{"title":"多波束水文测量系统的误差分析","authors":"Basil Daniel Devote","doi":"10.4314/sajg.v13i2.2","DOIUrl":null,"url":null,"abstract":"Hydrographic surveying involves the integration of a depth-measuring sonar (Sound navigation and ranging) with a positioning system or Global Navigation Satellite System (GNSS); a motion sensor or Inertia Measuring Unit (IMU); and an azimuth sensor (gyroscope). The various sensors acquire data in terms of their respective reference frame and time. The challenge lies in integrating the various sensor frames and time, and in transforming the vessel frame coordinate system into a terrestrial reference frame. The integration of the various sensor frames and time is necessary to minimize systematic errors in the bathymetric data that result from latency, and calibration uncertainty. The focus of this research is to model the systematic bias associated with the integration of the various sensor reference frames. In so doing, the quality of the acquired data is enhanced, and error budgeting and uncertainty prediction can be effectively carried out during the preparation, acquisition, and processing stages of the bathymetric exercise. As such, the required project specification and hydrographic standards, as defined by the International Hydrographic Organization (IHO), are met.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Error Analysis in Multibeam Hydrographic Survey System\",\"authors\":\"Basil Daniel Devote\",\"doi\":\"10.4314/sajg.v13i2.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hydrographic surveying involves the integration of a depth-measuring sonar (Sound navigation and ranging) with a positioning system or Global Navigation Satellite System (GNSS); a motion sensor or Inertia Measuring Unit (IMU); and an azimuth sensor (gyroscope). The various sensors acquire data in terms of their respective reference frame and time. The challenge lies in integrating the various sensor frames and time, and in transforming the vessel frame coordinate system into a terrestrial reference frame. The integration of the various sensor frames and time is necessary to minimize systematic errors in the bathymetric data that result from latency, and calibration uncertainty. The focus of this research is to model the systematic bias associated with the integration of the various sensor reference frames. In so doing, the quality of the acquired data is enhanced, and error budgeting and uncertainty prediction can be effectively carried out during the preparation, acquisition, and processing stages of the bathymetric exercise. As such, the required project specification and hydrographic standards, as defined by the International Hydrographic Organization (IHO), are met.\",\"PeriodicalId\":43854,\"journal\":{\"name\":\"South African Journal of Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/sajg.v13i2.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v13i2.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Error Analysis in Multibeam Hydrographic Survey System
Hydrographic surveying involves the integration of a depth-measuring sonar (Sound navigation and ranging) with a positioning system or Global Navigation Satellite System (GNSS); a motion sensor or Inertia Measuring Unit (IMU); and an azimuth sensor (gyroscope). The various sensors acquire data in terms of their respective reference frame and time. The challenge lies in integrating the various sensor frames and time, and in transforming the vessel frame coordinate system into a terrestrial reference frame. The integration of the various sensor frames and time is necessary to minimize systematic errors in the bathymetric data that result from latency, and calibration uncertainty. The focus of this research is to model the systematic bias associated with the integration of the various sensor reference frames. In so doing, the quality of the acquired data is enhanced, and error budgeting and uncertainty prediction can be effectively carried out during the preparation, acquisition, and processing stages of the bathymetric exercise. As such, the required project specification and hydrographic standards, as defined by the International Hydrographic Organization (IHO), are met.