article
This paper introduces a novel approach to enhance aviation safety by integrating Single-photon Light Detection and Ranging (LiDAR) technology into the existing Traffic Collision Avoidance Systems (TCAS). This integration aims to address the limitations of current TCAS by providing precise 3D imaging over extensive distances. A study of data fusion using the Kalman filter algorithm is presented for TCAS and LiDAR sensors. The results indicate successful superposition for a moving 2D object. Additionally, design considerations, and cost and power analyses for the proposed system are discussed. A simulation in Python using iterative closest point (ICP) shows that comprehensive 3D point cloud acquisition is attainable. Hence, the system has the potential to enhance the safety of the aviation industry, by potentially reducing mid-air collisions (MAC).
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DOI: 10.1109/icitcom62788.2024.10762412
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