target Detection Based on Singular Value Decomposition Method[J]. Journal of University of Electronic Science and Technology of China, 2019, 48(3):326-330.
[18]	黄凤青, 郑霖, 杨超, 等. 基于K-均值聚类的SVD杂波抑制算法[J]. 雷达科学与技术, 2020, 18(6):611-617.
	HUANG Fengqing, ZHENG Lin, YANG Chao, et al. SVD Clutter Suppression Method Based on K-Means Clustering[J]. Radar Science and Technology, 2020, 18(6):611-617.
[19]	DUDA R O, HART P C. Pattern Classification and Scene Analysis[M]. New York: John Wiley and Sons,1973.
[20]	BAI L L, SONG Z R, BAO H J, et al. K-Means Clustering Based on Improved Quantum Particle Swarm Optimization Algorithm[C]// Proceedings of the 13th International Conference on Advanced Computational Intelligence(ICACI 2021).Piscataway:IEEE 2021:140-145.
[21]	HSU C C. Generalizing Self-Organizing Map for Categorical Data[J]. IEEE Transactions on Neural Networks, 2006, 17(2):294-304.
[22]	张良, 保铮, 廖桂生. 基于特征空间的降维STAP方法比较研究[J]. 电子学报, 2000, 8(9):27-30.
	ZHANG Liang, BAO Zheng, LIAO Guisheng. A Comparative Study of Eigenspace-based Rank-reduced STAP Methods[J]. Chinese Journal of Electronics, 28(9):27-30.
[23]	DEMENE C, DEFFIEUX T, PERNOT M, et al. Spatiotemporal Clutter Filtering of Ultrafast Ultrasound Data Highly Increases Doppler and Ultrasound Sensitivity[J]. IEEE Transactions on Medical Imaging, 2015, 34(11):2271-2285.
[24]	GUO K S, ZHENG X, SHI S H, et al. A Low-Slow-Small Target Detection Method for Offshore Radar Based on GPU[C]// Proceedings of the 2th China International SAR Symposium(CISS 2021).Piscataway:IEEE, 2021:1-4.
[25]	徐步云, 倪禾. 自组织神经网络和K-means聚类算法的比较分析[J]. 新型工业化, 2014(7):63-69.
	XU Buyun, NI He. Comparative Analysis of SOM and K-Means Clustering[J]. The Journal of New Industrialization, 2014(7):63-69.
[26]	LUO J, QIU H B, ZHOU Z, et al. MFR Working Mode Recognition Method Based on SOM Clustering Smoothing Graph Signal Generation[J]. Journal of Guilin University of Electronic Technology, 2023, 43(2):120-127.
[27]	FLORA G, SONIA C, LUCA D, et al. Changes in the Eruptive Style of Stromboli Volcano before the 2019 Paroxysmal Phase Discovered through SOM Clustering of Seismo-Acoustic Features Compared with Camera Images and GB In SAR Data[J]. Remote Sensing, 2022, 14(5):1287.
[28]	JING J S, EN LW, HAO C, et al. SAR Image Segmentation Method Based on SOM Neural Network Algorithm[C]// Proceedings of the 7th International Symposium on Advances in Electrical,Electronics,and Computer Engineering(ISAEECE 2022).Piscataway:IEEE, 2022:1229445-1-1229445-6.
[29]	TIVIVE F, BOUZERDOUM A, AMIN M G. A Subspace Projection Approach for Wall Clutter Mitigation in Through the Wall Radar Imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4):2018-2122.

参数	数值
信号带宽/MHz	20
载波频率/GHz	16
脉冲重复频率/μs	690
采样频率/MHz	5
脉冲积累数目	64

杂波抑制技术	改善因子(IF)/dB
去除第1个子空间	1.93
去除前2个子空间	3.67
去除前3个子空间	5.89
去除前4个子空间	6.72
去除前5个子空间	10.83
去除前15个子空间	-7.54
文献[8]中算法	7.67
文献[17]中算法	8.45
文献[18]中算法(1)	7.52
文献[18]中算法(2)	10.21
文中所提算法	13.20

杂波抑制技术	改善因子(IF)/dB
去除前5个子空间	5.67
去除前15个子空间	-5.54
文献[8]中算法	7.79
文献[17]中算法	8.43
文献[18]中算法(1)	7.52
文献[18]中算法(2)	3.21
文中所提算法	14.20

参数	数值
信号带宽/MHz	20
载波频率/GHz	16
脉冲重复频率/μs	690
采样频率/MHz	5

杂波抑制技术	改善因子(IF)/dB
传统子空间方法	6.45
文献[8]中算法	5.36
文献[17]中算法	11.36
文献[18]中算法(1)	8.08
文献[18]中算法(2)	9.71
文中所提算法	15.29

EVD clutter suppression method based on the self-organizing neural network

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Figures/Tables 13

References 29

Related Articles 15

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杂波抑制技术	单帧时间/s	数据处理时间/s
传统子空间方法	0.90	4.70
文献[8]中算法	0.98	4.73
文献[17]中算法	0.94	4.60
文献[18]中算法	1.20	4.68
文中所提算法	1.35	4.42

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