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Drones are capable of exploring large areas due to their swift mobility and utilization efficiency, so their use in various fields such as surveillance is increasing. When a drone performs its mission, the estimation of drone's location relies on GPS signals. Therefore, it becomes difficult to accurately estimate the drone's location in environments where GPS signals are unstable or in denied areas, which directly affects the safety and mission performance of the drone. Drone missions by autonomous flight are often carried out along a given route. This can be done by extracting and comparing the feature points of the image data from the camera mounted on the drone and the image data on the already constructed map using the SIFT algorithm. It allows the drone’s location to be estimated under GPS-denied environments. In this paper, we aim to construct aerial map data and verify the technology for estimating and correcting the drone’s location through image data received from the drone. [ABSTRACT FROM AUTHOR]

In this letter, we investigate a beam placement problem to determine the optimal beam center position that maximizes the minimum transmission rate of users within a spot beam for a multicast transmission in low-Earth-orbit satellite communications. We make a system model for satellite beam placement and formulate an optimization problem that maximize the minimum transmission rate of ground nodes (GNs). Then, we propose a gradient ascent algorithm to calculate the optimal beam center position. The simulation results show that the proposed scheme optimally determines the position of the beam center and maximizes the minimum rate of GNs according to various satellite parameters. [ABSTRACT FROM AUTHOR]