Detection and Tracking of MAVs Using a Rosette Scanning Pattern LiDAR

• URL: http://arxiv.org/abs/2408.08555v2
• Date: Mon, 24 Feb 2025 16:37:57 GMT
• Title: Detection and Tracking of MAVs Using a Rosette Scanning Pattern LiDAR
• Authors: Sándor Gazdag, Tom Möller, Anita Keszler, András L. Majdik,
• Abstract summary: Drone detection and tracking has become a priority due to the increased security risks.<n>In this study, we tackle this challenge, by using non-repetitive rosette scanning pattern LiDARs.<n>A Pan-Tilt platform is utilized to take advantage of the specific characteristics of the rosette scanning pattern LiDAR.<n>Our approach achieved accuracy on par with the state-of-the-art indoor method while increasing the maximum detection range by approximately 80% beyond the state-of-the-art outdoor method.
• Score: 2.2124180701409233
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The use of commercial Micro Aerial Vehicles (MAVs) has surged in the past decade, offering societal benefits but also raising risks such as airspace violations and privacy concerns. Due to the increased security risks, the development of autonomous drone detection and tracking systems has become a priority. In this study, we tackle this challenge, by using non-repetitive rosette scanning pattern LiDARs, particularly focusing on increasing the detection distance by leveraging the characteristics of the sensor. The presented method utilizes a particle filter with a velocity component for the detection and tracking of the drone, which offers added re-detection capability. A Pan-Tilt platform is utilized to take advantage of the specific characteristics of the rosette scanning pattern LiDAR by keeping the tracked object in the center where the measurement is most dense. The detection capabilities and accuracy of the system are validated through indoor experiments, while the maximum detection distance is shown in our outdoor experiments. Our approach achieved accuracy on par with the state-of-the-art indoor method while increasing the maximum detection range by approximately 80\% beyond the state-of-the-art outdoor method.

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