mmTracking: A DL-Based mmWave RADAR Data Processing Algorithm for Indoor People Tracking
Year: 2025
Type: article
Abstract: Locating and tracking targets in indoor environments is a challenging field of research. The complexity and variability of the environment limit the suitability of many technologies for this application. In this context, mmWave frequency modulated continuous wave (FMCW) radars can prove to be valuable sensors when combined with deep learning (DL) techniques, in order to extend performance in target locating and tracking. This paper presents an original approach to locate and track moving targets in indoor environments, based on a YOLOv3 deep learning network that can be applied to radar data. To quantify the performance of the proposed method, here namedmmTracking, tests were designed in accordance with the ISO/IEC 18305:2016 reference standard. The results show a mean error in localization of 0.39 m with a variance of 0.01 m2, and a root mean square error (RMSE) in the tracking of 0.40 m.
Source: IEEE Sensors Journal
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W4416010476