• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.81-90
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• 2020

The use of machine learning technologies such as deep and reinforcement learning has proliferated in various domains with the advancement of deep neural network studies. To make the learning successful, both big data acquisition and fast processing are required. However, for some physical world applications such as autonomous drone flight, it is difficult to achieve efficient learning because learning with a premature A.I. is dangerous, cost-ineffective, and time-consuming. To solve these problems, simulation-based approaches can be considered. In this study, we analyze recent trends in drone simulation technologies and compare their features. Subsequently, we introduce Octopus, which is a highly precise and scalable drone simulator being developed by ETRI.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.691-694
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• 2011

본 논문은 항공관제 시스템을 구성하는 핵심 시스템인 비행자료처리시스템(FDP: Flight Data Processing System)에서 적용되고 있는 비행계획 포스팅 기법을 효율적으로 관리하기 위한 자동 포스팅 메커니즘에 대해 제안하고 있다. 본 논문에서 제안하는 방식은 관제사의 항공기 관제중에 가장 빈번하고도 중요하게 활용되는 정보인 비행계획 포스팅 정보를 FDP에서 처리할 때 자동 포스팅 방식을 적용하여 관제사와 항공관제 시스템과의 연결을 최소화하고 이를 통해 효율적이고 집중적인 관제가 지속될 수 있도록 지원한다. 또한 FDP 시스템에서 포스팅을 관리하기 위한 프로세서를 분리하여 존재시킴으로서, 전자 스트립 뿐만 아니라 종이 스트립까지 지원하는 정책 설계가 가능하며 정책 수정시 반영이 용이하다는 장점이 존재한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.1
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• pp.39-48
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• 2003

A GPS translator system is used to get the precise and reliable trajectory data for the high dynamic test vehicles, such as missiles or artillery shells. The missile system with high dynamics, vibration and shock needs to determine its position and velocity in particular. The proposed GPS translator on the test vehicle receives GPS signals, amplifies, down-converts, digitally samples, BPSK modulates, up-converts them to S-band, and then retransmits them to the ground translator processing station. It has doppler variation and signal noise, so design method for resolving them is proposed. The performance of the translator is proved by environmental test and real flight test.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.151-161
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• 2011

PGA(Phase Gradient Autofocus) is a representative autofocus technique to improve the SAR(Synthetic Aperture Radar) image quality. PGA can estimate high order phase errors and have good robustness in noisy environments. However, PGA is not suitable to apply to the stripmap mode data directly because it is based on the spotlight mode operation. In this paper, the PGA implementation technique for stripmap mode data and the method of ROI(Region of Interest) selection that affects severely on PGA performance have been proposed. The proposed technique was verified by the point target simulation first, and was applied to the real SAR signal data acquired by the flight test. Finally, the significant improvements in focusing quality were shown in the processed SAR images using the proposed method.

• Journal of Astronomy and Space Sciences
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• v.15 no.2
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• pp.373-389
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• 1998

The test result of the X-ray observation system is presented which have been developed at Korea Astronomy Observatory for 3 years(1995 -1997). The instrument, which is composed of detector and signal processing parts, is designed for the future observations of compact X-ray sources. The performance of the instrument was tested by mounting on the two-stage Korean Sounding Rocket, which was launched from Taean rocket flight center on June 11 at 10:00 KST 1998. Telemetry data was received from individual parts of the instrument for 32 and 55.7 sec, respectively, since the launch of the rocket. In this paper, the result of the data analysis based on the received telemetry data and discussion about the performance of the instrument is reported.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.242-245
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• 2019

움직이는 UAV는 많은 위치에너지와 운동에너지를 가지므로 지상으로 추락하는 경우 많은 충격량을 가질 수 있다. 이는 인명피해로 연결될 수 있기 때문에 본 논문에서는 UAV 비행경로 상의 인구밀집지역을 위험구역으로 정의하였다. 기존의 UAV 경로비행은 사용자에 의해 미리 설정된 경로만을 운행하는 수동적인 형태였다. 일부 UAV는 경로비행 중 장애물을 회피하는 시스템 등 안전기능을 포함하고 있지만, 비행환경변화에 대응하기에는 부족하다. UAV 경로비행에 공공 데이터를 활용할 경우, 위험구역을 검출하고 회피비행을 수행할 수 있어서 비행환경변화에 대한 대응이 향상될 수 있다. 따라서 본 논문에서는 수집된 데이터를 활용하여 위험구역을 회피하는 최적경로 비행 방안을 제안한다. 실험결과, 제안하는 자동경로비행에서 목적지와 목적지에 따른 경로를 지정할 경우, 위험지역을 스스로 판단하여 최적 우회경로로 비행하는 것을 확인하였다. 추후 회피방안에 따라 비행하여 획득하는 영상의 질적 만족도를 높일 수 있는 방안을 연구할 예정이다.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.55-62
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• 2011

The precise orbit determination (POD) of low earth orbiter (LEO) has complied with its required positioning accuracy by the double-differencing of observations between International GNSS Service (IGS) and LEO to eliminate the common clock error of the global positioning system (GPS) satellites and receiver. Using this method, we also have achieved the 1 m positioning accuracy of Korea Multi-Purpose Satellite (KOMPSAT)-2. However double-differencing POD has huge load of processing the global network of lots of ground stations because LEO turns around the Earth with rapid velocity. And both the centimeter accuracy and the near real time (NRT) processing have been needed in the LEO POD applications--atmospheric sounding or urgent image processing--as well as the surveying. An alternative to differential GPS for high accuracy NRT POD is precise point positioning (PPP) to use measurements from one satellite receiver only, to replace the broadcast navigation message with precise post processed values from IGS, and to have phase measurements of dual frequency GPS receiver. PPP can obtain positioning accuracy comparable to that of differential positioning. KOMPSAT-5 has a precise dual frequency GPS flight receiver (integrated GPS and occultation receiver, IGOR) to satisfy the accuracy requirements of 20 cm positioning accuracy for highly precise synthetic aperture radar image processing and to collect GPS radio occultation measurements for atmospheric sounding. In this paper we obtained about 3-5 cm positioning accuracies using the real GPS data of the Gravity Recover and Climate Experiment (GRACE) satellites loaded the Blackjack receiver, a predecessor of IGOR. And it is important to reduce the latency of orbit determination processing in the NRT POD. This latency is determined as the volume of GPS measurements. Thus changing the sampling intervals, we show their latency to able to reduce without the precision degradation as the assessment of their precision.

• Spatial Information Research
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• v.23 no.3
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• pp.91-100
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• 2015

We developed a micro UAV based rapid mapping system that provides geospatial information of target areas in a rapid and automatic way. Users can operate the system easily although they are inexperienced in UAV operation and photogrammetric processes. For the aerial data acquisition, we constructed a micro UAV system mounted with a digital camera, a GPS/IMU, and a control board for the sensor integration and synchronization. We also developed a flight planning software and data processing software for the generation of geo-spatial information. The processing software operates automatically with a high speed to perform data quality control, image matching, georeferencing, and orthoimage generation. With the system, we have generated individual ortho-images within 30 minutes from 57 images of 3cm resolution acquired from a target area of $400m{\times}300m$.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• Tunnel and Underground Space
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• v.25 no.6
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• pp.527-533
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• 2015

This study performed an on-site demonstration of the topographic surveying technique at a large-scale open-pit limestone mine in Korea using a fixed-wing unmanned aerial vehicle (UAV, Drone, SenseFly eBee). 288 sheets of aerial photos were taken by an automatic flight for 30 minutes under conditions of 300 m altitude and 12 m/s speed. Except for 37 aerial photos in which no keypoint was detected, 251 aerial photos were utilized for data processing including correction and matching, then an orthomosaic image and digital surface model with 7 cm grid spacing could be generated. A comparison of the X, Y, Z-coordinates of 4 ground control points measured by differential global positioning system and those determined by fixed-wing UAV photogrammetry revealed that the root mean squared errors were around 15 cm. Because the fixed-wing UAV has relatively longer flight time and larger coverage area than rotary-wing UAVs, it can be effectively utilized in large-scale open-pit mines as a topographic surveying tool.