{"title":"利用伽利略在密集的城市环境中提高精度的3d测绘辅助GNSS","authors":"M. Adjrad, P. Groves","doi":"10.1109/EURONAV.2017.7954199","DOIUrl":null,"url":null,"abstract":"Conventional single-epoch GNSS positioning in dense urban areas can exhibit errors of tens of meters due to blockage and reflection of signals by the surrounding buildings. Here, we present the first implementation of 3D-mapping-aided (3DMA) GNSS to use Galileo signals as well as GPS and GLONASS. Our intelligent urban positioning (IUP) concept combines conventional ranging-based GNSS positioning enhanced by 3D mapping with the GNSS shadow-matching technique. Shadow matching (SM) determines position by comparing the measured signal availability with that predicted over a grid of candidate positions using 3D mapping. Thus, IUP uses both pseudo-range and signal-to-noise measurements to determine position. All algorithms incorporate terrain-height aiding and use measurements from a single epoch in time.","PeriodicalId":145124,"journal":{"name":"2017 European Navigation Conference (ENC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"3D-mapping-aided GNSS exploiting Galileo for better accuracy in dense urban environments\",\"authors\":\"M. Adjrad, P. Groves\",\"doi\":\"10.1109/EURONAV.2017.7954199\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conventional single-epoch GNSS positioning in dense urban areas can exhibit errors of tens of meters due to blockage and reflection of signals by the surrounding buildings. Here, we present the first implementation of 3D-mapping-aided (3DMA) GNSS to use Galileo signals as well as GPS and GLONASS. Our intelligent urban positioning (IUP) concept combines conventional ranging-based GNSS positioning enhanced by 3D mapping with the GNSS shadow-matching technique. Shadow matching (SM) determines position by comparing the measured signal availability with that predicted over a grid of candidate positions using 3D mapping. Thus, IUP uses both pseudo-range and signal-to-noise measurements to determine position. All algorithms incorporate terrain-height aiding and use measurements from a single epoch in time.\",\"PeriodicalId\":145124,\"journal\":{\"name\":\"2017 European Navigation Conference (ENC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 European Navigation Conference (ENC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EURONAV.2017.7954199\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 European Navigation Conference (ENC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EURONAV.2017.7954199","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3D-mapping-aided GNSS exploiting Galileo for better accuracy in dense urban environments
Conventional single-epoch GNSS positioning in dense urban areas can exhibit errors of tens of meters due to blockage and reflection of signals by the surrounding buildings. Here, we present the first implementation of 3D-mapping-aided (3DMA) GNSS to use Galileo signals as well as GPS and GLONASS. Our intelligent urban positioning (IUP) concept combines conventional ranging-based GNSS positioning enhanced by 3D mapping with the GNSS shadow-matching technique. Shadow matching (SM) determines position by comparing the measured signal availability with that predicted over a grid of candidate positions using 3D mapping. Thus, IUP uses both pseudo-range and signal-to-noise measurements to determine position. All algorithms incorporate terrain-height aiding and use measurements from a single epoch in time.