• Title/Summary/Keyword: Deep Space

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A Study on the System Design for Deep-Space Probe Reference Model (표준 심우주 탐사선 시스템 설계 연구)

  • Euikeun Kim;Hyeon-Jin Jeon
    • Journal of Space Technology and Applications
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    • v.3 no.1
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    • pp.44-57
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    • 2023
  • In order for a latecomer in deep-space exploration such as Korea to quickly keep pace with advanced deep-space exploration countries in the mutually-beneficial space exploration market, it is essential to derive a deep-space probe reference model that can reduce development period and cost. In this paper, concept and configuration for the deep-space probe reference model consisting of basic, lightweight, and expansion types are newly presented, which are based on commonly required designs for various deep-space probes. The proposed configuration adopts modular design so that the expandability and design/implementation efficiency are improved. In addition, the electrical system design pursuing lightweight and expandability is also described, which is applicable to the proposed three-types of deep-space probe reference model.

DeepSDO: Solar event detection using deep-learning-based object detection methods

  • Baek, Ji-Hye;Kim, Sujin;Choi, Seonghwan;Park, Jongyeob;Kim, Jihun;Jo, Wonkeum;Kim, Dongil
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.2
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    • pp.46.2-46.2
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    • 2021
  • We present solar event auto detection using deep-learning-based object detection algorithms and DeepSDO event dataset. DeepSDO event dataset is a new detection dataset with bounding boxed as ground-truth for three solar event (coronal holes, sunspots and prominences) features using Solar Dynamics Observatory data. To access the reliability of DeepSDO event dataset, we compared to HEK data. We train two representative object detection models, the Single Shot MultiBox Detector (SSD) and the Faster Region-based Convolutional Neural Network (R-CNN) with DeepSDO event dataset. We compared the performance of the two models for three solar events and this study demonstrates that deep learning-based object detection can successfully detect multiple types of solar events. In addition, we provide DeepSDO event dataset for further achievements event detection in solar physics.

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Analysis of effectiveness of solar system internet to deep space exploration (태양계 인터넷이 심우주 탐사에 미치는 영향 분석)

  • Koo, Cheolhea;Kim, Changkyun;Rew, Dongyoung;Choi, Gihyuk
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.3
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    • pp.240-246
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    • 2016
  • The hottest news and achievements of space science and research in recent years may be NASA Curiosity rover's exploration (2013) of Mars, China Chang'e 3's exploration (2013) of Moon, ESA Rosetta's exploration (2014) of Comet 67P/Churyumov-Gerasimenko, and NASA New Horizons' exploration (2015) of Pluto, which are very astonishing achievement since such a deep space journey was possible with current technology. In contrast the wonderful cruise and navigation technologies evolution of explorer in deep space, there are no remarkable changes in deep space data communication, it is still in conservative area, of which much changes are reluctantly accepted so far. But there are some movements of deep space exploration in order to allow ground brilliant technologies to deep space. One of those experiments is internet, whose main topic of this paper. In this paper, we will present the analysis of effectiveness of solar system internet to deep space exploration.

DEEP-South: 2nd phase of observations for small Solar System bodies

  • Kim, Myung-Jin;Choi, Young-Jun;Yang, Hongu;Lee, Hee-Jae;Kim, Dong-Heun;JeongAhn, Youngmin;Roh, Dong-Goo;Moon, Hong-Kyu;Chang, Chan-Kao;Durech, Josef;Broz, Miroslav;Hanus, Josef;Masiero, Joseph;Mainzer, Amy;Bauer, James
    • The Bulletin of The Korean Astronomical Society
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    • v.45 no.1
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    • pp.46.1-46.1
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    • 2020
  • DEEP-South (DEep Ecliptic Patrol of the Southern Sky) team will start the 2nd phase of KMTNet observation in Oct 2020. The DEEP-South observation mainly consists of three survey modes: (1) Activity survey (AS) that aims at finding active phenomena of small Solar System bodies. (2) Light curve survey (LS) targets to discover and characterize light variations of asteroids. And (3) Deep drilling survey (DS) focuses on the objects beyond the orbit of Jupiter (Centaurus and trans-Neptunian objects) as well as near Earth asteroids. For asteroid family (AF) studies and target of opportunity (TO) observations for urgent photometric follow-up, targeted mode will also be used. DEEP-South team is awarded 7.0% of the telescope time at each site every year from Oct 2020 to Sep 2023 in the 2nd phase of KMTNet operation which corresponds to about 75 full nights a year for the network. In this presentation, we will introduce our survey strategy and observation plan.

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Multi-wavelength Extragalactic Studies in the AKARI Deep Field - South

  • Jeong, Woong-Seob;Kim, Minjin;Ko, Jongwan;Park, Sung-Joon;Ko, Kyeongyeon;Jo, Youngsoo;Lee, Min Gyu;Seo, Hyun Jong;Kim, Taehyun;Pyo, Jeonghyun;Lee, Dongseob;Kim, Il-Joong
    • The Bulletin of The Korean Astronomical Society
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    • v.43 no.2
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    • pp.31.4-32
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    • 2018
  • The ADF-S (AKARI Deep Field - South) toward South Ecliptic Pole is one of the deep survey fields designed for the study of Cosmic Infrared Background (CIB). Owing to the easy accessibility with space missions and its low background brightness, the deep extragalactic survey was initiated by AKARI deep far-infrared observations and it will be performed by other future missions (e.g., Euclid, NISS, SPHEREx). The recent optical survey with KMTNet enabled us to identify the optical counterparts for dusty star-forming galaxies such as ULIRG, DOG, SMG. In addition, the NISS will perform the valuable spectro-photometric survey in the ADF-S. Those multi-wavelength data sets helps to trace the major galaxy population contributing to the CIB. Here, we introduce the extragalactic survey with the NISS and report the current status of the multi-wavelength extragalactic studies in the ADF-S.

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DEEP-South: Lightcurves of Near Earth Asteroids from Year One Operations

  • Kim, Myung-Jin;Moon, Hong-Kyu;Choi, Young-Jun;Yim, Hong-Suh;Park, Jintae;Roh, Dong-Goo;Lee, Hee-Jae;Oh, Young-Seok;Choi, Jung-Yong;Bae, Young-Ho
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.2
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    • pp.49.3-50
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    • 2016
  • Deep Ecliptic Patrol of the Southern Sky (DEEP-South) observations have been conducted officially during the off-season for exoplanet search since October 2015. Most of the allocated time for DEEP-South is devoted to targeted photometry, Opposition Census (OC), of Near Earth Asteroids (NEAs) to increase the number of such objects with known physical properties. It is efficiently achieved by multiband, time series photometry. This Opposition Census (OC) mode target objects near their opposition, with km-sized PHAs in the early stage and goes down to sub-km objects. Continuous monitoring of the sky with KMTNet is optimized for spin characterization of various kinds of asteroids, including binaries, satellites, slow/fast- and non-principal axis-rotators, and hence is expected to facilitate the debiasing of previously reported lightcurve observations. We present the preliminary lightcurves of NEAs from year one of the DEEP-South with our long term plan.

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Design and Verification of Spacecraft Pose Estimation Algorithm using Deep Learning

  • Shinhye Moon;Sang-Young Park;Seunggwon Jeon;Dae-Eun Kang
    • Journal of Astronomy and Space Sciences
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    • v.41 no.2
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    • pp.61-78
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    • 2024
  • This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

Properties of High-Redshift Dust-Obscured Galaxies Revealed in the ADF-S

  • Kim, Seongjae;Jeong, Woong-Seob;Park, Daeseong;Kim, Minjin;Hwang, Hoseong;Park, Sung-Joon;Ko, Kyeongyeon;Seo, Hyun Jong
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.62.2-62.2
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    • 2019
  • The ADF-S (AKARI Deep Field - South) toward South Ecliptic Pole is one of the deep survey fields designed for the study of Extragalactic Background Light (EBL). The deep extragalactic survey was initiated by AKARI far-infrared deep observations. Other space missions (e.g., Euclid, NISS, SPHEREx) will perform the deep observations in the ADF-S. Based upon the recent optical survey with KMTNet, we can identify the optical counterparts for dusty star-forming galaxies such as ULIRG, DOG, SMG. Among them, the Dust-Obscured Galaxies (hereafter DOGs with f(24um)/f(R) > 1,000) in the heavily obscured system are expected to play an important role in the formation of most massive galaxies. We have newly discovered ~100 DOGs in ~12 sq. deg. of the ADF-S from our optical survey with KMTNet. We also confirmed that some of DOGs host the most luminous AGN for their black hole masses through the near-infrared spectroscopic follow-ups. Here, we report the properties of high-z hyperluminous DOGs in the ADF-S.

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Ground Stations of Korean Deep Space Network for Lunar Explorations (달 탐사를 위한 한국형 심우주 지상국)

  • Kim, Sang-Goo;Yoon, Dong-Weon;Hyun, Kwang-Min
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.5
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    • pp.499-506
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    • 2010
  • Many countries of the world have been launched the competition of space development and Korea also has a plan for the launch of Lunar orbiter in 2020 and Lunar lander in 2025 for Lunar explorations. For the success of the planned Lunar exploration, we need to enhance the required deep space communication technologies. To achieve our goals, we should develop space communications system and Korean DSN (deep space network) based on experiences and technologies through cooperation with the advanced countries in the field of deep space exploration. In this paper, we investigate overseas DSNs and deep space communication systems, and present the link margin and other technical requirements for successful DSN deployment. In addition, we propose a best strategy to secure domestic ground stations for the Korean Lunar exploration missions.

Deep Space Observatory Technology using Satellite (인공위성을 이용한 심우주 관측 기술)

  • Yoon, Yong-Sik
    • Aerospace Engineering and Technology
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    • v.12 no.2
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    • pp.64-73
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    • 2013
  • In order to observe the deep space more efficiently, a satellite installed with a telescope on earth is needed. Advanced countries in space such as U.S.A and E.U. etc. have obtained and analyzed informations and images of the space from Hubble telescope, Kepler space observatory and Herschel space observatory. This paper studied specifications and operation status of space observation satellite of the several foreign countries and described technologies and plans for the domestic deep space observation satellite.