3D Head Motion Detection Using Millimeter-Wave Doppler Radar

In advanced driver assistance systems to conditional automation systems, monitoring of driver state is vital for predicting the driver's capacity to supervise or maneuver the vehicle in cases of unexpected road events and to facilitate better in-car services. The paper presents a technique that exploits millimeter-wave Doppler radar for 3D head tracking. Identifying the bistatic and monostatic geometry for antennas to detect rotational vs. translational movements, the authors propose the biscattering angle for computing a distinctive feature set to isolate dynamic movements via class memberships. Through data reduction and joint time-frequency analysis, movement boundaries are marked for creation of a simplified, uncorrelated, and highly separable feature set. The authors report movement-prediction accuracy of 92%. This non-invasive and simplified head tracking has the potential to enhance monitoring of driver state in autonomous vehicles and aid intelligent car assistants in guaranteeing seamless and safe journeys.

Keywords

3D motion detection, Bistatic radar, Doppler effect, head movements, STFT, wireless sensing

DOI

10.1109/ACCESS.2020.2973957

Citation

Raja, M, Vali, Z, Palipana, S, Michelson, D G & Sigg, S 2020, '3D Head Motion Detection Using Millimeter-Wave Doppler Radar', IEEE Access, vol. 8, 8998250, pp. 32321-32331. https://doi.org/10.1109/ACCESS.2020.2973957

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202004092804

Collections

[article-cris] Sähkötekniikan korkeakoulu / ELEC

Show all metadata

3D Head Motion Detection Using Millimeter-Wave Doppler Radar

Access rights

URL

Journal Title

Journal ISSN

Volume Title

Authors

Date

Department

Major/Subject

Mcode

Degree programme

Language

Pages

Series

Abstract

Description

Keywords

Other note

DOI

Citation

Permanent link to this item

Collections