Enhanced Axle-Based Vehicle Classification Using Angle-Based Micro-Doppler Signature

Abstract

This study introduces an angle-based micro-Doppler analysis using Frequency Modulated Continuous Wave (FMCW) radar tailored for axle-based vehicle classification. The novel approach exploits the signal angle of arrival to separate incoming signals and noise from distinct targets. This is done by analysing the phase difference of a dual antenna radar system based on the time-frequency representation of the radar beat signal. Vehicles driving side by side can now be discriminated. Multipath signals and clutter are more easily identified and filtered out. This paper extends the use of radar systems for non-invasive axle-based vehicle classification by improving the estimation of vehicle features. The method’s effectiveness is demonstrated using real traffic data on vehicle classification performance.