K. Pourvoyeur, Andreas Stelzer, Guenter Stelzhammer
{"title":"Error estimation for reliable fault detection of a TDOA local positioning system","authors":"K. Pourvoyeur, Andreas Stelzer, Guenter Stelzhammer","doi":"10.1109/TIWDC.2008.4649036","DOIUrl":null,"url":null,"abstract":"A key element in precise position estimation is the ability to detect as well as to assign measurement errors. These errors may be caused by disturbances within the propagation path of the electromagnetic wave as well as by the hardware itself. In this contribution the error estimation for a time difference of arrival (TDOA) local position estimation system is discussed in detail. Scenarios are proposed to estimate path-related errors, as well as hardware-related errors. The developed algorithms, which are based on Kalman filtering techniques, are verified with measurements.","PeriodicalId":113942,"journal":{"name":"2008 Tyrrhenian International Workshop on Digital Communications - Enhanced Surveillance of Aircraft and Vehicles","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Tyrrhenian International Workshop on Digital Communications - Enhanced Surveillance of Aircraft and Vehicles","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIWDC.2008.4649036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A key element in precise position estimation is the ability to detect as well as to assign measurement errors. These errors may be caused by disturbances within the propagation path of the electromagnetic wave as well as by the hardware itself. In this contribution the error estimation for a time difference of arrival (TDOA) local position estimation system is discussed in detail. Scenarios are proposed to estimate path-related errors, as well as hardware-related errors. The developed algorithms, which are based on Kalman filtering techniques, are verified with measurements.