Automatic radar target recognition of objects falling on railway tracks

被引:9
作者
Mroue, A. [1 ,2 ]
Heddebaut, M. [1 ,2 ]
Elbahhar, F. [1 ,2 ]
Rivenq, A. [1 ,3 ,4 ]
Rouvaen, J-M [1 ,3 ,4 ]
机构
[1] Univ Lille Nord France, F-59000 Lille, France
[2] IFSTTAR, LEOST, F-59666 Villeneuve Dascq, France
[3] UVHC, IEMN DOAE, F-59313 Valenciennes, France
[4] CNRS, UMR 8520, F-59650 Villeneuve Dascq, France
关键词
UWB radar; detection/identification; discrimination; singularity expansion method (SEM); complex natural resonance (CNR); OF-FUNCTION METHOD; TRANSIENT-RESPONSE; EXTRACTING POLES; MATRIX PENCIL; IDENTIFICATION; FREQUENCIES; PARAMETERS; SINUSOIDS; SYSTEM; NOISE;
D O I
10.1088/0957-0233/23/2/025401
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents an automatic radar target recognition procedure based on complex resonances using the signals provided by ultra-wideband radar. This procedure is dedicated to detection and identification of objects lying on railway tracks. For an efficient complex resonance extraction, a comparison between several pole extraction methods is illustrated. Therefore, preprocessing methods are presented aiming to remove most of the erroneous poles interfering with the discrimination scheme. Once physical poles are determined, a specific discrimination technique is introduced based on the Euclidean distances. Both simulation and experimental results are depicted showing an efficient discrimination of different targets including guided transport passengers.
引用
收藏
页数:10
相关论文
共 49 条
[31]   Robust Automatic Target Recognition via HRRP Sequence Based on Scatterer Matching [J].
Jiang, Yuan ;
Li, Yang ;
Cai, Jinjian ;
Wang, Yanhua ;
Xu, Jia .
SENSORS, 2018, 18 (02)
[32]   Multi-View Automatic Target Recognition using Joint Sparse Representation [J].
Zhang, Haichao ;
Nasrabadi, Nasser M. ;
Zhang, Yanning ;
Huang, Thomas S. .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2012, 48 (03) :2481-2497
[33]   Automatic target recognition of moving target based on empirical mode decomposition and genetic algorithm support vector machine [J].
Zhang Jun ;
Ou Jian-ping ;
Zhan Rong-hui .
JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2015, 22 (04) :1389-1396
[34]   Automatic Recognition of Pole-Like Objects from Mobile Laser Scanning Point Clouds [J].
Shi, Zhenwei ;
Kang, Zhizhong ;
Lin, Yi ;
Liu, Yu ;
Chen, Wei .
REMOTE SENSING, 2018, 10 (12)
[35]   Adaptive soft threshold transformer for radar high-resolution range profile target recognition [J].
Chen, Siyu ;
Huang, Xiaohong ;
Xu, Weibo .
IET RADAR SONAR AND NAVIGATION, 2024, 18 (08) :1260-1273
[36]   Numerically Efficient Determination of the Optimal Threshold in Natural Frequency-Based Radar Target Recognition [J].
Lee, Joon-Ho ;
Moon, Hyun-Jin ;
Jeong, So-Hee .
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2014, 62 (11) :5889-5894
[37]   Radar Target Recognition by Frequency-Diversity RCS Together with Kernel Scatter Difference Discrimination [J].
Lee, Kun-Chou .
PROGRESS IN ELECTROMAGNETICS RESEARCH M, 2019, 87 :137-145
[38]   Pruning Support Vector Data Description Method for HRRP-Based Radar Target Recognition [J].
Guo, Yu ;
Xiao, Huaitie .
PROCEEDINGS OF 2016 9TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1, 2016, :330-333
[39]   Automatic Detection and Classification of Buried Objects Using Ground-Penetrating Radar for Counter-Improvised Explosive Devices [J].
Chantasen, Nattawat ;
Boonpoonga, Akkarat ;
Burintramart, Santana ;
Athikulwongse, Krit ;
Akkaraekthalin, Prayoot .
RADIO SCIENCE, 2018, 53 (02) :210-227
[40]   Radar target recognition based on fuzzy optimal transformation using high-resolution range profile [J].
Zhou, Daiying ;
Shen, Xiaofeng ;
Yang, Wanlin .
PATTERN RECOGNITION LETTERS, 2013, 34 (03) :256-264