In this work, the authors present results for classification of different classes of targets (car,
single and multiple people, bicycle) using automotive radar data and different neural …

This work studies the feasibility of using backscatter-modulated tags to introduce false
information into a signal received by a frequency-modulated continuous-wave (FMCW) …

In urban areas, pedestrians are the road users category that is the most exposed to road
accident fatalities. In this context, the present article proposes a totally new architecture …

Pedestrian trajectory perception is always a challenging task for autonomous urban driving
since the weak echoes from pedestrians may be masked by strong background clutters, for …

In recent years, there has been a significant increase in the number of collisions between
vehicles and vulnerable road users such as pedestrians, cyclists, road workers and more …

Robust pedestrian trajectory-tracking is an essential prerequisite to traffic accident
prevention. However, it is a challenging task in urban autonomous driving, since the weak …

This work asses a way to improve the detection of pedestrians, workers or cyclists, but also
other static elements on the road. These elements due to its low radar cross-section can be …

Moving target classification is an essential ingredient to avoid accidents in autonomous
driving systems. Recently, 77GHz automotive frequency modulated continuous wave …

Due to the small radar cross Section (RCS), pedestrians are typical low-observable traffic
participants for radar-based automotive perception systems. The early detection and …

The widespread of automotive radars leads to increase of mutual interference, which in turn
degrades road safety. The effect of mutual interference with a focus on detection of …