3D Detection Under Foggy Weather: The Effective Multi-Sensor Fusion of LiDAR and Radar

Adverse weather conditions are a significant challenge for fully automated driving systems in autonomous vehicles. While radar sensor integration can alleviate some of the adverse effects of weather, the inherent sparsity and altitude discrepancies in radar data remain significant concerns. In response to these challenges, we introduce an innovative sensor fusion method for LiDAR and radar data under foggy weather conditions. This method effectively augments radar data in voxel space. It facilitates the synchronization and complementation of Li-DAR and radar features in the bird's eye view space, thereby achieving high-precision 3D object detection. The effectiveness of this method has been extensively validated through extensive experimentation on the Oxford Radar RobotCar dataset under foggy weather conditions.