Spiking-based Radar Processing for Automotive Applications

A self-driving car relies on the data fusion from three different sensors (Radar, camera and LiDAR) to explore the environment. Traditionally, the LiDAR is employed to map the surroundings, the camera to establish the route and classify the objects, and the radar is in charge of collision avoidance and automatic cruise control. The fusion of these three data sources composes a robust semi-autonomous system. The radar robustness against weather or light condition, and its potential resolution make it a key sensor.

In this discussion group a short overview about the Digital Signal Processor chain of Frequency-Modulated Continuous-Wave (FMCW) radar will be given, which is the technology being used in the state-of-the-art automotive solutions. The discussion group incorporates the exploration of possible spiking-based radar processing to be included either in the normal DSP chain, Simultaneous Localization and Mapping (SLAM), extended functionality through micro-Doppler classifiers or any new idea you might add.

Go to group wiki


Day Time Location
Thu, 25.04.2019 21:00 - 21:30 Panorama Room


Hector Gonzalez
Christian Mayr


yansong chua
Daniel Gehrig
Daniel Gutierrez-Galan
Michael Hopkins
Raphaela Kreiser
chen liu
Qian Liu
Ole Richter
Thorben Schoepe