Deep Learning Method for Doppler Disambiguation

Marco Braun, Adrian Becker, Mirko Meuter, Simon Roesler, Kevin Kollek, Anton Kummert

Abstract: Velocities measured by radar sensors suffer from ambiguities caused by aliasing effects associated with signal processing. These ambiguities are highly undesired as they affect otherwise very accurate speed measurements. For automotive applications utilizing radar sensors, this means that measured velocities are potentially unreliable which can lead to unsafe conditions for automated driving functionalities. This work presents the first approach to disambiguate radial velocities measured by radar sensors based on Deep Learning methods. By utilizing the presented method, radial velocity estimates can be obtained which are both highly accurate while being reliable as ambiguities are resolved.

External IDs:dblp:conf/iscas/BraunBMRKK24