{"title":"COSMIC/FORMOSAT: Ionospheric Weather Observed by GNSS Radio Occultation","authors":"T. Liu","doi":"10.33012/2019.16858","DOIUrl":"https://doi.org/10.33012/2019.16858","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130786969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Step-Based Attitude Update (SBUPT) Technique for Pedestrian Dead Reckoning (PDR) using Handheld Devices","authors":"M. Khedr, Ahmed Radi, N. El-Sheimy","doi":"10.33012/2019.16825","DOIUrl":"https://doi.org/10.33012/2019.16825","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134456603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hridayangam Jain, S. Lo, Yu‐Hsuan Chen, F. Rothmaier, J. Powell
Using direction of arrival (DOA) for GNSS spoof detection has several desirable properties. First, DOA-based spoof detection makes any spoofing from a single antenna very detectable regardless of how sophisticated its generation. It is difficult for a GNSS spoofer to create different DOAs as it generally requires transmitting from different locations, simultaneously. Thus, it forces a spoofer to utilize a much more complicated transmission system than a single antenna to create signals that can deceive DOA-based spoof detection. Second, it is complementary to and independent of other commonly used GNSS spoof detection methods thus providing additional layer of protection and certitude to detection. To utilize this method, we need means of getting DOA measurements of GNSS signals, preferably one that is both simple and has small form factor equipment. Controlled reception pattern antenna (CRPA) and dual polarization antenna (DPA) are two means of making such measurements [1][2]. While simple, low-profile methods such as the DPA and a two-element antenna are preferred, these methods result in ambiguity in measured direction of arrivals. DPA measurements have a 180degree ambiguity while two-element antennas have a symmetric ambiguity in DOA along the axis between the two antennas. The ambiguity can affect detection performance and limit the utility of such a system. This paper examines the ambiguity issue, focused on the DPA. It examines and develops a processing method to handle the ambiguity. First, we create two separate cases from the ambiguous measurements – a best genuine and a best spoof case. From these cases, we develop tests to examine each case and their likelihood. We use the processing results of both cases to manage the ambiguity. The processing method is tested and demonstrated using simulations and data from on-air tests in both nominal and spoofing conditions.
{"title":"Accommodating Direction Ambiguities in Direction of Arrival based GNSS Spoof Detection","authors":"Hridayangam Jain, S. Lo, Yu‐Hsuan Chen, F. Rothmaier, J. Powell","doi":"10.33012/2019.16784","DOIUrl":"https://doi.org/10.33012/2019.16784","url":null,"abstract":"Using direction of arrival (DOA) for GNSS spoof detection has several desirable properties. First, DOA-based spoof detection makes any spoofing from a single antenna very detectable regardless of how sophisticated its generation. It is difficult for a GNSS spoofer to create different DOAs as it generally requires transmitting from different locations, simultaneously. Thus, it forces a spoofer to utilize a much more complicated transmission system than a single antenna to create signals that can deceive DOA-based spoof detection. Second, it is complementary to and independent of other commonly used GNSS spoof detection methods thus providing additional layer of protection and certitude to detection. To utilize this method, we need means of getting DOA measurements of GNSS signals, preferably one that is both simple and has small form factor equipment. Controlled reception pattern antenna (CRPA) and dual polarization antenna (DPA) are two means of making such measurements [1][2]. While simple, low-profile methods such as the DPA and a two-element antenna are preferred, these methods result in ambiguity in measured direction of arrivals. DPA measurements have a 180degree ambiguity while two-element antennas have a symmetric ambiguity in DOA along the axis between the two antennas. The ambiguity can affect detection performance and limit the utility of such a system. This paper examines the ambiguity issue, focused on the DPA. It examines and develops a processing method to handle the ambiguity. First, we create two separate cases from the ambiguous measurements – a best genuine and a best spoof case. From these cases, we develop tests to examine each case and their likelihood. We use the processing results of both cases to manage the ambiguity. The processing method is tested and demonstrated using simulations and data from on-air tests in both nominal and spoofing conditions.","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133606385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Adaptive Method for BeiDou Dual-Frequency Joint Acquisition Based on SNR Estimation","authors":"Wuxun Zhang, Xin Chen, Di He, Yueming Yang","doi":"10.33012/2019.16799","DOIUrl":"https://doi.org/10.33012/2019.16799","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133987892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
1. A. E. Hedin, Extension of the MSIS Thermospheric Model into the Middle and Lower Atmosphere, J. Geophys. Res., 96, 1159, 1991. 2. Defense Mapping Agency (1987). Supplement to Department of Defense World Geodetic System 1984 Technical Report: Part I Methods, Techniques, and Data Used in WGS 84 Development. DMA Tech. Rep. 8350.2-A, Building 56, U.S. Naval Observatory, Washington, DC. 3. Dormand, J.R.; Prince, P.J. A family of embedded Runge–Kutta formulae. J. Comput. Appl. Math. 1980, 6, 19–26. 4. Emmert, J. T. (2009), A long-term data set of globally averaged thermospheric total mass density, J. Geophys. Res., 114, A06315, doi:10.1029/2009JA014102. 5. Jones, Brandon A. (2010). Efficient Models for the Evaluation and Estimation of the Gravity Field. Doctoral dissertation, University of Colorado, Boulder. http://ccar.colorado.edu/geryon/papers/Misc/bajones_phd.pdf 6. Kumar, M. (1988). "World Geodetic System 1984 a Modern and Accurate Global Reference Frame." Marine Geodesy 12(2): 117-126. 7. L. G. Jacchia, Revised Static Models of the Thermosphere and Exosphere with Empirical Temperature Profiles, Smithson. Astrophys. Obs. Spec. Rept. No. 332, 1971. 8. L. G. Jacchia, Static Diffusion Models of the Upper Atmosphere with Empirical Temperature Profiles, Smithson. Astrophys. Obs. Spec. Rept. No. 170, Cambridge, Massachusetts, 1964. 9. L. G. Jacchia, Thermospheric Temperature, Density, and Composition: New Models, Smithson. Astrophys. Obs. Spec. Rept. No. 375, 1977. 10.Liao, Edward Chi-Ting, Chang, Loren C., Chiang, Wen-Lung, Yeh, Ming-Yu, "Performance Assessment and Improvements for the FORMOSAT-5 Onboard Orbit Propagator Using GPS Ephemeris," Proceedings of the ION 2019 Pacific PNT Meeting, Honolulu, Hawaii, April 2019, pp. 199-205. https://doi.org/10.33012/2019.16804 11.Losch, M. and Seufer, V. (2003): How to Compute Geoid Undulations (Geoid Height Relative to a Given Reference Ellipsoid) from Spherical Harmonic Coefficients for Satellite Altimetry Applications 12.Marsh, J. G., et al., An improved model of the Earth's gravitational field: GEM-T1, NASA Tech. Memo., TM-4019, 1987. 13.Pavlis, N. K., Holmes, S. A., Kenyon, S. C., & Factor, J. K. (2012). The development and evaluation of the earth gravitational model 2008 (EGM2008). Journal of Geophysical Research, 117, B04406. https://doi.org/10.1029/2011JB008916 14.Shuster, Simon P., "A Survey and Performance Analysis of Orbit Propagators for LEO, GEO, and Highly Elliptical Orbits" (2017). All Graduate Theses and Dissertations. 6510. 15.Vallado, David A. 2007. Fundamentals of Astrodynamics and Applications. Third Edition. Microcosm, Hawthorne, CA. 16.Vallado, D.A., Finkleman, D., 2014. A critical assessment of satellite drag and atmospheric density modeling. Acta Astronautica 95 (1), 141–165. p. 1. ABSTRACT
1. A. E. Hedin, MSIS热层模式在中低层大气中的应用，地球物理学报。Res.， 96, 1159, 1991。2. 国防测绘局(1987年)。美国国防部1984年世界大地测量系统技术报告的补充:第一部分:WGS 84开发中使用的方法、技术和数据。DMA技术代表8350.2-A, 56号楼，美国海军天文台，华盛顿特区3.Dormand jr;嵌入龙格-库塔公式族。j .第一版。达成。数学。1980,6,19-26。4. Emmert, j.t.(2009)，全球平均热层总质量密度长期数据集[j] .地球物理学报。研究，114,A06315, doi:10.1029/2009JA014102。5. 琼斯，布兰登A.(2010)。重力场评估和估计的有效模型。博士论文，科罗拉多大学博尔德分校。http://ccar.colorado.edu/geryon/papers/Misc/bajones_phd.pdf 6。库马尔，M.(1988)。《1984年世界大地测量系统:现代和精确的全球参考系》海洋大地测量，12(2):117-126。7. L. G. Jacchia，基于经验温度分布的热层和外逸层静态模式的修正，中国科学院学报。12,54。奥林匹克广播服务公司。规范报告。1971年第332号。8. 李志刚，基于经验温度分布的大气静态扩散模式，中国科学院学报。12,54。奥林匹克广播服务公司。规范报告。第170号，剑桥，马萨诸塞州，1964年。9. L. G. Jacchia，热层温度、密度和组成:新模型，史密森。12,54。奥林匹克广播服务公司。规范报告。1977年第375号。10.廖志廷，张文龙，叶明宇，蒋文龙，“基于GPS星历的FORMOSAT-5星载轨道传播器性能评估与改进”，2019年太平洋PNT会议论文集，夏威夷，2019年4月，pp. 199-205。https://doi.org/10.33012/2019.16804 11。Losch, M.和Seufer, V.(2003):如何从卫星测高应用的球谐系数计算大地水准面波动(相对于给定参考椭球的大地水准面高度)12。Marsh, j.g.等，地球引力场的改进模型:GEM-T1, NASA技术备忘录。， tm-4019, 1987。13.Pavlis, n.k.， Holmes, s.a.， Kenyon, s.c.， & Factor, j.k.(2012)。地球引力模型2008 (EGM2008)的发展与评价。地球物理学报，33(4):444 - 444。https://doi.org/10.1029/2011JB008916 14。Shuster, Simon P.，“LEO, GEO和高椭圆轨道轨道传播器的调查和性能分析”(2017)。所有毕业论文和学位论文。15.David A. Vallado, 2007。天体动力学基础及其应用“，”第三版。加州霍桑市的“微观世界”。valallado, d.a.， Finkleman, D.， 2014。卫星阻力和大气密度模拟的关键评估。宇航学报，1995(1)，141-165。p。1。摘要
{"title":"Performance Assessment and Improvements for the FORMOSAT-5 Onboard Orbit Propagator Using GPS Ephemeris","authors":"Edward Chi-Ting Liao, L. Chang, W. Chiang, M. Yeh","doi":"10.33012/2019.16804","DOIUrl":"https://doi.org/10.33012/2019.16804","url":null,"abstract":"1. A. E. Hedin, Extension of the MSIS Thermospheric Model into the Middle and Lower Atmosphere, J. Geophys. Res., 96, 1159, 1991. 2. Defense Mapping Agency (1987). Supplement to Department of Defense World Geodetic System 1984 Technical Report: Part I Methods, Techniques, and Data Used in WGS 84 Development. DMA Tech. Rep. 8350.2-A, Building 56, U.S. Naval Observatory, Washington, DC. 3. Dormand, J.R.; Prince, P.J. A family of embedded Runge–Kutta formulae. J. Comput. Appl. Math. 1980, 6, 19–26. 4. Emmert, J. T. (2009), A long-term data set of globally averaged thermospheric total mass density, J. Geophys. Res., 114, A06315, doi:10.1029/2009JA014102. 5. Jones, Brandon A. (2010). Efficient Models for the Evaluation and Estimation of the Gravity Field. Doctoral dissertation, University of Colorado, Boulder. http://ccar.colorado.edu/geryon/papers/Misc/bajones_phd.pdf 6. Kumar, M. (1988). \"World Geodetic System 1984 a Modern and Accurate Global Reference Frame.\" Marine Geodesy 12(2): 117-126. 7. L. G. Jacchia, Revised Static Models of the Thermosphere and Exosphere with Empirical Temperature Profiles, Smithson. Astrophys. Obs. Spec. Rept. No. 332, 1971. 8. L. G. Jacchia, Static Diffusion Models of the Upper Atmosphere with Empirical Temperature Profiles, Smithson. Astrophys. Obs. Spec. Rept. No. 170, Cambridge, Massachusetts, 1964. 9. L. G. Jacchia, Thermospheric Temperature, Density, and Composition: New Models, Smithson. Astrophys. Obs. Spec. Rept. No. 375, 1977. 10.Liao, Edward Chi-Ting, Chang, Loren C., Chiang, Wen-Lung, Yeh, Ming-Yu, \"Performance Assessment and Improvements for the FORMOSAT-5 Onboard Orbit Propagator Using GPS Ephemeris,\" Proceedings of the ION 2019 Pacific PNT Meeting, Honolulu, Hawaii, April 2019, pp. 199-205. https://doi.org/10.33012/2019.16804 11.Losch, M. and Seufer, V. (2003): How to Compute Geoid Undulations (Geoid Height Relative to a Given Reference Ellipsoid) from Spherical Harmonic Coefficients for Satellite Altimetry Applications 12.Marsh, J. G., et al., An improved model of the Earth's gravitational field: GEM-T1, NASA Tech. Memo., TM-4019, 1987. 13.Pavlis, N. K., Holmes, S. A., Kenyon, S. C., & Factor, J. K. (2012). The development and evaluation of the earth gravitational model 2008 (EGM2008). Journal of Geophysical Research, 117, B04406. https://doi.org/10.1029/2011JB008916 14.Shuster, Simon P., \"A Survey and Performance Analysis of Orbit Propagators for LEO, GEO, and Highly Elliptical Orbits\" (2017). All Graduate Theses and Dissertations. 6510. 15.Vallado, David A. 2007. Fundamentals of Astrodynamics and Applications. Third Edition. Microcosm, Hawthorne, CA. 16.Vallado, D.A., Finkleman, D., 2014. A critical assessment of satellite drag and atmospheric density modeling. Acta Astronautica 95 (1), 141–165. p. 1. ABSTRACT","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116656717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Angermann, S. Wolkow, Andreas Dekiert, U. Bestmann, P. Hecker
{"title":"Linear Blend: Data Fusion in the Image Domain for Image-based Aircraft Positioning during Landing Approach","authors":"M. Angermann, S. Wolkow, Andreas Dekiert, U. Bestmann, P. Hecker","doi":"10.33012/2019.16836","DOIUrl":"https://doi.org/10.33012/2019.16836","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129188549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When designing a GNSS conference, one of the first steps is having individuals determine a set of tracks and sessions that are most likely to cover the topic areas of interest by those writing and submitting papers. While these decisions are made by experts in the field, it can be difficult to anticipate what topics will capture the attention of researchers and industry around the world. Furthermore, when submitting a paper, it can be hard to decide what sessions to submit a paper to when the work might lie at the intersection of several fields. As a first step to creating tools to helping the ION conference organizers decide on sessions for a conference and identifying papers that should be grouped together, this paper explores the ability to see trends in past data using commercially available natural language processing tools. Specifically, the abstract and title data for accepted papers from ION GNSS+ 2007-2018 are analyzed for different trends and patterns that can help inform future conference organization.
{"title":"Paper Trends in ION Conferences from 2007 - 2018","authors":"A. Perkins, Todd Walter","doi":"10.33012/2019.16790","DOIUrl":"https://doi.org/10.33012/2019.16790","url":null,"abstract":"When designing a GNSS conference, one of the first steps is having individuals determine a set of tracks and sessions that are most likely to cover the topic areas of interest by those writing and submitting papers. While these decisions are made by experts in the field, it can be difficult to anticipate what topics will capture the attention of researchers and industry around the world. Furthermore, when submitting a paper, it can be hard to decide what sessions to submit a paper to when the work might lie at the intersection of several fields. As a first step to creating tools to helping the ION conference organizers decide on sessions for a conference and identifying papers that should be grouped together, this paper explores the ability to see trends in past data using commercially available natural language processing tools. Specifically, the abstract and title data for accepted papers from ION GNSS+ 2007-2018 are analyzed for different trends and patterns that can help inform future conference organization.","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122137198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Future Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is expected to bring significant global navigation performance improvement to civil aviation. Currently, the ARAIM research activities are led by a joint working group of the United States (U.S.) and the European Union (E.U.), which focuses on dual-constellation scenario using the Global Positioning System (GPS) and Galileo. However, even though the BeiDou System (BDS) and GLONASS had achieved remarkable developments in recent years, there had been no comprehensive exploration on their potential benefits to ARAIM. In response, this paper investigates the achievable ARAIM service capability and robustness using more than two full Global Navigation Satellite Systems (GNSS) constellations. Moreover, the key issues with the current baseline ARAIM user algorithm under the new operational scenarios are identified. It is shown that due to the exponentially increased number of monitored satellite subsets, the computational load can be significantly increased when additional constellations are employed. To mitigate this impact, an efficient Fault Detection and Exclusion (FDE) algorithm is rigorously developed by grouping multiple fault hypotheses. To accommodate the non-equal performance levels among the constellations, a series of sensitivity analyses are carried out using variable Integrity Support Message (ISM) values, and the results are presented in terms of availability.
{"title":"ARAIM with More than two Constellations","authors":"Y. Zhai, X. Zhan, Jin Chang, B. Pervan","doi":"10.33012/2019.16849","DOIUrl":"https://doi.org/10.33012/2019.16849","url":null,"abstract":"Future Advanced Receiver Autonomous Integrity Monitoring (ARAIM) is expected to bring significant global navigation performance improvement to civil aviation. Currently, the ARAIM research activities are led by a joint working group of the United States (U.S.) and the European Union (E.U.), which focuses on dual-constellation scenario using the Global Positioning System (GPS) and Galileo. However, even though the BeiDou System (BDS) and GLONASS had achieved remarkable developments in recent years, there had been no comprehensive exploration on their potential benefits to ARAIM. In response, this paper investigates the achievable ARAIM service capability and robustness using more than two full Global Navigation Satellite Systems (GNSS) constellations. Moreover, the key issues with the current baseline ARAIM user algorithm under the new operational scenarios are identified. It is shown that due to the exponentially increased number of monitored satellite subsets, the computational load can be significantly increased when additional constellations are employed. To mitigate this impact, an efficient Fault Detection and Exclusion (FDE) algorithm is rigorously developed by grouping multiple fault hypotheses. To accommodate the non-equal performance levels among the constellations, a series of sensitivity analyses are carried out using variable Integrity Support Message (ISM) values, and the results are presented in terms of availability.","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117265133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Stallo, P. Salvatori, A. Coluccia, M. Capozzi, G. Gamba, E. Cianca, T. Rossi, S. D. Domenico, A. Neri, F. Rispoli, M. Ciaffi
{"title":"Intelligent Antennas for Mitigating GNSS Jamming & Spoofing Hazards on the ERTMS Train Control","authors":"C. Stallo, P. Salvatori, A. Coluccia, M. Capozzi, G. Gamba, E. Cianca, T. Rossi, S. D. Domenico, A. Neri, F. Rispoli, M. Ciaffi","doi":"10.33012/2019.16818","DOIUrl":"https://doi.org/10.33012/2019.16818","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123072794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Ugazio, Kevin Croissant, Brian C. Peters, F. Graas
{"title":"Bobcat-1: The Ohio University CubeSat for Inter-Constellation Time Offset Determination","authors":"S. Ugazio, Kevin Croissant, Brian C. Peters, F. Graas","doi":"10.33012/2019.16808","DOIUrl":"https://doi.org/10.33012/2019.16808","url":null,"abstract":"","PeriodicalId":201935,"journal":{"name":"Proceedings of the ION 2019 Pacific PNT Meeting","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128776229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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