Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

Filters

2
2
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Lidar-based detection and tracking of small UAVs
    ( 2018)
    Hammer, Marcus
    ;
    Hebel, Marcus orcid-logo
    ;
    Laurenzis, Martin
    ;
    Arens, Michael
    The number of reported incidents caused by small UAVs, intentional as well as accidental, is rising. To avoid such incidents in future, it is essential to be able to detect UAVs. LiDAR sensors (e.g., laser scanners) are well known to be adequate sensors for object detection and tracking. In this paper, we expand our existing LiDAR-based approach for the tracking and detection of (low) flying small objects like commercial mini/micro UAVs. We show that UAVs can be detected by the proposed methods, as long as the movements of the UAVs correspond to the LiDAR sensor's capabilities in scanning performance, range and resolution. The trajectory of the tracked object can further be analyzed to support the classification, meaning that UAVs and non- UAV objects can be distinguished by an identification of typical movement patterns. A stable tracking of the UAV is achieved by a precise prediction of its movement. In addition to this precise prediction of the target's position, the object detection, tracking and classification have to be achieved in real-time. For the algorithm development and a performance analysis, we analyzed LiDAR data that we acquired during a field trial. Several different mini/micro UAVs were observed by a system of four 360° LiDAR sensors mounted to a car. Using this specific sensor system, the results show that UAVs can be detected and tracked by the proposed methods, allowing a protection of the car against UAV threats within a radius of up to 35 m.
  • Publication
    Potential of lidar sensors for the detection of UAVs
    ( 2018)
    Hammer, Marcus
    ;
    Hebel, Marcus orcid-logo
    ;
    Borgmann, Björn
    ;
    Laurenzis, Martin
    ;
    Arens, Michael
    The number of reported incidents caused by UAVs, intentional as well as accidental, is rising. To avoid such incidents in future, it is essential to be able to detect UAVs. LiDAR systems are well known to be adequate sensors for object detection and tracking. In contrast to the detection of pedestrians or cars in traffic scenarios, the challenges of UAV detection lie in the small size, the various shapes and materials, and in the high speed and volatility of their movement. Due to the small size of the object and the limited sensor resolution, a UAV can hardly be detected in a single frame. It rather has to be spotted by its motion in the scene. In this paper, we present a fast approach for the tracking and detection of (low) flying small objects like commercial mini/micro UAVs. Unlike with the typical sequence -track-after-detect-, we start with looking for clues by finding minor 3D details in the 360° LiDAR scans of scene. If these clues are detectable in consecutive scans (possibly including a movement), the probability for the actual detection of a UAV is rising. For the algorithm development and a performance analysis, we collected data during a field trial with several different UAV types and several different sensor types (acoustic, radar, EO/IR, LiDAR). The results show that UAVs can be detected by the proposed methods, as long as the movements of the UAVs correspond to the LiDAR sensor's capabilities in scanning performance, range and resolution. Based on data collected during the field trial, the paper shows first results of this analysis.