[논문]Analysis of Inter-satellite Ranging Precision for Gravity Recovery in a Satellite Gravimetry Mission

Kim, Pureum; Park, Sang-Young; Kang, Dae-Eun; Lee, Youngro

doi:10.5140/jass.2018.35.4.243

Analysis of Inter-satellite Ranging Precision for Gravity Recovery in a Satellite Gravimetry Mission 원문보기

Journal of astronomy and space sciences, v.35 no.4, 2018년, pp.243 - 252

Kim, Pureum (Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University) , Park, Sang-Young (Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University) , Kang, Dae-Eun (Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University) , Lee, Youngro (Astrodynamics and Control Laboratory, Department of Astronomy, Yonsei University)

Abstract ▼ AI-Helper

In a satellite gravimetry mission similar to GRACE, the precision of inter-satellite ranging is one of the key factors affecting the quality of gravity field recovery. In this paper, the impact of ranging precision on the accuracy of recovered geopotential coefficients is analyzed. Simulated precise orbit determination (POD) data and inter-satellite range data of formation-flying satellites containing white noise were generated, and geopotential coefficients were recovered from these simulated data sets using the crude acceleration approach. The accuracy of the recovered coefficients was quantitatively compared between data sets encompassing different ranging precisions. From this analysis, a rough prediction of the accuracy of geopotential coefficients could be obtained from the hypothetical mission. For a given POD precision, a ranging measurement precision that matches the POD precision was determined. Since the purpose of adopting inter-satellite ranging in a gravimetry mission is to overcome the imprecision of determining orbits, ranging measurements should be more precise than POD. For that reason, it can be concluded that this critical ranging precision matching the POD precision can serve as the minimum precision requirement for an on-board ranging device. Although the result obtained herein is about a very particular case, this methodology can also be applied in cases where different parameters are used.

주제어

표/그림 (10)

표 Table 1. Orbital parameters of the satellites at epoch (February 21, 2011 23:58:45:000 UTC)
그림 Fig. 1. Low-rate inter-satellite range (top), range rate (middle), and range acceleration (bottom) as a function of hours since epoch, obtained from true high-rate range values.
표 Table 2. Gaussian noise sigmas used to simulate the noisy data
표 Table 3. Parameters for the CRN-class digital filter used in GRACE data processing and our simulation
그림 Fig. 2. Flowchart for the simulation process.
그림 Fig. 3. Averaged RMS coefficient differences per degree. Light-colored lines are drawn for each data set. Bright-colored lines are drawn by averaging the ten same light-colored lines. Smaller values imply more accurate coefficients. The RMS coefficients per degree of EGM96 are plotted as a black dotted line for comparison. Note that all values are unitless.
그림 Fig. 4. RMS coefficient differences per each coefficient for different one-sigma ranging precisions: (a) 10 mm (1e-5 km), (b) 1 mm (1e-6 km), (c) 100 μm (1e-7 km), and (d) 10 μm (1e-8 km). Smaller values imply more accurate coefficients. Note that all values are unitless.
표 Table 4. RMS geoid height diferences for all data sets
그림 Fig. 5. Map of geoid height differences for the worst data set among the ten sets sharing the same range noise sigma of (a) 10 mm (1e-5 km), (b) 1 mm (1e-6 km), (c) 100 μm (1e-7 km), and (d) 10 μm (1e-8 km).
그림 Fig. 6. Averaged RMS coefficient differences per degree, for the improved POD case. See Fig. 3 for a more detailed description.

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

First, the ‘true’ high-rate (100 Hz) position and velocity vectors (in the inertial J2000 frame) of each satellite and the ‘true’ high-rate range values were obtained by propagating their orbits with the help of GMAT.
From this study, it is possible to make a rough estimate on the accuracy of geopotential models that can be generated with the data of this hypothetical mission. Additionally, we can estimate the minimum measurement precision that its onboard ranging device must satisfy for the range measurements to be meaningful.
In this paper, we will cover the whole process of the simulation, from generating simulated data obtainable from the hypothetical ranging device and POD to extracting gravity fields from the simulated data, and then we will determine the minimum precision requirement for the ranging system. In Section 2, the theory of the crude acceleration approach is explained in detail.
In this study, geopotential coefficient recovery was performed on data sets generated and processed by assuming a hypothetical GRACE-like mission. The crude acceleration approach was used in recovering coefficients.
Instead, we used three different ways to quantify or visualize the differences between the ‘true’ gravitational coefficients and the obtained ones.
Also computable from this output are the ‘true’ ranges for the same time interval. Then we contaminated the true data to generate noisy data, which can be considered a proxy of the imprecise data we would have from POD and the on-board ranging system in a real-life mission. When GPS data is used in the POD process, it is natural that relative position and velocity between the satellites can be determined more precisely than with absolute values.

대상 데이터

The Gaussian noise sigmas used for our simulation are given in Table 2. For each range noise sigma, we made 10 sets of random simulation data, so in total, 40 data sets were made.

참고문헌 (33)

Choi MS, Lim HC, Choi EJ, Park E, Yu SY, et al., Performance analysis of the first Korean satellite laser ranging system, J. Astron. Space Sci. 31, 225-233 (2014). https://doi.org/10.5140/JASS.2014.31.3.225

원문보기 상세보기
Eun Y, Park SY, Kim GN, Development of a hardware-in-the-loop testbed to demonstrate multiple spacecraft operations in proximity, Acta Astronaut. 147, 48-58 (2018). https://doi.org/10.1016/j.actaastro.2018.03.030

상세보기
Flechtner F, Morton P, Watkins M, Webb F, Status of the GRACE follow-on mission, Proceedings of the International Association of Geodesy (IAU) Symposium GGHS2012, Venice, Italy, 9-12 Oct 2012.
Floberghagen R, Fehringer M, Lamarre D, Muzi D, Frommknecht B, et al., Mission design, operation and exploitation of the gravity field and steady-state ocean circulation explorer mission, J. Geodesy 85, 749-758 (2011). https://doi.org/10.1007/s00190-011-0498-3

상세보기
Flury J, Bettadpur S, Tapley BD, Precise accelerometry onboard the GRACE gravity field satellite mission, Adv. Space Res. 42, 1414-1423 (2008). https://doi.org/10.1016/j.asr.2008.05.004

상세보기
Gunter B, Ries J, Bettadpur S, Tapley B, A simulation study of the errors of omission and commission for GRACE RL01 gravity fields, J. Geodesy 80, 341-351 (2006). https://doi.org/10.1007/s00190-006-0083-3

상세보기
Han SC, Efficient determination of global gravity field from satellite-to-satellite tracking mission, Celest. Mech. Dyn. Astron. 88, 69-102 (2004). https://doi.org/10.1023/B:CELE.0000009383.07092.1f

상세보기
Heiskanen WA, Moritz H, Physical Geodesy (W. H. Freeman and Company, San Francisco, 1967).
Hoffman TL, GRAIL: gravity mapping the Moon, in 2009 IEEE Aerospace Conference, Big Sky, MT, 7-14 Mar 2009.
Hughes SP, General Mission Analysis Tool (GMAT), NASA Goddard Space Flight Center Technical Report, GSFC-E-DAA-TN29897 (2016).
Jo JH, Park IK, Lim HC, Seo YK, Yim HS, et al., The design concept of the first mobile satellite ranging system (ARGO-M) in Korea, J. Astron. Space Sci. 28, 93-102 (2011). https://doi.org/10.5140/JASS.2011.28.1.093

원문보기 상세보기
Jung S, Park SY, Park HE, Park CD, Kim SW, et al., Real-time determination of relative position between satellites using laser ranging, J. Astron. Space Sci. 29, 351-362 (2012). https://doi.org/10.5140/JASS.2012.29.4.351

원문보기 상세보기
Kim Y, Park SY, Lee E, Kim M, A deep space orbit determination software: overview and event prediction capability, J. Astron. Space Sci. 34, 139-151 (2017). https://doi.org/10.5140/JASS.2017.34.2.139

원문보기 상세보기
Kim YR, Park ES, Kucharski D, Lim HC, Orbit determination using SLR data for STSAT-2C: short-arc analysis, J. Astron. Space Sci. 32, 189-200 (2015). https://doi.org/10.5140/JASS.2015.32.3.189

원문보기 상세보기
Lee E, Park SY, Shin B, Cho S, Choi EJ, et al., Orbit determination of KOMPSAT-1 and Cryosat-2 satellites using Optical Wide-field Patrol Network (OWL-Net) data with batch least squares filter, J. Astron. Space Sci. 34 , 19-30 (2017a). https://doi.org/10.5140/JASS.2017.34.1.19

원문보기 상세보기
Lee E, Kim Y, Kim M, Park SY, Development, demonstration and validation of the deep space orbit determination software using lunar prospector tracking data, J. Astron. Space Sci. 34, 213-223 (2017b). https://doi.org/10.5140/JASS.2017.34.3.213

원문보기 상세보기
Lee J, Park SY, Kang DE, Relative navigation with intermittent laser-based measurement for spacecraft formation flying, J. Astron. Space Sci. 35, 163-173 (2018). https://doi.org/10.5140/JASS.2018.35.3.163

원문보기 상세보기
Lemoine FG, Kenyon SC, Factor JK, Trimmer RG, Pavlis NK, et al., The development of the joint NASA GSFC and the National Imagery and Mapping Agency (NIMA) geopotential model EGM96, NASA Goddard Space Flight Center Technical Report, NASA/TP-1998-206861 (1998).
Lim HC, Bang SC, Yu SY, Seo YK, Park ES, et al., Study on the optoelectronic design for Korean mobile satellite laser ranging system, J. Astron. Space Sci. 28, 155-162 (2011). https://doi.org/10.5140/JASS.2011.28.2.155

원문보기 상세보기
Mayer-Gurr T, Behzadpour S, Ellmer M, Kvas A, Klinger B, et al., ITSG-Grace2016 - Monthly and daily gravity field solutions from GRACE, GFZ Data Services (2016). https://doi.org/10.5880/icgem.2016.007
Oh H, Park HE, Lee K, Park SY, Park C, Improved GPS-based satellites relative navigation using femtosecond laser relative distance measurements, J. Astron. Space Sci. 33, 45-54 (2016). https://doi.org/10.5140/JASS.2016.33.1.45

원문보기 상세보기
Oh H, Park E, Lim HC, Lee SR, Choi JD, et al., Orbit determination of high-Earth-orbit satellites by satellite laser ranging, J. Astron. Space Sci. 34, 271-280 (2017). https://doi.org/10.5140/JASS.2017.34.4.271

원문보기 상세보기
Reigber C, Schmidt R, Flechtner F, Konig R, Meyer U, et al., An Earth gravity field model complete to degree and order 150 from GRACE: EIGEN-GRACE02S, J. Geodyn. 39, 1-10 (2005). https://doi.org/10.1016/j.jog.2004.07.001

상세보기
Ries J, Bettadpur S, Eanes R, Kang Z, Ko U, et al., The development and evaluation of the global gravity model GGM05, Center for Space Research at The University of Texas at Austin Technical Report, CSR-16-02 (2016).
Shang K, Guo J, Shum CK, Dai C, Luo J, GRACE time-variable gravity field recovery using an improved energy balance approach, Geophys. J. Int. 203, 1773-1786 (2015). https://doi.org/10.1093/gji/ggv392
Shin K, Oh H, Park SY, Park C, Real-time orbit determination for future Korean regional navigation satellite system, J. Astron. Space Sci. 33, 37-44 (2016). https://doi.org/10.5140/JASS.2016.33.1.37

원문보기 상세보기
Tapley BD, Bettadpur S, Watkins M, Reigber C, The gravity recovery and climate experiment: Mission overview and early results, Geophys. Res. Lett. 31, L09607 (2004). https://doi.org/10.1029/2004GL019920
Tapley BD, Ries J, Bettadpur S, Chambers D, Cheng M, et al., GGM02 - An improved Earth gravity field model from GRACE, J. Geodesy 79, 467-478 (2005). https://doi.org/10.1007/s00190-005-0480-z

상세보기
Thomas JB, An analysis of gravity-field estimation based on intersatellite dual-1-way biased ranging, Jet Propulsion Laboratory at California Institute of Technology Technical Report, JPL Publication 98-15 (1999).
Vallado DA, Fundamentals of astrodynamics and applications, 4th edition (Microcosm Press, Hawthorne, 2013).
Wei Z, Houtse H, Min Z, Meijuan Y, Xuhua Z, Effect of different inter-satellite range on measurement precision of Earth's gravitational field from GRACE, Geodesy Geodyn. 3, 44-51 (2012). https://doi.org/10.3724/SP.J.1246.2012.00044

상세보기
Weigelt M, The acceleration approach, in Global gravity field modeling from satellite-to-satellite tracking data, eds. Naeimi M, Flury J (Springer, Cham, 2017), 97-126.
Wu SC, Kruizinga G, Bertiger W, Algorithm theoretical basis document for GRACE Level-1B data processing V1.2, Jet Propulsion Laboratory at California Institute of Technology Technical Report, GRACE 327-741 (JPL D-27672) (2006)

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

용어 설명 출처 목록 (6)

용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증