Automotive-Radar, UAV and Environment Perception

The Automotive Radar, UAV, and Environment Perception research group addresses the complete processing chain of radar-based perception systems. We work on novel system concepts, radar measurement and simulation setups and advanced signal processing algorithms.

FMCW Radar Processing

The group focuses on automotive FMCW radar processing for automated driving, covering object detection and classification, real-time processing, and integration into modern vehicle platforms.

SAR-Processing

We research radar-based environment perception to create high-quality radar maps, focusing on occupancy gridmapping and automotive SAR in front- and side-looking configurations.

Radar Networks

To advance cooperative perception, we investigate coherent and non-coherent radar networks as well as UAV-based radar sensing, enabling distributed sensing for vehicles and infrastructure.

Testing Platforms

We validate our developed algorithms on our test platforms enabling real-world radar raw data acquisition, combined with high-quality, temporally and spatially synchronized reference data.

Radar Simulation

Complementing extensive real-world measurements, we use realistic radar simulations to accelerate system design, validate signal processing methods, and develop AI-based radar algorithms.