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Machine Learning Based Object Classification and Identification Scheme Using an Embedded Millimeter-Wave Radar Sensor

Homa Arab, Iman Ghaffari, Lydia Chioukh, Serioja Tatu and Steven Dufour

Article (2021)

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A target’s movements and radar cross sections are the key parameters to consider when designing a radar sensor for a given application. This paper shows the feasibility and effectiveness of using 24 GHz radar built-in low-noise microwave amplifiers for detecting an object. For this purpose a supervised machine learning model (SVM) is trained using the recorded data to classify the targets based on their cross sections into four categories. The trained classifiers were used to classify the objects with varying distances from the receiver. The SVM classification is also compared with three methods based on binary classification: a one-against-all classification, a one-against-one classification, and a directed acyclic graph SVM. The level of accuracy is approximately 96.6%, and an F1-score of 96.5% is achieved using the one-against-one SVM method with an RFB kernel. The proposed contactless radar in combination with an SVM algorithm can be used to detect and categorize a target in real time without a signal processing toolbox.

Uncontrolled Keywords

doppler frequency; in-phase/quadrature demodulator; machine learning; millimeter-wave; multi-class SVMs; metronome; radar cross section (RCS); wavelet scalogram

Subjects: 2800 Artificial intelligence > 2800 Artificial intelligence (Computer vision, see 2603)
Department: Non applicable
Funders: Fonds de recherche du Quebec—Nature et technologies (FRQNT)
PolyPublie URL: https://publications.polymtl.ca/9435/
Journal Title: Sensors (vol. 21, no. 13)
Publisher: MDPI
DOI: 10.3390/s21134291
Official URL: https://doi.org/10.3390/s21134291
Date Deposited: 07 Sep 2023 10:21
Last Modified: 06 Apr 2024 13:00
Cite in APA 7: Arab, H., Ghaffari, I., Chioukh, L., Tatu, S., & Dufour, S. (2021). Machine Learning Based Object Classification and Identification Scheme Using an Embedded Millimeter-Wave Radar Sensor. Sensors, 21(13), 4291 (12 pages). https://doi.org/10.3390/s21134291


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