• Journal of Aerospace System Engineering
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• v.14 no.1
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• pp.68-73
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• 2020

This purpose of this paper was to review the development trend of the VTOL MAVs with a ducted propellant that can fly like the VTOL at intermediate and high speeds, hovering, landing, and lifting off vertically over urban areas, warships, bridges, and mountainous terrains. The MAV differs in flight characteristics from helicopters and fixed wings in many respects. In addition to enhancing thrust, the duct protects personnel from accidental contact with the spinning rotor. The purpose of the U.S. Army FCS and DARPA's OAV program is spurring development of a the VTOL ducted MAV. Today's MAVs are equipped with video/infrared cameras to hover-and-stare at enemies hidden behind forests and hills for approximately one hour surveillance and reconnaissance. Class-I is a VTOL ducted MAV developed in size and weight that individual soldiers can store in their backpacks. Class-II is the development of an organic VTOL ducted fan MAV with twice the operating time and a wider range of flight than Class-I. MAVs will need to develop to perch-and-stare technology for lengthy operation on the current hover-and-stare. The near future OAV's concept is to expand its mission capability and efficiency with a joint operation that automatically lifts-off, lands, refuels, and recharges on the vehicle's landing pad while the manned-unmanned ground vehicle is in operation. A ducted MAV needs the development of highly accurate relative position technology using low cost and small GPS for automatic lift-off and landing on the landing pad. There is also a need to develop a common command and control architecture that enables the cooperative operation of organisms between a VTOL ducted MAV and a manned-unmanned ground vehicle.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.9
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• pp.854-864
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• 2016

The use of small drone platform has become a popular topic in these days but its application for SAR operation has been little known due to the burden of the payload implementation. Drone platforms are distinguished from the conventional UAV system by the increased vulnerability to the turbulences, control-errors and poor motion stability. Consequently, sophisticated motion compensation may be required to guarantee the successful acquisition of high quality SAR imagery. Extremely limited power and mass budgets may prevent the use of additional hardwares for motion compensation and the difficulty of SAR focusing is further aggravated. In this paper, we have carried out a feasibility study of mico-SAR drone operation. We present the image acquisition results from the preliminary flight tests and a quality assessment is followed on the experimental SAR images. The in-flight motion errors derived from the unique drone movements are investigated and attempts have been made to compensate for the geometrical and phase errors caused by motions against the nominal trajectory. Finally, the successful operation of drone SAR system is validated through the focussed SAR images taken over test sites.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Smart Media Journal
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• v.13 no.2
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• pp.52-61
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• 2024

In the shipyard, aerial images are acquired at regular intervals using Unmanned Aerial Vehicles (UAVs) for the management of external storage yards. These images are then investigated by humans to manage the status of the storage yards. This method requires a significant amount of time and manpower especially for large areas. In this paper, we propose an automated management technology based on a semantic segmentation foundation model to address these challenges and accurately assess the status of external storage yards. In addition, as there is insufficient publicly available dataset for external storage yards, we collected a small-scale dataset for external storage yards objects and equipment. Using this dataset, we fine-tune an object detector and extract initial object candidates. They are utilized as prompts for the Segment Anything Model(SAM) to obtain precise semantic segmentation results. Furthermore, to facilitate continuous storage yards dataset collection, we propose a training data generation pipeline using SAM. Our proposed method has achieved 4.00%p higher performance compared to those of previous semantic segmentation methods on average. Specifically, our method has achieved 5.08% higher performance than that of SegFormer.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.135-161
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• 2014

An unmanned aerial vehicle (UAV), commonly known as a drone and also referred to as an unpiloted aerial vehicle and a remotely piloted aircraft (RPA) by the International Civil Aviation Organization (ICAO), is an aircraft without a human pilot aboard. ICAO classify unmanned aircraft into two types under Circular 328 AN/190. Unmanned aircraft, which is the core of the development of the aviation industry. However, there are also elements of the legal dispute. Unmanned aircraft are manufactured in small size, it is possible to shoot a record peripheral routes stored in high-performance cameras and sensors without the consent of the citizens, there is a risk of invasion of privacy. In addition, the occurrence of the people of invasion of privacy is expected to use of civilian unmanned aircraft. If the exposure of private life that people did not want for unmanned aircraft has occurred, may occur liability to the operator of unmanned aircraft, this is a factor to be taken into account for the development of unmanned aircraft industry. In the United States, which is currently led by the unmanned aircraft industry, policy related to unmanned aircraft, invasion of privacy is under development, is preparing an efficient measures making. Unmanned aircraft special law has not been enforced. So there is a need for legal measures based on infringement of privacy by the unmanned aircraft. US was presented Privacy Protection Act of unmanned aircraft (draft). However Korea has many laws have been enacted, to enact a new law, but will be able to harm the legal stability, there is a need for the enactment of laws for public safety of life. Although in force Personal Information Protection Law, unmanned aerospace, when the invasion of privacy occurs, it is difficult to apply the Personal Information Protection Law. So, it was presented a privacy protection bill with infringement of privacy of unmanned aircraft in the reference US legislation and the Personal Information Protection Act.