• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.77-87
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• 2022

The Precision Aerial Delivery System is an instrument designed to improve the poor landing accuracy of aerial delivery system with conventional circular parachutes, and is equipped with an Airborne Guidance Unit to safely transport supplies to the desired destination. Currently, the landing accuracy of the PADS product is reported as CEP₅₀ 100m and also differs significantly, depending on the actual topography and weather environment. In this study, HILS was constructed based on the 6DOF nonlinear modeling of PADS to analyze the maneuver characteristics of Ram Air Parachute under wind environments. By using the new algorithm a precision soft landing algorithm including Energy Management and Final Approach is designed. HILS results show that it is possible to achieve a precise soft landing within CEP₅₀ 40m, and it can be exploited to develop an actual PADS drop test.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.6
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• pp.499-508
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• 2016

This paper describes a study of performance prediction of an electric propulsion system for multirotor UAVs. The electric propulsion system consists of motors, propellers, batteries and speed controllers, and significantly affects performance characteristics of the platform. The performance of the electric propulsion system for multirotor UAVs was predicted using an analytical model derived from the characteristics of each component, operation experiments and statistical analyses. Ground performance tests and endurance flights were performed to verify the reliability of the proposed performance prediction method. A quadrotor platform was designed to demonstrate the parcel delivery service used in the endurance flight. From the result of verification tests, it was confirmed that the proposed method has a good agreement.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.14-29
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• 2020

The 6G mobile communication system will become a backbone infrastructure around 2030 for the future digital world by providing distinctive services such as five-sense holograms, ultra-high reliability/low-latency, ultra-high-precision positioning, ultra-massive connectivity, and gigabit-per-second data rate for aerial and maritime terminals. The recent remarkable advances in machine learning (ML) technology have recognized its efficiency in wireless networking fields such as resource management and cell-configuration optimization. Further innovation in ML is expected to play an important role in solving new problems arising from 6G network management and service delivery. In contrast, an approach to apply ML to a physical-layer (PHY) target tackles the basic problems in radio links, such as overcoming signal distortion and interference. This paper reviews the methodologies of ML-based PHY, relevant industrial trends, and candiate technologies, including future research directions and standardization impacts.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.173-179
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• 2022

Through the 2014 Donbas conflict and the 2022 Ukraine-Russia war, we are experiencing that the command of the air is no longer only secured by the Air Force. Long-range surveillance reconnaissance and strikes carried out by the Air Force could be replaced by drones and missiles, and the enemy's aerial attacks could be controlled by air defense systems such as Panchir and portable anti-aircraft missiles, allowing ground forces to carry out maneuvers freely. In other words, it is much more advantageous for the air force and the navy to take control of the air through long-distance operations, and the ground forces should support them. Therefore, this study aims to consider the cost-effectiveness aspect of the delivery command of the air; it provides implications for quickly responding to enemy air attacks by developing the air defense weapon system, drones, missiles, precision-guided munitions, etc rather than focusing on expensive fighter jets.