{"title":"基于超宽带和人工智能技术的智能电网实时室内定位系统","authors":"Long Cheng, Hao Chang, Kexin Wang, Zhaoqi Wu","doi":"10.1109/SusTech47890.2020.9150486","DOIUrl":null,"url":null,"abstract":"Indoor positioning system plays an important role in smart grid. Although GPS is the predominant outdoor positioning technology, it is unsuitable to be used in many fields of smart grid for three main reasons: first, signals sent from GPS could easily get blocked by solid materials such as metal or brick; second, the complex electromagnetic interference induced by electrical circuits greatly affects GPS signals; third, GPS can only achieve meter-level real time positioning accuracy, which is far from sufficient for many requirements of smart grid applications. Some other indoor positioning technologies, such as Bluetooth, Wi-Fi, ultrasound, infrared and RFID, fail in either the positioning accuracy, the positioning range, or the positioning speed required in many smart grid applications. Therefore, this paper proposes a real time indoor positioning system for smart gird based on a more promising technology, ultra-wideband (UWB). UWB is suitable for real-time localization in smart grid because UWB has short radio frequency pulse duration and wide bandwidth, which can minimize the effects of multipath interference and allow for high-resolution ranging and easier material penetration. In addition, since high-accuracy position information is required in many smart grid fields, a comprehensive framework integrating several artificial intelligence techniques, including outlier detection, line-of-sight/non-line-of-sight classification, filter design, range measurement correction and maximum likelihood localization estimation, is also proposed to further improve the positioning accuracy. At last, the performance of this system is verified through a series of experiments.","PeriodicalId":184112,"journal":{"name":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Real Time Indoor Positioning System for Smart Grid based on UWB and Artificial Intelligence Techniques\",\"authors\":\"Long Cheng, Hao Chang, Kexin Wang, Zhaoqi Wu\",\"doi\":\"10.1109/SusTech47890.2020.9150486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Indoor positioning system plays an important role in smart grid. Although GPS is the predominant outdoor positioning technology, it is unsuitable to be used in many fields of smart grid for three main reasons: first, signals sent from GPS could easily get blocked by solid materials such as metal or brick; second, the complex electromagnetic interference induced by electrical circuits greatly affects GPS signals; third, GPS can only achieve meter-level real time positioning accuracy, which is far from sufficient for many requirements of smart grid applications. Some other indoor positioning technologies, such as Bluetooth, Wi-Fi, ultrasound, infrared and RFID, fail in either the positioning accuracy, the positioning range, or the positioning speed required in many smart grid applications. Therefore, this paper proposes a real time indoor positioning system for smart gird based on a more promising technology, ultra-wideband (UWB). UWB is suitable for real-time localization in smart grid because UWB has short radio frequency pulse duration and wide bandwidth, which can minimize the effects of multipath interference and allow for high-resolution ranging and easier material penetration. In addition, since high-accuracy position information is required in many smart grid fields, a comprehensive framework integrating several artificial intelligence techniques, including outlier detection, line-of-sight/non-line-of-sight classification, filter design, range measurement correction and maximum likelihood localization estimation, is also proposed to further improve the positioning accuracy. At last, the performance of this system is verified through a series of experiments.\",\"PeriodicalId\":184112,\"journal\":{\"name\":\"2020 IEEE Conference on Technologies for Sustainability (SusTech)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Conference on Technologies for Sustainability (SusTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SusTech47890.2020.9150486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SusTech47890.2020.9150486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real Time Indoor Positioning System for Smart Grid based on UWB and Artificial Intelligence Techniques
Indoor positioning system plays an important role in smart grid. Although GPS is the predominant outdoor positioning technology, it is unsuitable to be used in many fields of smart grid for three main reasons: first, signals sent from GPS could easily get blocked by solid materials such as metal or brick; second, the complex electromagnetic interference induced by electrical circuits greatly affects GPS signals; third, GPS can only achieve meter-level real time positioning accuracy, which is far from sufficient for many requirements of smart grid applications. Some other indoor positioning technologies, such as Bluetooth, Wi-Fi, ultrasound, infrared and RFID, fail in either the positioning accuracy, the positioning range, or the positioning speed required in many smart grid applications. Therefore, this paper proposes a real time indoor positioning system for smart gird based on a more promising technology, ultra-wideband (UWB). UWB is suitable for real-time localization in smart grid because UWB has short radio frequency pulse duration and wide bandwidth, which can minimize the effects of multipath interference and allow for high-resolution ranging and easier material penetration. In addition, since high-accuracy position information is required in many smart grid fields, a comprehensive framework integrating several artificial intelligence techniques, including outlier detection, line-of-sight/non-line-of-sight classification, filter design, range measurement correction and maximum likelihood localization estimation, is also proposed to further improve the positioning accuracy. At last, the performance of this system is verified through a series of experiments.