D. Corry, D. Gleeson, M. Martin, J. Murphy, P. O'Connor, A. O'Grady, P. Reynolds, J. Ward
{"title":"5.4 Utilising an Autonomous Video Kit for Launcher to Video Deployment of the James Webb Space Telescope","authors":"D. Corry, D. Gleeson, M. Martin, J. Murphy, P. O'Connor, A. O'Grady, P. Reynolds, J. Ward","doi":"10.5162/ettc2022/5.4","DOIUrl":"https://doi.org/10.5162/ettc2022/5.4","url":null,"abstract":"","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133647904","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}
: The latest developments in the GNSS precise positioning and timing receivers from JAVAD GNSS include the option to replace the classical TCXO (Temperature Compensated Crystal Oscillator) by an OCXO (Oven Controlled Crystal Oscillator). This internal OCXO delivers an unmachted short term frequency stability 2x10-12 (@1sec) and 5x10-12 (@10sec). The position and timing signals measured using this OCXO will have great advantages, especially for flight test measurements with high dynamics or ionosphere scintillation measurements both requiring high update rates for raw measurement and positioning (up to 200Hz supported). For the long term frequency stability, the latest JAVAD GNSS receivers have the ability to precisely synchronize the internal receiver clock with external 1 PPS signal without any additional equipment. In this mode the receiver uses the external frequency as the reference, but the time offset between 1 PPS and 10 MHz signal is measured inside the receiver and can be recorded. All the observations are performed in the epoch defined by an incoming 1 PPS signal. Receiver synchronizes its internal time scale to input 1 PPS signal with accuracy less or equal 0.4 ns, without any external time interval counter. This is the optimal solution for network timing or to synchronize FTI.
{"title":"3.5 New developments for GNSS precise positioning and timing","authors":"M. Schulz, J. Rüffer","doi":"10.5162/ettc2022/3.5","DOIUrl":"https://doi.org/10.5162/ettc2022/3.5","url":null,"abstract":": The latest developments in the GNSS precise positioning and timing receivers from JAVAD GNSS include the option to replace the classical TCXO (Temperature Compensated Crystal Oscillator) by an OCXO (Oven Controlled Crystal Oscillator). This internal OCXO delivers an unmachted short term frequency stability 2x10-12 (@1sec) and 5x10-12 (@10sec). The position and timing signals measured using this OCXO will have great advantages, especially for flight test measurements with high dynamics or ionosphere scintillation measurements both requiring high update rates for raw measurement and positioning (up to 200Hz supported). For the long term frequency stability, the latest JAVAD GNSS receivers have the ability to precisely synchronize the internal receiver clock with external 1 PPS signal without any additional equipment. In this mode the receiver uses the external frequency as the reference, but the time offset between 1 PPS and 10 MHz signal is measured inside the receiver and can be recorded. All the observations are performed in the epoch defined by an incoming 1 PPS signal. Receiver synchronizes its internal time scale to input 1 PPS signal with accuracy less or equal 0.4 ns, without any external time interval counter. This is the optimal solution for network timing or to synchronize FTI.","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115496745","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}
In the past years, Airbus Group has been investing into Big Data by developing and setting up infrastructures and backends which have already been presented in various papers. The platform has now reached sufficient maturity to be usable for concrete work and while work is continuing on the backends to improve performance and features, the emphasis is gradually shifting towards end-user tools and operational use cases, among others in the testing domain. New possibilities are appearing, but it also requires some changes in mindsets as commonly used approaches and habits need to be challenged. This paper will discuss these aspects, focusing on tests performed during development and covering in particular:
{"title":"7.4 Big Data Tooling and Usage Perspectives in the Airbus Helicopters Test Center","authors":"N. Brisset","doi":"10.5162/ettc2022/7.4","DOIUrl":"https://doi.org/10.5162/ettc2022/7.4","url":null,"abstract":"In the past years, Airbus Group has been investing into Big Data by developing and setting up infrastructures and backends which have already been presented in various papers. The platform has now reached sufficient maturity to be usable for concrete work and while work is continuing on the backends to improve performance and features, the emphasis is gradually shifting towards end-user tools and operational use cases, among others in the testing domain. New possibilities are appearing, but it also requires some changes in mindsets as commonly used approaches and habits need to be challenged. This paper will discuss these aspects, focusing on tests performed during development and covering in particular:","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128656313","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":"9.4 TABAI. Test Assistant Based on Artificial Intelligence","authors":"F. Coll Herrero, P. Rubio Alvarez","doi":"10.5162/ettc2022/9.4","DOIUrl":"https://doi.org/10.5162/ettc2022/9.4","url":null,"abstract":"","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258358","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":"5.2 A400M Image Processing Methodology to Calculate Relative Speed in Air to Air Refuelling","authors":"I. López Herreros","doi":"10.5162/ettc2022/5.2","DOIUrl":"https://doi.org/10.5162/ettc2022/5.2","url":null,"abstract":"","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126762634","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}
K. Lutz, L. Greda, M. Smyrnaios, W. Dilg, T. Schilling, I. Ioanid, J. Furthner, S. Thölert, G. Allende Alba, M. Kriegel, L. Spataro, P. Rosauer, A. Meinecke, A. Brydon
: Satellite navigation has become a vital part of our daily lives by ensuring navigation on land, in air and at sea, and by providing precise timing information for the energy, communications and finance sector. It is therefore essential to monitor the performance of the four main global navigation satellite systems (GNSS) Galileo, GPS, GLONASS and BeiDou. The Galileo Competence Center (GK), part of the German Aerospace Center (DLR), is dedicated to the further development of the European GNSS consisting of Galileo and EGNOS. Within the SigPerMon project, the GK monitors the reliability and quality of navigation signals with comparable metrics for all four GNSS, and detects deviations from the nominal state of navigation systems. Necessary data are sourced from a global network of GNSS receiver stations. These data are used to compute performance indicators to monitor and analyse the availability and health status of navigation signals, and the precision of positioning and timing solutions. In the future, machine learning models will be used to detect anomalies in the satellite signals. A summary of the results will be presented on a dedicated webpage, which provides both detailed analyses for authorized researchers and personnel, and interactive data visualizations for the general public.
{"title":"3.4 Performance Monitoring for Galileo and other GNSS at the Galileo Competence Center","authors":"K. Lutz, L. Greda, M. Smyrnaios, W. Dilg, T. Schilling, I. Ioanid, J. Furthner, S. Thölert, G. Allende Alba, M. Kriegel, L. Spataro, P. Rosauer, A. Meinecke, A. Brydon","doi":"10.5162/ettc2022/3.4","DOIUrl":"https://doi.org/10.5162/ettc2022/3.4","url":null,"abstract":": Satellite navigation has become a vital part of our daily lives by ensuring navigation on land, in air and at sea, and by providing precise timing information for the energy, communications and finance sector. It is therefore essential to monitor the performance of the four main global navigation satellite systems (GNSS) Galileo, GPS, GLONASS and BeiDou. The Galileo Competence Center (GK), part of the German Aerospace Center (DLR), is dedicated to the further development of the European GNSS consisting of Galileo and EGNOS. Within the SigPerMon project, the GK monitors the reliability and quality of navigation signals with comparable metrics for all four GNSS, and detects deviations from the nominal state of navigation systems. Necessary data are sourced from a global network of GNSS receiver stations. These data are used to compute performance indicators to monitor and analyse the availability and health status of navigation signals, and the precision of positioning and timing solutions. In the future, machine learning models will be used to detect anomalies in the satellite signals. A summary of the results will be presented on a dedicated webpage, which provides both detailed analyses for authorized researchers and personnel, and interactive data visualizations for the general public.","PeriodicalId":193365,"journal":{"name":"Proceedings - ettc2022","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121966201","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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