• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.379-388
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• 2019

Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.2
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• pp.51-56
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• 2017

Given that the utilization of Unmanned Aerial Vehicles (UAVs) is recently increased, a variety of UAV control methods are being applied. In general, it has been used a lot to directly control a UAV via manipulator. However, tangible user interface is required to control UAVs accurately. This paper proposes a method for controlling an UAV based on multiple Myos. The UAV is connected to a ground control station and then controlled by Myos. Intuitive control is possible by controlling the UAV using tangible user interface.

• ETRI Journal
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• v.45 no.5
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• pp.874-886
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• 2023

A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.4
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• pp.284-291
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• 2017

There is no doubt that advances in UAV technology have improved military performance. However, these advances require humans to adapt to new and complex operational systems. UAV has been rapidly expanding to a variety of fields such as reconnaissance, transportation, communication and aerial photographing recently. Also, with the development of UAV automation technology, one operator is able to supervisory-control multiple-UAVs. However, as the number of assigned UAV increases, the amount of information increases and this results in the workload of the operator increasing and deterioration in controlling performance. Accordingly, there is a need for a model to determine the level of overload an operator may encounter with regard to multiple-UAV but nationally this kind of research is currently lacking. Therefore, this paper provides an experimental platform for evaluating workload index effectiveness integrating multiple-UAV operational environments, GCS, and eye-tracking system followed by a limited survey of domestic and international studies of multi-UAV overload studies.

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.141-152
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• 2009

The simultaneous operation of multiple UAV's makes it possible for us to raise the mission accomplishment and cost efficiency. For this we need an easily scalable control algorithm, and swarm intelligence having the characteristics such as flexibility, robustness, decentralized control and self-organization comes into the spotlight as a practical substitute. In this paper the features of swarm intelligence are described, and various research results are introduced which show that the application of swarm intelligence to the control of multiple UAV's enables the missions of surveillance, path planning, target tracking and attack to be accomplished efficiently by simulations and tests.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.479-480
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• 2018

최근 무인항공기(Unmanned Aerial Vehicle, UAV)에 부착된 카메라로 사용자를 촬영함으로써 레저 및 여행 중 영상을 기록하기 위해 활용하고 있다. UAV에 부착된 카메라로 사용자를 촬영하기 위해 사용자가 직접 조종하거나 NUI/NUX 기술을 활용한다. UAV가 비행해야 되는 비행경로를 미리 설정하거나 단일 사용자를 추적해서 자동적으로 UAV가 비행하며 UAV에 부착된 카메라로 단일 사용자 중심으로 촬영한다. 하지만 레저 및 여행 중 영상을 기록하는 과정에서 단일 사용자 중심이 아니라 복수의 사용자를 고려하여 촬영해야 되는 경우가 있다. UAV가 복수의 사용자 위치를 고려하여 복수의 사용자를 촬영하는 시스템이 필요하다. 본 논문에서는 복수의 사용자를 촬영하기 위한 촬영 시스템을 설계한다. 촬영 시스템은 복수의 사용자 위치의 변화를 기반으로 UAV를 제어한다.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.118-122
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• 2013

In this study, We show that multiple UAVs (Unmaned Air Vehicle) have datalink system which includes the IEEE 802.11b technology. we are predicting and calculating to the number of the UAV and data rate between UAV and ground control system, using the IEEE 802.11 standards which include the transmit/receive the delay time and theoretical maximum throughput (TMT).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.352-362
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• 2010

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

• Journal of Advanced Navigation Technology
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• v.25 no.3
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• pp.211-216
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• 2021

Multiple UAV System has been used for various purposes such as reconnaissance, networking and aerial photography. In such systems, it is essential to form and maintain the formation of multiple UAVs. This paper proposes the algorithm that produces an autonomous distributed control for each vehicle for a flexible formation. This command is a repulsive force in the form of the second-order system by the nearest UAV or mission area. The algorithm uses the relative position/speed through sensing and communication for calculating the command without external intervention. The command allows each UAV to follow the reference distance and fill the mission area as densely as possible without overlapping. We determine the reference distance via optimization technique solving the packing problem. The mission area comprises the desired formation outline and can be set flexibly depending on the mission. Numerical simulation is carried out to verify the performance of the proposed algorithm under a complex and flexible environment. The formation is formed in 26.94 seconds and has a packing density of 71.91%.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.3-11
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• 2017

UAV system has the limitation to allocate enough spectrum bandwidth for the operation of multiple UAVs due to the market expansion. In addition, the communication environment of UAV network varies dynamically due to the UAV's mobility. Thus, to operate the stable UAV system and maximize the transmission data rate, it needs to allocate the resource effectively in the limited bandwidth considering the given network environment. In this paper, we propose the resource allocation algorithm which can maximize the network throughput as well as satisfy the minimum data requirement for the UAV system operation in the given network environment based on TDMA(Time Division Multiple Access). By performance analysis, we show that the proposed algorithm can allocate the resource to satisfy the high network throughput as well as the minimum data requirement in the given network environment.