{"title":"基于实时操作系统的嵌入式无人水面车辆导航多传感器数据融合系统设计","authors":"Wenwen Liu, Yuanchang Liu, R. Song, R. Bucknall","doi":"10.1109/OCEANSKOBE.2018.8559352","DOIUrl":null,"url":null,"abstract":"This paper describes the design and implementation of a practical multi-sensor data fusion system for unmanned surface vehicle (USV) navigation. The system employs an embedded Linux board as the main on-board control module to extract and preprocess raw measurements from various navigational sensors using the real time operating system (RTOS). An unscented Kalman Filter (UKF) based data fusion algorithm has been developed to fuse the obtained and preprocessed sensor measurements and provide more reliable and accurate estimations of USV's navigational data in real time. The results demonstrate the effectiveness of the data fusion algorithm in reducing unpredicted errors of a standalone sensor.","PeriodicalId":441405,"journal":{"name":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System\",\"authors\":\"Wenwen Liu, Yuanchang Liu, R. Song, R. Bucknall\",\"doi\":\"10.1109/OCEANSKOBE.2018.8559352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the design and implementation of a practical multi-sensor data fusion system for unmanned surface vehicle (USV) navigation. The system employs an embedded Linux board as the main on-board control module to extract and preprocess raw measurements from various navigational sensors using the real time operating system (RTOS). An unscented Kalman Filter (UKF) based data fusion algorithm has been developed to fuse the obtained and preprocessed sensor measurements and provide more reliable and accurate estimations of USV's navigational data in real time. The results demonstrate the effectiveness of the data fusion algorithm in reducing unpredicted errors of a standalone sensor.\",\"PeriodicalId\":441405,\"journal\":{\"name\":\"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCEANSKOBE.2018.8559352\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCEANSKOBE.2018.8559352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Design of an Embedded Multi-Sensor Data Fusion System for Unmanned Surface Vehicle Navigation Based on Real Time Operating System
This paper describes the design and implementation of a practical multi-sensor data fusion system for unmanned surface vehicle (USV) navigation. The system employs an embedded Linux board as the main on-board control module to extract and preprocess raw measurements from various navigational sensors using the real time operating system (RTOS). An unscented Kalman Filter (UKF) based data fusion algorithm has been developed to fuse the obtained and preprocessed sensor measurements and provide more reliable and accurate estimations of USV's navigational data in real time. The results demonstrate the effectiveness of the data fusion algorithm in reducing unpredicted errors of a standalone sensor.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
