{"title":"一个客观优化的地球观测系统","authors":"David John Lary","doi":"10.1109/AERO.2007.353089","DOIUrl":null,"url":null,"abstract":"This paper describes one vision for future Earth observing systems. New in this vision is the desire for symbiotic communication to dynamically guide an observation system. An earth observation system which is not just a single satellite acting on its own but a constellation of satellites, and sub-orbital platforms such as unmanned aerial vehicles, and ground observations interacting with computer systems used for modeling, data analysis and dynamic observation guidance. An autonomous objectively optimized observation direction system (OOODS) is of great utility for earth observation. In particular, to have a fleet of smart assets that can be reconfigured based on the changing needs of science and technology. The OOODS integrates a modeling and assimilation system within the sensor web allowing the autonomous scheduling of the chosen assets and the autonomous provision of analyses to users. The OOODS operates on generic principles that could easily be used in configurations other than the specific examples described here. Metrics of what we do not know (state vector uncertainty) are used to define what we need to measure and the required mode, time and location of the observations, i.e. to define in real time the observing system targets. Metrics of how important it is to know this information (information content) are used to assign a priority to each observation. The metrics are passed in real time to the sensor web observation scheduler to implement the observation plan for the next observing cycle. The same system could also be used to reduce the cost and development time in an observation sensitivity simulation experiment (OSSE) mode for the optimum development of the next generation of space and ground-based observing systems.","PeriodicalId":6295,"journal":{"name":"2007 IEEE Aerospace Conference","volume":"4 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"An Objectively Optimized Earth Observing System\",\"authors\":\"David John Lary\",\"doi\":\"10.1109/AERO.2007.353089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes one vision for future Earth observing systems. New in this vision is the desire for symbiotic communication to dynamically guide an observation system. An earth observation system which is not just a single satellite acting on its own but a constellation of satellites, and sub-orbital platforms such as unmanned aerial vehicles, and ground observations interacting with computer systems used for modeling, data analysis and dynamic observation guidance. An autonomous objectively optimized observation direction system (OOODS) is of great utility for earth observation. In particular, to have a fleet of smart assets that can be reconfigured based on the changing needs of science and technology. The OOODS integrates a modeling and assimilation system within the sensor web allowing the autonomous scheduling of the chosen assets and the autonomous provision of analyses to users. The OOODS operates on generic principles that could easily be used in configurations other than the specific examples described here. Metrics of what we do not know (state vector uncertainty) are used to define what we need to measure and the required mode, time and location of the observations, i.e. to define in real time the observing system targets. Metrics of how important it is to know this information (information content) are used to assign a priority to each observation. The metrics are passed in real time to the sensor web observation scheduler to implement the observation plan for the next observing cycle. The same system could also be used to reduce the cost and development time in an observation sensitivity simulation experiment (OSSE) mode for the optimum development of the next generation of space and ground-based observing systems.\",\"PeriodicalId\":6295,\"journal\":{\"name\":\"2007 IEEE Aerospace Conference\",\"volume\":\"4 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE Aerospace Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AERO.2007.353089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Aerospace Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AERO.2007.353089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes one vision for future Earth observing systems. New in this vision is the desire for symbiotic communication to dynamically guide an observation system. An earth observation system which is not just a single satellite acting on its own but a constellation of satellites, and sub-orbital platforms such as unmanned aerial vehicles, and ground observations interacting with computer systems used for modeling, data analysis and dynamic observation guidance. An autonomous objectively optimized observation direction system (OOODS) is of great utility for earth observation. In particular, to have a fleet of smart assets that can be reconfigured based on the changing needs of science and technology. The OOODS integrates a modeling and assimilation system within the sensor web allowing the autonomous scheduling of the chosen assets and the autonomous provision of analyses to users. The OOODS operates on generic principles that could easily be used in configurations other than the specific examples described here. Metrics of what we do not know (state vector uncertainty) are used to define what we need to measure and the required mode, time and location of the observations, i.e. to define in real time the observing system targets. Metrics of how important it is to know this information (information content) are used to assign a priority to each observation. The metrics are passed in real time to the sensor web observation scheduler to implement the observation plan for the next observing cycle. The same system could also be used to reduce the cost and development time in an observation sensitivity simulation experiment (OSSE) mode for the optimum development of the next generation of space and ground-based observing systems.