{"title":"基于逆问题求解的远程多传感器动态标定","authors":"D. Necsulescu, R. Jassemi-Zargani, J. Sasiadek","doi":"10.1109/OPTIM.2008.4602462","DOIUrl":null,"url":null,"abstract":"Remote multisensing problem results from the use a variety of instruments in non-collocated measurement of time varying quantities. Variables measured by multiple sensors h ave to b e associated with spatial coordinates and synchronized in time. Sensors outputs are, however, dependent not only on the inputs from measured variables, but also by the instrument inner dynamics. Sensor fusion is accurate only if it uses signals with properly calibrated magnitudes and with the same phase shifts. An effective approach for achieving these requirements is dynamic calibration of individual sensors output signals. This paper investigates dynamic calibration as an inverse problem and proposes to use the solutions developed for such problems. Numerical results illustrate the benefits of dynamic calibration for remote sensing.","PeriodicalId":244464,"journal":{"name":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic calibration of remote multisensors using inverse problem solution\",\"authors\":\"D. Necsulescu, R. Jassemi-Zargani, J. Sasiadek\",\"doi\":\"10.1109/OPTIM.2008.4602462\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Remote multisensing problem results from the use a variety of instruments in non-collocated measurement of time varying quantities. Variables measured by multiple sensors h ave to b e associated with spatial coordinates and synchronized in time. Sensors outputs are, however, dependent not only on the inputs from measured variables, but also by the instrument inner dynamics. Sensor fusion is accurate only if it uses signals with properly calibrated magnitudes and with the same phase shifts. An effective approach for achieving these requirements is dynamic calibration of individual sensors output signals. This paper investigates dynamic calibration as an inverse problem and proposes to use the solutions developed for such problems. Numerical results illustrate the benefits of dynamic calibration for remote sensing.\",\"PeriodicalId\":244464,\"journal\":{\"name\":\"2008 11th International Conference on Optimization of Electrical and Electronic Equipment\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 11th International Conference on Optimization of Electrical and Electronic Equipment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OPTIM.2008.4602462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 11th International Conference on Optimization of Electrical and Electronic Equipment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OPTIM.2008.4602462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dynamic calibration of remote multisensors using inverse problem solution
Remote multisensing problem results from the use a variety of instruments in non-collocated measurement of time varying quantities. Variables measured by multiple sensors h ave to b e associated with spatial coordinates and synchronized in time. Sensors outputs are, however, dependent not only on the inputs from measured variables, but also by the instrument inner dynamics. Sensor fusion is accurate only if it uses signals with properly calibrated magnitudes and with the same phase shifts. An effective approach for achieving these requirements is dynamic calibration of individual sensors output signals. This paper investigates dynamic calibration as an inverse problem and proposes to use the solutions developed for such problems. Numerical results illustrate the benefits of dynamic calibration for remote sensing.