Aug 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· Vol XLIX-B4-2026, pp. 275-280· 0 citations· 3 references
Abstract
Abstract. Reliable communication between satellites and ground control stations (GCS) is fundamental to modern space missions, with its effectiveness being directly dependent on an unobstructed Line-of-Sight (LoS). Traditional site planning methods, relying on low-resolution terrain models, often overlook crucial obstacles like buildings or dense vegetation. This paper presents a comprehensive methodology using high-resolution Light Detection and Ranging (LiDAR) data, acquired from an Unmanned Aerial Vehicle (UAV), to precisely model horizon obstruction and optimize the placement of transceiver antennas. The methodology was verified on a real-world case study in Zielona Góra, Poland. The workflow included data acquisition, PPK-based trajectory processing, and point cloud subsampling using an Octree-based algorithm. The core of this work was the implementation of an algorithm to generate detailed elevation masks by calculating the maximum obstruction angle for defined azimuthal intervals. The analysis clearly identified the superior of two potential locations, proving the method's effectiveness as a decision-support tool in the space sector.
Driven by the rapid development of the low-altitude economy, unmanned aerial vehicles (UAVs) urgently require high reliability, low-latency, and continuous coverage in complex urban environments. However, conventional 5G networks employ fixed two-dimensional (2D) beamforming strategies optimized for ground users, resul...
Jun Li, Pei-Quan Fan, Wen-Juan Hou et al.· Conference on Advanced Algor...· 0 citations
The synthesis indicates that LiDAR remains a strong perceptual backbone for UAV autonomy, but that state-of-the-art systems increasingly combine it with inertial, visual, radar, and learning-based components rather than relying on LiDAR in isolation.
Svitlana Pavlova, V. Chepizhenko, Fu-Zhong Li et al.· Applied Sciences· 0 citations
With the rapid development of unmanned aerial vehicle (UAV) technology, UAV mapping has been widely adopted in surveying production and smart city applications due to its cost-effectiveness and high efficiency. However, deploying ground control points (GCPs) remains labor-intensive and time-consuming. To address the li...
Tao Zhang, Xue-Cai Yu· International Conference on...· 0 citations
Accurate and robust localization of UAV swarms in GNSS-denied urban environments remains a major challenge because signal blockage, multipath, and poor anchor geometry can severely degrade positioning performance. This paper extends our previous work on degree-centrality-based clustering for UAV swarm relative locali...
Asma Boulkaid, Aurelio Bermúdez, Rafael Casado et al.· Annals of Telecommunications· 0 citations
LiDAR-based SLAM (Simultaneous Localization and Mapping) and LIO (LiDAR-inertial odometry) algorithms are often used for precise navigation of unmanned aerial vehicles, especially during interactions with the aerial robot's environment. However, the performance of these algorithms is greatly dependent on the scenario,...
Robert Milijaš, J. R. M. Dios, Stjepan Bogdan· 0 citations
Visual SLAM (Simultaneous Localization and Mapping) is a core technology for UAV autonomous navigation. However, it suffers from cumulative errors and heading drift in texture-less environments (e.g., sky, water surfaces) or during longterm operation. Traditional methods relying on GPS or inertial sensors face limitati...
Junwei Lv, Qin-Bin Xu, Hao Liu et al.· International Conference on...· 0 citations
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