• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.471-478
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• 2022

This paper is about research and development of Korea Aerospace University's Solar-Powered UAV System that named of KAU-SPUAV, and describes the design process of the 4.2 m solar UAV that succeeded in a long flight of 32 hours and 19 minutes at June 2020. In order to improve the long-term flight performance of the KAU-SPUAV, For reduce drag, a circular cross-section of the fuselage was designed, and manufactured light and sturdy fuselage by applying a monocoque structure using a glass fiber composite material. In addition, a solar module optimized for the wing shape of a 4.2 m solar drone was constructed and arranged, and a propulsion system applied with the 23[in] × 23[in] propeller was constructed to improve charging and flight efficiency. The developed KAU-SPUAV consumes an average of 55W when cruising and can receive up to 165W of energy during the day, and its Long-term Endurance was verified through flight tests.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.551-560
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• 2014

Compare to other industrial sites, the civil construction work not only takes longer time but also has made of complicated processes, such as the integrated management, process control, and quality control until the completion. However, it is hard to take control the construction sites, since numerous issues are always emerged. The study purposes on providing the dataset to synthetically manage and monitor the civil construction site, main design, drawings, process, construction cost, and others at real-time by using the low altitude close-range aerial images, based on UAV, and the GPS surveying method for treating the three-dimensional spatial information quickly and accurately. As a result, we could provide the latest information for the quick decision-making following from planning to completion of the construction, and objective site evaluation by the high-resolution three-dimensional spatial information and drawings. Also, the present map, longitudinal map, and cross sectional view are developed to provide various datasets rapidly, such as earthwork volume table, specifications, and transition of ground level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.295-301
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• 2018

Recently, GPS(Global Positioning System) array antenna technology is generally used and widely adopted as a national infrastructure structure and aero-vehicles for protection the GPS signal reception. Until now, the 2-dimensional planar array is universally used for its applications in the array antenna signal processing, however relatively higher altitude air vehicles such as UAV experiences additional null zones induced by low altitude GPS interferences which is located in a symmetry zone of antenna horizontal plane and this could make the receiving antenna pattern coverage reduction. In this paper, we improved 20% of the beam pattern receiving performance and 13 dB correlation value improvement by eliminating the interference mirror images.

• 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 the Korea Institute of Military Science and Technology
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• v.19 no.4
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• pp.443-452
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• 2016

Current low-altitude radar system often fails to detect small unmanned aerial vehicles (UAV) because of their small radar cross section (RCS) compared with larger targets. As a potential alternative, a passive bistatic radar system has been considered. We study an optimal deployment problem for the passive bistatic radar system. We model this problem as a covering problem, and develop an integer programming model. The objective of the model is to maximize coverage of a passive bistatic radar system. Our model takes into account factors specific to a bistatic radar system, including bistatic RCS and transmitter-receiver pair coverage. Considering bistatic RCS instead of constant RCS is important because the slight difference of RCS value for small UAVs could significantly influence the detection probability. The paired radar coverage is defined by using the concept of gradual coverage and cooperative coverage to represent a realistic environment.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1104-1111
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• 2009

In the low altitude, mission of the aircraft is restricted by a variety of threats such as anti-air missiles and terrain obstacles. Especially, aircraft have always a risk of ground collision near terrain. In this study, to effectively solve this problem, we developed the flight path generation algorithm that is considered the terrain avoidance. In this flight path generation algorithm, waypoints that should be passed by the UAV are selected first. The waypoints are located in the middle of the terrain obstacles. Then, physically meaningful waypoints sets are classified by Dijkstra algorithm. The optimal waypoint guidance law based on the optimal control theory is applied to produce trajectory candidates. And finally the minimum control energy trajectory is determined.

• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.59-66
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• 2018

Using hydrogen fuel is expected to be suitable as a reciprocating internal combustion engine with heightened interest in HALE(High Altitude Long Endurance) UAV(Unmanned Aerial Vehicle). Hydrogen is hightest energy density per mass so it can continue to charge for long periods of time and have positive part of the environmental effects. However, it is estimated that there is less research on hydrogen fuel engine currently applied, and many studies need to be done. Depending on the operation, there are factors that result in supercooling due to reduced radiation or reduce cooling performance due to low air density. Therefore, the experiment was to change the temperature of the cooling water and investigate the effect on engine combustions. The limitation of the stable operation range due to backfire is dominated by the excess air ratio rather than the effect of the cooling water temperature change. When the cooling water temperature increases, the volumetric efficiency decreases and the torque decreases. As the cooling water temperature decreases, the heat loss was increased and consequently the thermal efficiency was decreased.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.611-624
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• 2018

The percentage of moisture content in rice before harvest is crucial to reduce the economic loss in terms of yield, quality and drying cost. This paper discusses the application of artificial neural network (ANN) in developing a reliable prediction model using the low altitude fixed-wing unmanned air vehicle (UAV) based reflectance value of green, red, and NIR and statistical moisture content data. A comparison between the actual statistical data and the predicted data was performed to evaluate the performance of the model. The correlation coefficient (R) is 0.862 and the mean absolute percentage error (MAPE) is 0.914% indicate a very good accuracy of the model to predict the moisture content in rice before harvest. The model predicted values are matched well with the measured values($R^2=0.743$, and Nash-Sutcliffe Efficiency = 0.730). The model results are very promising and show the reliable potential to predict moisture content with the error of prediction less than 7%. This model might be potentially helpful for the rice production system in the field of precision agriculture (PA).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.257-264
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• 2020

Vectorization is currently the main method in feature collection (extraction) during digital mapping using UAV-Photogrammetry. However, this method is time consuming and prone to gross elevation errors when extracted from a DSM (Digital Surface Model), because three-dimensional feature coordinates are vectorized separately: plane information from an orthophoto and height from a DSM. Consequently, the demand for stereo plotting method capable of acquiring three- dimensional spatial information simultaneously is increasing. However, this method requires an expensive equipment, a Digital Photogrammetry Workstation (DPW), and the technology itself is still incomplete. In this paper, we evaluated the accuracy of low-cost stereo plotting system, Menci's StereoCAD, by analyzing its three-dimensional spatial information acquisition. Images were taken with a FC 6310 camera mounted on a Phantom4 pro at a 90 m altitude with a Ground Sample Distance (GSD) of 3 cm. The accuracy analysis was performed by comparing differences in coordinates between the results from the ground survey and the stereo plotting at check points, and also at the corner points by layers. The results showed that the Root Mean Square Error (RMSE) at check points was 0.048 m for horizontal and 0.078 m for vertical coordinates, respectively, and for different layers, it ranged from 0.104 m to 0.127 m for horizontal and 0.086 m to 0.092 m for vertical coordinates, respectively. In conclusion, the results showed 1: 1,000 digital topographic map can be generated using a stereo plotting system with UAV images.