Giovanni A. Santos, J. P. J. D. Da Costa, Daniel V. de Lima, M. R. Zanatta, B. Praciano, Gabriel P. M. Pinheiro, F. L. L. de Mendonça, R. D. de Sousa
{"title":"基于张量和天线阵列的GNSS接收机改进的自动驾驶车辆定位框架","authors":"Giovanni A. Santos, J. P. J. D. Da Costa, Daniel V. de Lima, M. R. Zanatta, B. Praciano, Gabriel P. M. Pinheiro, F. L. L. de Mendonça, R. D. de Sousa","doi":"10.1109/WCNPS50723.2020.9263757","DOIUrl":null,"url":null,"abstract":"Autonomous vehicles may save 500.000 lives between 2035 and 2045, since humans cause more than 90% of traffic accidents. In order to have an accurate perception of the environment and to avoid accidents, autonomous vehicles require a positioning estimation with only a few centimeters errors. Therefore, state-of-the-art third generation GNSS systems are not suitable for autonomous vehicle applications. In this paper, we propose an improved localization framework for autonomous vehicles via tensor and antenna array based GNSS receiver. As shown in this paper, in challenging urban scenarios, antenna array based GNSS receivers using tensor based algorithms can provide a positioning five times more accurante than state-of-the-art single antenna based GNSS receivers, reducing the positioning error from 149 cm to 30 cm.","PeriodicalId":385668,"journal":{"name":"2020 Workshop on Communication Networks and Power Systems (WCNPS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Improved localization framework for autonomous vehicles via tensor and antenna array based GNSS receivers\",\"authors\":\"Giovanni A. Santos, J. P. J. D. Da Costa, Daniel V. de Lima, M. R. Zanatta, B. Praciano, Gabriel P. M. Pinheiro, F. L. L. de Mendonça, R. D. de Sousa\",\"doi\":\"10.1109/WCNPS50723.2020.9263757\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Autonomous vehicles may save 500.000 lives between 2035 and 2045, since humans cause more than 90% of traffic accidents. In order to have an accurate perception of the environment and to avoid accidents, autonomous vehicles require a positioning estimation with only a few centimeters errors. Therefore, state-of-the-art third generation GNSS systems are not suitable for autonomous vehicle applications. In this paper, we propose an improved localization framework for autonomous vehicles via tensor and antenna array based GNSS receiver. As shown in this paper, in challenging urban scenarios, antenna array based GNSS receivers using tensor based algorithms can provide a positioning five times more accurante than state-of-the-art single antenna based GNSS receivers, reducing the positioning error from 149 cm to 30 cm.\",\"PeriodicalId\":385668,\"journal\":{\"name\":\"2020 Workshop on Communication Networks and Power Systems (WCNPS)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Workshop on Communication Networks and Power Systems (WCNPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNPS50723.2020.9263757\",\"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 Workshop on Communication Networks and Power Systems (WCNPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNPS50723.2020.9263757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improved localization framework for autonomous vehicles via tensor and antenna array based GNSS receivers
Autonomous vehicles may save 500.000 lives between 2035 and 2045, since humans cause more than 90% of traffic accidents. In order to have an accurate perception of the environment and to avoid accidents, autonomous vehicles require a positioning estimation with only a few centimeters errors. Therefore, state-of-the-art third generation GNSS systems are not suitable for autonomous vehicle applications. In this paper, we propose an improved localization framework for autonomous vehicles via tensor and antenna array based GNSS receiver. As shown in this paper, in challenging urban scenarios, antenna array based GNSS receivers using tensor based algorithms can provide a positioning five times more accurante than state-of-the-art single antenna based GNSS receivers, reducing the positioning error from 149 cm to 30 cm.