Cited 2 time in webofscience Cited 3 time in scopus

Doppler-Spectrum Feature-Based Human-Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor

Title
Doppler-Spectrum Feature-Based Human-Vehicle Classification Scheme Using Machine Learning for an FMCW Radar Sensor
Authors
Hyun, EuginJin, YoungSeok
DGIST Authors
Hyun, Eugin; Jin, YoungSeok
Issue Date
2020-04
Citation
Sensors, 20(7)
Type
Article
Article Type
Article
Author Keywords
human detectionFMCW radarrange-Doppler processingradar machine learning
Keywords
Classification decisionFMCW radar sensorsFrequency-modulated continuous wavesFront end modulesReal time data acquisitionSVM(support vector machine)Vehicle classificationRadar measurementBinary treesContinuous wave radarData acquisitionDecision treesDoppler effectFrequency modulationRadar equipmentSpectrum analysisSupport vector machinesVehiclesBinary decision trees
ISSN
1424-8220
Abstract
In this paper, we propose a Doppler-spectrum feature-based human–vehicle classification scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce three novel features referred to as the scattering point count, scattering point difference, and magnitude difference rate features based on the characteristics of the Doppler spectrum in two successive frames. We also use an SVM (support vector machine) and BDT (binary decision tree) for training and validation of the three aforementioned features. We measured the signals using a 24-GHz FMCW radar front-end module and a real-time data acquisition module and extracted three features from a walking human and a moving vehicle in the field. We then repeatedly measured the classification decision rate of the proposed algorithm using the SVM and BDT, finding that the average performance exceeded 99% and 96% for the walking human and the moving vehicle, respectively. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
URI
http://hdl.handle.net/20.500.11750/12044
DOI
10.3390/s20072001
Publisher
MDPI AG
Related Researcher
  • Author Hyun, Eugin  
  • Research Interests Radar system, Radar signal processing, Automotive radar, Surveillance radar, Commercial radar, Defence radar,
Files:
There are no files associated with this item.
Collection:
Division of Automotive Technology1. Journal Articles


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