2018/07/30 by Hatem Hajri, Mohamed-Cherif Rahal, Hajri, Hatem +1
Computer Science · Engineering · Physics and Astronomy · #Advanced Optical Sensing Technologies #Autonomous Vehicle Technology and Safety #FOS: Computer and information sciences #Performance (cs.PF) #Robotics (cs.RO) #Target Tracking and Data Fusion in Sensor Networks
paper · pdf · doi:10.48550/arxiv.1807.11264
openalex publication_date 2018/07/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
- Both Lidars and Radars are sensors for obstacle detection. While Lidars are\nvery accurate on obstacles positions and less accurate on their velocities,\nRadars are more precise on obstacles velocities and less precise on their\npositions. Sensor fusion between Lidar and Radar aims at improving obstacle\ndetection using advantages of the two sensors. The present paper proposes a\nreal-time Lidar/Radar data fusion algorithm for obstacle detection and tracking\nbased on the global nearest neighbour standard filter (GNN). This algorithm is\nimplemented and embedded in an automative vehicle as a component generated by a\nreal-time multisensor software. The benefits of data fusion comparing with the\nuse of a single sensor are illustrated through several tracking scenarios (on a\nhighway and on a bend) and using real-time kinematic sensors mounted on the ego\nand tracked vehicles as a ground truth.\n