Radar group target recognition based on HRRPs and weighted mean shift clustering

doi:10.23919/JSEE.2020.000087

Journal of Systems Engineering and Electronics ›› 2020, Vol. 31 ›› Issue (6): 1152-1159.doi: 10.23919/JSEE.2020.000087

• DEFENCE ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Radar group target recognition based on HRRPs and weighted mean shift clustering

Pengcheng GUO^1,², Zheng LIU^1,*(), Jingjing WANG¹

¹ National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
² Xi'an Electronic Engineering Research Institute, Xi’an 710100, China

Received:2019-01-17 Online:2020-12-18 Published:2020-12-29
Contact: Zheng LIU E-mail:lz@xidian.edu.cn
About author:|GUO Pengcheng was born in 1983. He received his M.S. degree in signal and information processing from Xi'an Electronic Engineering Research Institute, Xi’an, China, in 2009, where he has been pursuing his Ph.D. degree in signal processing at the National Laboratory of Radar Signal Processing since 2017. He is also a senior scientist at Xi’an Electronic Engineering Research Institute. His research interests are radar target detection and automatic target recognition. E-mail: guopc206@163.com||LIU Zheng was born in 1964. He received his B.S., M.S. and Ph.D. degrees in 1985, 1991, and 2000, respectively. He is currently a professor, adoctoral director, and the vice director of the National Laboratory of Radar Signal Processing at Xidian University, Xi’an, China. His research interests include the theory and system design of radar signal processing, precision guiding technology, and multi-sensor data fusion. E-mail: lz@xidian.edu.cn||WANG Jingjing was born in 1993. She received her M.S. degree in information countermeasure technology from Xidian University, Xi’an, China, in 2015, where she is currently pursuing her Ph.D. degree in signal processing at the National Laboratory of Radar Signal Processing. Her research interests include radar HRRP target recognition and polarization information processing. E-mail: wangjj0523@163.com

Abstract

Abstract:

When range high-resolution radar is applied to target recognition, it is quite possible for the high-resolution range profiles (HRRPs) of group targets in a beam to overlap, which reduces the target recognition performance of the radar. In this paper, we propose a group target recognition method based on a weighted mean shift (weighted-MS) clustering method. During the training phase, subtarget features are extracted based on the template database, which is established through simulation or data acquisition, and the features are fed to the support vector machine (SVM) classifier to obtain the classifier parameters. In the test phase, the weighted-MS algorithm is exploited to extract the HRRP of each subtarget. Then, the features of the subtarget HRRP are extracted and used as input in the SVM classifier to be recognized. Compared to the traditional group target recognition method, the proposed method has the advantages of requiring only a small amount of computation, setting parameters automatically, and having no requirement for target motion. The experimental results based on the measured data show that the method proposed in this paper has better recognition performance and is more robust against noise than other recognition methods.

Key words: clustering, group target recognition, high resolution range profile (HRRP), mean shift (MS)

Pengcheng GUO, Zheng LIU, Jingjing WANG. Radar group target recognition based on HRRPs and weighted mean shift clustering[J]. Journal of Systems Engineering and Electronics, 2020, 31(6): 1152-1159.

Figures/Tables 9

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References 27

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Target type		Sample size	Length/m	Width/m
Training data	Truck	4500	6.8	2.7
Training data	Car	4500	4.8	1.9
Test data	Truck+Car	520	—	—

Method	Operation time
Weighted-MS	0.793
MS	0.936
DP	1.160
DBSCAN	1.200
K-means	0.850

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Radar group target recognition based on HRRPs and weighted mean shift clustering

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