• Title/Summary/Keyword: Orbit Anomaly

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Design and Development of MIMIC regarding Telemetry in LEO Satellites (저궤도 관측위성에서의 원격 측정 데이터 관련 MIMIC 설계 및 구현)

  • Huh, Yun-Goo;Kim, Young-Yun;Cho, Seung-Won;Choi, Jong-Yeoun
    • Aerospace Engineering and Technology
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    • v.11 no.1
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    • pp.42-48
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    • 2012
  • The telemetry data received from satellite in real-time are used to monitor LEO satellite during the AIT (Assembly, Integration & Test) phase and the mission operation phase after launch. However, it is impossible to check all the incoming telemetry data from satellite in real time in order to detect abnormality of satellite quickly. Especially, the contact time of LEO satellite is limited because of its orbital characteristics. So the anomaly state of the LEO satellite should be detected and resolved during the contact time. Therefore, all incoming spacecraft telemetry data must be selected and manipulated in MIMIC. It is used in order to display summarized information about spacecraft in a visualized way that is quickly and easily understood. That is, it provides essential function to monitor a satellite both in orbit and during testing. In this paper, the design and development of MIMIC currently used in KOMPSAT, a LEO Earth observation satellite is described in detail. In future work, we plan to enhance MIMIC in order to improve user-friendliness and efficiency.

Extraction of Ocean Surface Current Velocity Using Envisat ASAR Raw Data (Envisat ASAR 원시자료를 이용한 표층 해류 속도 추출)

  • Kang, Ki-Mook;Kim, Duk-Jin
    • Korean Journal of Remote Sensing
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    • v.29 no.1
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    • pp.11-20
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    • 2013
  • Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite's orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

Introduction and Evaluation of the Production Method for Chlorophyll-a Using Merging of GOCI-II and Polar Orbit Satellite Data (GOCI-II 및 극궤도 위성 자료를 병합한 Chlorophyll-a 산출물 생산방법 소개 및 활용 가능성 평가)

  • Hye-Kyeong Shin;Jae Yeop Kwon;Pyeong Joong Kim;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1255-1272
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    • 2023
  • Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

Sensitivity Experiment of Surface Reflectance to Error-inducing Variables Based on the GEMS Satellite Observations (GEMS 위성관측에 기반한 지면반사도 산출 시에 오차 유발 변수에 대한 민감도 실험)

  • Shin, Hee-Woo;Yoo, Jung-Moon
    • Journal of the Korean earth science society
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    • v.39 no.1
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    • pp.53-66
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    • 2018
  • The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.