• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.842-850
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• 2014

This paper presents a trajectory tracking controller for rotorcraft UAVs to improve the tracking performances in the presence of various uncertainties. The proposed tracking method consists of a velocity guidance law based on the relative distance and L1 adaptive augmentation loop for tracking the velocity commands. In the proposed structure, the desired velocity generated by the guidance law is the reference value of the adaptive controller for accurate path tracking. In the guidance law, the desired acceleration is generated based on the relative distance and its derivatives, and then the velocity command of the inner control loop is calculated by integrating the accelerations. $L_1$ augmentation loop supplements the linear controller to guarantee the flight performances such as a tracking accuracy in the presence of the uncertainties. The proposed controller was validated in actual flight tests to successfully demonstrate its capability using a quadrotor UAV.

• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.264-271
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• 2017

This paper presents air traffic control simulation model for generating 4D trajectory, and aircraft dynamic model based on 4D trajectory information. With aircraft parameters from BADA and Total Energy Model, the trajectory is defined through modified Bezier curve and the simulation supports two aircraft control methods based on controlled time of arrival (CTA) or airspeed. The simulation results shown that flight time and path were almost identical to the defined trajectory, and derived the differences of each control methods according to wind conditions. Based on the simulation model developed in this study, it is expected to be applied to various air traffic management researches. Future studies will focus on applying optimization techniques in order to minimize the difference between generated trajectories and actual flight routes. This work will increase utilization of developed simulation futhermore.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.282-287
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• 2015

In modern warfare, the importance of SEAD(Suppression of Enemy Air Defense) mission is being emphasized. However, this mission runs the risk of hull damage or casualties of our friendly air forces. Because of these risks, research on the way of minimizing damages and enhancing mission capability is under active discussion. As a part of this research, SEAD mission planning with multiple UAVs has been covered using vector field guidance. This guidance method not only applies to various forms of flight path but also requires less computational power than other guidance methods. Therefore, in this paper, planning methods of SEAD mission for multiple UAVs using vector field guidance and experimental data from flight experiments regarding designed mission has been covered.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.187-194
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• 2008

Because the types and severities of most engine faults are various and complex, it is not easy that the conventional model based fault detection approach like the GPA(Gas Path Analysis) method can monitor all engine fault conditions. Therefore this study proposed newly a diagnostic algorithm for isolating and diagnosing effectively the faulted components of the smart UAV propulsion system, which has been developed by KARI(Korea Aerospace Research Institute), using the fuzzy logic and the neural network algorithms. A precise performance model should be needed to perform the model-based diagnostics. The based engine performance model was developed using SIMULINK. For the work and mass flow matching between components of the steady-state simulation, the state-flow library was applied. The proposed steady-state performance model can simulate off-design point performance at various flight conditions and part loads, and in order to evaluate the steady-state performance model their simulation results were compared with manufacturer's performance deck data. According to comparison results, it was confirm that the steady-state model well agreed with the deck data within 3% in all flight envelop. The diagnosis procedure of the proposed diagnostic system has the following steps. Firstly after obtaining database of fault patterns through performance simulation, then secondly the diagnostic system was trained by the FFBP networks. Thirdly after analyzing the trend of the measuring parameters due to fault patterns, then fourthly faulted components were isolated using the fuzzy logic. Finally magnitudes of the detected faults were obtained by the trained neural networks. Because the detected faults have almost same as degradation values of the implanted fault pattern, it was confirmed that the proposed diagnostic system can detect well the engine faults.

• Journal of Aerospace System Engineering
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• v.17 no.6
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• pp.46-53
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• 2023

As urban traffic congestion and environmental pollution are becoming significant issues in major cities, Urban Air Mobility (UAM) is gaining attention as an efficient solution. In this study, we conducted a geographic information system (GIS)-based spatial analysis and clustering algorithm considering the actual data of the terrain and infrastructure in the Busan area, through which we were able to select the location of vertiports and corridors (flight routes) for the UAM operation. Based on the Gimhae International Airport, which is expected to be the center of the UAM infrastructure system in the Busan region, we judged that three vertiport locations in the target area were suitable. Subsequently, we used the A^* (A-star) algorithm considering Ground Risk to select a flight path that minimized both risk and distance. Through this, we confirmed a risk reduction effect of 80.168% compared to the minimum distance route.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.103-111
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• 2021

The purpose of this study is to study a method for preventing collisions of multiple drones in controlled airspace. As a result of the study, it was proved that it is appropriate as a method to control drone collisions after setting accurate information on the ROI (Region of Interest) area estimated based on the expected drone path and time in the control system as a method to avoid drone collision. As a result of the empirical analysis, the diameter of the flight path of the operating drone should be selected to reduce the risk of collision, and the change in the departure time and operating speed of the operating drone did not act as an influencing factor in the collision. In addition, it has been demonstrated that providing flight priority is one of the appropriate methods as a countermeasure to avoid collisions. For collision avoidance methods, not only drone sensor-based collision avoidance, but also collision avoidance can be doubled by monitoring and predicting collisions in the control system and performing real-time control. This study is meaningful in that it provided an idea for a method for preventing collisions of multiple drones in controlled airspace and conducted practical tests. This helps to solve the problem of collisions that occur when multiple drones of different types are operating based on the control system. This study will contribute to the development of related industries by preventing accidents caused by drone collisions and providing a safe drone operation environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.55-63
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• 2018

In this paper, we measured the propagation path loss by a ground to air flight communication test at UHF band and analyzed the results. The ground receiving terminal was located at 1,100m above sea level in Cheju Island and the airborne transmit terminal flew at an altitude of 3.5km from 150 to 220km from the ground terminal. In this case, the ground terminal and the airborne terminal are on the Line of Sight. Therefore loss in this communications environment can be predicted based on Free Space Loss. However, in this test, the sea level exists between two terminals, and due to the very small angle of incidence on the reflecting surface due to the long-range communication environment, it is not possible to accurately predict the loss of free space only. Therefore, considering that there are no surrounding obstacles and that a line of sight is secured between the end of two terminals, we applied a plane earth reflection model and a spherical earth reflection model to estimate the propagation path loss and compared with the actual test results. As a result of the comparison, the predicted propagation path loss by a spherical earth reflection model were quite similar to the actual test values.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.181-190
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• 2014

The optimized flight path planning which is appropriate for UAV operation with high performance and multiplex sensors is required for efficient ISR missions. Furthermore, a mission visualization tool is necessary for the assessment of MoE(Measures of Effectiveness) prior to mission operation and the urgent tactical decision in peace time and wartime. A mission visualization and analysis tool was developed by combining STK and MATLAB, whose tool was used for UAV ISR mission analyses in this study. In this mission analysis tool, obstacle avoidance and FoM(Figure of Merit) analysis algorithms were applied to enable the optimized mission planning.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.76-80
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• 2017

With the fast growing popularity of small UAVs (Unmanned Aerial Vehicles), recent UAV systems have been designed and utilized for the various field with their own specific purposes. UAVs are opening up many new opportunities in the fields of electronics, sensors, camera, and software for pilots. Increase in awareness and mission capabilities of UAVs are driving innovations and new applications driven with the help of low cost and its capability in undertaking high threat task. In particular, small unmanned aerial vehicles should fly in environments with high probability of unexpected sudden change or obstacle appearance in low altitude situations. In this paper, current researches regarding techniques of autonomous flight of smal UAV systems are introduced and we propose a draft idea for planning paths for small unmanned aerial vehicles in adversarial environments to arrive at the given target safely with low cost sensors.