• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.2
• /
• pp.154-159
• /
• 2013

Alignment tolerance for EO/IR airborne camera using common optic is an important factor in stabilization accuracy and geo-pointing accuracy. Before airborne camera is mounted on the aircraft, defining alignment tolerance and verification of it is essential in production as well as research and development. In this paper we establish basic concept on the definition and elements of alignment tolerance for airborne camera and propose how to measure each of those elements. Components and the measurement sequence of alignment tolerance are as follows: 1) tolerance of alignment between EO and IR LOS. 2) tolerance of sensor alignment. 3) tolerance of position reporting accuracy. 4) tolerance of mount alignment

• Journal of the Korea Institute of Military Science and Technology
• /
• v.16 no.5
• /
• pp.646-652
• /
• 2013

PRA(Position Reporting Accuracy) for EO/IR(Electro-Optic/Infrared) airborne camera is an important factor in geo-pointing accuracy. Generally, rate table is used to measure PRA of gimbal actuated camera like EO/IR. However, it is not always possible to fix an EUT(Equipment for Under Test) to rate table due to capacity limit of the table on the size and weight of the object(EUT). Our EO/IR is too big and heavy to emplace on it. Therefore, we propose a new verification method of PRA for airborne camera and assess the validity of our proposition. In this method we use collimator, angle measuring instrument, 6 dof motion simulator, optical surface plate, leveling laser, inclinometer and poster(for alignment).

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.5
• /
• pp.490-498
• /
• 2010

This paper presents an autonomous target tracking approach and technique for transmitting ground control station image periodically for an unmanned aerial vehicle using onboard gimbaled(pan-tilt) camera system. The miniature rotary UAV which was used in this study has a small, high-performance camera, improved target acquisition technique, and autonomous target tracking algorithm. Also in order to stabilize real-time image sequences, image stabilization algorithm was adopted. Finally the target tracking performance was verified through a real flight test.

• Journal of Aerospace System Engineering
• /
• v.15 no.1
• /
• pp.102-110
• /
• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• Korean Journal of Remote Sensing
• /
• v.32 no.3
• /
• pp.275-285
• /
• 2016

This study analyzes the accuracy of ortho imagery based on whether camera calibration performed or not, using an unmanned aerial vehicle which equipped smart camera. Photgrammetric UAV system application was developed and smart camera performed image triangulation, and then created image as ortho imagery. Image triangulation was performed depending on whether interior orientation (IO) parameters were considered or not, which determined at the camera calibration phase. As a result of the camera calibration, RMS error appeared 0.57 pixel, which is more accurate compared to the result of the previous study using non-metric camera. When IO parameters were considered in static experiment, the triangulation resulted in 2 pixel or less (RMSE), which is at least 200 % higher than when IO parameters were not considered. After generate ortho imagery, the accuracy is 89% higher when camera calibration are considered than when they are not considered. Therefore, smart camera has high potential to use as a payload for UAV system and is expected to be equipped on the current UAV system to function directly or indirectly.

• Korean Journal of Remote Sensing
• /
• v.30 no.6
• /
• pp.797-807
• /
• 2014

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of $1^{\circ}C$.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.36 no.6
• /
• pp.600-607
• /
• 2008

Reliable wireless transmission of data generated by the flight critical subsystems or mission equipments of the unmanned aerial system is critical for mission success. As the UAS system becomes more sophisticated, its dependency on a reliable high rate radio communication system also increases. This requirement is applied not only during the operation phase but also in the early development test phase. This paper introduces a practical cost-effective communication system for a UAS. The downlink module combines analog NTSC video signal with onboard data, and send them using 2.4 GHz carrier wave. The uplink system has less a severe requirement on the bandwidth, and thus uses 430 MHz signal. This paper also presents a sample packet structure which can be adopted for many UAS of similar class.

• The Optical Journal
• /
• s.158
• /
• pp.52-54
• /
• 2015

최근 무인항공기를 지칭하는 드론 관련 산업이 미래를 이끌 신산업으로 부상하고 있다. 드론은 20세기 초에 군사용으로 개발되어 정찰 감시 및 폭격과 같은 군사임무를 수행하여 왔으나 최근 들어 독일 DHL, 아마존, 구글 등과 같은 다국적 기업들이 상업적 용도로 활용을 선언하며 연구 개발에 뛰어 들면서 그 시장이 예상보다 빨리 커지고 있다. 미국 틸 그룹의 보고서에 의하면 2013년 세계 드론 시장의 규모는 66억 달러였고 그 중 군사용이 90% 이상을 차지하고 있으나 향후 민수용 시장 비율이 상당히 커질 것으로 예상된다. 2022년에는 114억 달러 규모로 커질 것으로 예상하고 있다. 현재 민수용으로 사진 촬영용 소형 드론으로부터 정밀농업, 인프라 관리, 택배 및 화물 수송 등으로 운용 범위를 확대하고 있다. 국내 드론 산업은 군수 위주로 시작되어 세계 7위권의 기술력을 확보한 것으로 평가되고 있다. 무인기 분야의 연구개발은 국방과학연구소와 한국항공우주연구원 등 정부출연연구소가 주도하는 가운데, 한국항공우주산업, 대한 항공이 주로 체계종합(System Integrator) 및 비행체 개발을 담당하고 LIG넥스원, 삼성탈레스, 삼성테크윈 등의 대기업을 포함한 중소업체들이 부체계 기술을 개발하고 있다. 최근 소형 드론을 중심으로 시장형성이 가시화되는 민수 시장에서는 가격, 기술 경쟁력의 열위에 있어, 국내 산업 경쟁력 확보와 미래 시장을 선도할 핵심 제품 개발이 시급한 실정이다. 또한 무인기의 비행체 국산화는 상당한 수준으로 진행되었으나, 광학(EO) 적외선(IR) 카메라 등 핵심 부가가치를 구성하는 탑재 임무장비의 경우 원천기술의 부족으로 해외에 의존하고 있다.

• Journal of Advanced Navigation Technology
• /
• v.18 no.2
• /
• pp.151-157
• /
• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Korean Journal of Remote Sensing
• /
• v.21 no.4
• /
• pp.341-369
• /
• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.