NDLI: Human–vehicle classification using feature-based SVM in 77-GHz automotive FMCW radar

Content Provider	IET Digital Library
Author	Lee, Seongwook Yoon, Young Jun Lee, Jae Eun Kim, Seong Cheol
Abstract	In this study, a human–vehicle classification using a feature-based support vector machine (SVM) in a 77-GHz automotive frequency modulated continuous wave (FMCW) radar system is proposed. As a classification criterion, the authors use a newly defined parameter called root radar cross section which reflects the reflection characteristics of targets. Based on this parameter, three distinctive signal features are extracted from frequency-domain received FMCW radar signals, and they become classification standards used for the SVM. Finally, through measurement results on the test field, the classification performance of the authors’ proposed method is verified, and the average classification accuracy from a four-fold cross data validation is found to be higher than 90%. In addition, the authors’ proposed classification method is applied to distinguish a pedestrian, a vehicle, and a cyclist in a more practical situation, and it also shows good classification performance.
Starting Page	1589
Ending Page	1596
Page Count	8
ISSN	17518784
Volume Number	11
e-ISSN	17518792
Issue Number	Issue 10, Oct (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/11/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2017.0126
Journal	IET Radar, Sonar & Navigation
Publisher Date	2017-07-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automotive FMCW Radar CW Radar Digital Signal Processing Feature Extraction Feature-based Support Vector Machine FM Radar Four-fold Cross Data Validation Frequency 77 GHz Frequency Domain Analysis Frequency Modulated Continuous Wave Radar System Human-vehicle Classification Knowledge Engineering Technique Mathematical Analysis Radar Equipment Road Traffic Root Radar Cross Section Signal Classification Signal Processing And Detection Support Vector Machine SVM System And Application Traffic Engineering Computing
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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