• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.233-239
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• 2013

A 100 W fuel cell system using chemical storage method has been applied for a propulsion system of the SUAV(Small Unmanned Aerial Vehicle). A fuel cell and battery have been combined for both the small/light hydrogen generation control system and the hybrid power supply system. A small hydrogen generation device was implemented to utilize NaBH4 aqueous solution and dead-end type PEMFC system, which were evaluated on the ground and by the flight tests. The system pressurized at a 45kpa stably operates and get higher fuel efficiency. The pressure inside of the hydrogen generation control system was maintained at between 45 kPa and 55 kPa. The 100W fuel cell system satisfies the required weight and power consumption rate as well as the propulsion system, and the fuel cell system performance was demonstrated through flight test.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.326-329
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• 2016

UAVs(Unmanned Aerial Vehicle) can be used in variant fields fornot only combat, but also recon, observation and exploration. Moreover, UAVs capacity can be expanded to impossible missions for existing surveillance system such as SAR(Synthetic Aperture Radar) technology that collecting images from all weather conditions. In recent days, with development of highly efficient IC and lightened system technology, there are significant increase of researches and demands to make SAR sensor as a payload of UAV. Therefore, this paper contains development process and results of small signal generator and RF device as a core module of SAR system based on the digital device of DDS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.934-939
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• 2012

In this study, the performance validation of a PAO-AIR heat exchanger developed for the ECS(Environmental Control System) of a UAV(Unmanned Aerial Vehicle) has been carried out. The performance goals of a PAO-AIR heat exchanger were established by the system schematic analysis. And a heat exchanger to be met the ECS performance was developed by a detailed design and a precision manufacture. Using the developed heat exchanger, the experiment about pressure loss and effectiveness, overall heat transfer coefficient to prove the developed PAO-AIR heat exchanger performance in various conditions as well as a design point of heat exchanger was performed and the experimental results were analyzed. As the experimental results, the performance and characteristic of a PAO-AIR heat exchanger developed for the ECS of a UAV were analyzed and the development suitability was proved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.511-523
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• 2023

Research on the integration of unmanned aerial vehicles and deep learning for reinforced concrete damage detection is actively underway. Convolutional neural networks have a high impact on the performance of image classification, detection, and segmentation as backbones. The MobileNet, a pre-trained convolutional neural network, is efficient as a backbone for an unmanned aerial vehicle-based damage detection model because it can achieve sufficient accuracy with low computational complexity. Analyzing vanilla convolutional neural networks and MobileNet under various conditions, MobileNet was evaluated to have a verification accuracy 6.0~9.0% higher than vanilla convolutional neural networks with 15.9~22.9% lower computational complexity. MobileNetV2, MobileNetV3Large and MobileNetV3Small showed almost identical maximum verification accuracy, and the optimal conditions for MobileNet's reinforced concrete damage image feature extraction were analyzed to be the optimizer RMSprop, no dropout, and average pooling. The maximum validation accuracy of 75.49% for 7 types of damage detection based on MobilenetV2 derived in this study can be improved by image accumulation and continuous learning.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.5
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• pp.376-382
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• 2014

This paper presents a method to enable a UAV in autonomous flight along a desired path to follow it backwards when a strong headwind prevents the vehicle from proceeding forward. The main purpose of the reverse path following in this study is to return to a mission quickly when the wind becomes weaker. When the nonlinear path following guidance law is used, there are two reference points available in the path following. One of the two points is selected considering a flight direction for calculating a straight-line distance(L) from the vehicle to the point for the path following. An initial heading angle with respect to the wind direction determines whether the reverse path following is feasible or not at the time of the wind is generated. The result of the proposed method based on kinematic model in this study is verified through simulations implemented in Matlab.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.112-119
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• 2004

This paper proposes an attitude determination GPS/INS integrated system scheme for a UAV and presents experimental flight test results. The proposed system is designed as a part of an autopilot system and comprises a GPS attitude determination receiver, an off-the-shelf inertial measurement unit (IMU), and a navigation computer unit (NCU). UAV requires accurate attitude information for stable automatic flight control. The proposed system can provide accurate attitude information for the flight control computer (FCC) so that stable automatic flight control can be achieved. In order to verify the performance of the proposed scheme, an integrated navigation system has been developed. In order to evaluate the developed navigation system, the flight test has been performed. In the flight test, the developed system was shown to provide the position, the velocity and the attitude satisfactorily enough for stable flight control. The accuracy of the attitude information of the developed system was confirmed by comparing attitude of vertical gyro.

• Journal of Aerospace System Engineering
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• v.14 no.spc
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• pp.39-48
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• 2020

This paper deals with the process of estimating the environmental noise generated from the actual flying aircraft using the noise measurement results obtained through the wind tunnel test and verifying it through flight tests. In order to evaluate the environmental noise of an aircraft, noise tests and evaluations are generally conducted according to the procedures prescribed by the International Civil Aviation Organization (ICAO). In this paper, we introduced environmental noise evaluation method that can be applied to composite both fixed-wing aircraft and multi-copter, and introduced the evaluation method by experiment. This paper introduces the process of simulating the noise test results measured in the wind tunnel test using real flight test results. In addition, in consideration of flight operating conditions and noise measurement methods proposed by the ICAO, the effective perceived noise level (EPNL) was predicted by performing both the wind tunnel test and the aircraft flight test.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Korean Journal of Optics and Photonics
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• v.26 no.3
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• pp.155-161
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• 2015

We report the design and performance analysis of an off-axis three-mirror telescope as the fore optics for a new hyperspectral sensor aboard a small unmanned aerial vehicle (UAV), for low-altitude coastal remote sensing. The sensor needs to have at least 4 cm of spatial resolution at an operating altitude of 500 m, $4^{\circ}$ field of view (FOV), and a signal to noise ratio (SNR) of 100 at 660 nm. For these performance requirements, the sensor's optical design has an entrance pupil diameter of 70 mm and an F-ratio of 5.0. The fore optics is a three-mirror system, including aspheric primary and secondary mirrors. The optical performance is expected to reach $1/15{\lambda}$ in RMS wavefront error and 0.75 in MTF value at 660 nm. Considering the manufacturing and assembling phase, we determined the alignment compensation due to the tertiary mirror from the sensitivity, and derived the tilt-tolerance range to be 0.17 mrad. The off-axis three-mirror telescope, which has better performance than the fore optics of other hyperspectral sensors and is fitted for a small UAV, will contribute to ocean remote-sensing research.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.