{"title":"电机产生音频信号的鲁棒检测","authors":"Adeola Bannis, H. Noh, Pei Zhang","doi":"10.1145/3274783.3275209","DOIUrl":null,"url":null,"abstract":"Indoor localization systems cannot rely on the same mechanisms, like GPS, that are used for outdoor or large-scale localization. Instead, autonomous or user-carried devices are often localized by measuring the time taken for an emitted signal to reach a known location; this signal can be sound, light, radio waves, or another similar sensed quantity. Autonomous mobile devices already contain motors, which produce sounds as a side effect of their operation, and so can potentially be included in a localization scheme without new hardware. In this paper, we briefly outline the challenges that need to be met for accurate detection and identification of motor-produced signals. We present a method for improving signal resolution for linear chirps that improves cross-correlation based signal detection by up to 2.8X.","PeriodicalId":156307,"journal":{"name":"Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust Detection of Motor-Produced Audio Signals\",\"authors\":\"Adeola Bannis, H. Noh, Pei Zhang\",\"doi\":\"10.1145/3274783.3275209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Indoor localization systems cannot rely on the same mechanisms, like GPS, that are used for outdoor or large-scale localization. Instead, autonomous or user-carried devices are often localized by measuring the time taken for an emitted signal to reach a known location; this signal can be sound, light, radio waves, or another similar sensed quantity. Autonomous mobile devices already contain motors, which produce sounds as a side effect of their operation, and so can potentially be included in a localization scheme without new hardware. In this paper, we briefly outline the challenges that need to be met for accurate detection and identification of motor-produced signals. We present a method for improving signal resolution for linear chirps that improves cross-correlation based signal detection by up to 2.8X.\",\"PeriodicalId\":156307,\"journal\":{\"name\":\"Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3274783.3275209\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3274783.3275209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Indoor localization systems cannot rely on the same mechanisms, like GPS, that are used for outdoor or large-scale localization. Instead, autonomous or user-carried devices are often localized by measuring the time taken for an emitted signal to reach a known location; this signal can be sound, light, radio waves, or another similar sensed quantity. Autonomous mobile devices already contain motors, which produce sounds as a side effect of their operation, and so can potentially be included in a localization scheme without new hardware. In this paper, we briefly outline the challenges that need to be met for accurate detection and identification of motor-produced signals. We present a method for improving signal resolution for linear chirps that improves cross-correlation based signal detection by up to 2.8X.