Multi-Sensory Data Fusion in Terms of UAV Detection in 3D Space is a research paper by Janusz Dudczyk, Roman Czyba, and Krzysztof Skrzypczyk.
This paper addresses the challenge of detecting unmanned aerial vehicles (UAVs) that intrude into restricted airspace. The primary objective of this research is to design an algorithm capable of detecting, identifying, and recognizing UAVs in three-dimensional space when they breach restricted airspace. The proposed method relies on multi-sensor data fusion and is founded on conditional complementary filtration and multi-stage clustering techniques.
After reviewing available UAV detection technologies, three sensory systems, categorized as passive and active methods, are selected for integration. The UAV detection algorithm is developed using data collected during field tests conducted under realistic conditions, utilizing input from three sensors: a radio system, an ADS-B transponder, and a radar-equipped with four antenna arrays. To assess the effectiveness of the proposed solution, rapid prototyping is carried out within the MATLAB simulation environment, utilizing data from actual sensory systems obtained during controlled UAV flights. The results of UAV detections obtained through this approach validate the effectiveness of the proposed method, aligning with the theoretical expectations.
Publication Date– June 2022
Multi-Sensory Data Fusion in Terms of UAV Detection in 3D Space contains the following major sections:
- Review of Anti-Drone Systems
- UAV Detection Technologies
- Data Acquisition during Operational Activities
- Sensory Data Analysis
- Sensory Fusion Concept
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Authors- Janusz Dudczyk, Roman Czyba, and Krzysztof Skrzypczyk.
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Post Image- UAV flight path registered by various sensors after the information fusion (Image Credit: Authors)