{"title":"用于精确GNSS定位的随机电离层模型:灵敏度分析","authors":"Peiyuan Zhou, Jinling Wang","doi":"10.5081/JGPS.12.1.53","DOIUrl":null,"url":null,"abstract":"In Global Navigation Satellite System (GNSS) positioning, ranging signals are delayed when travelling through the ionosphere, the layer of the atmosphere ranging in altitude from about 50 to 1000 km consisting largely of ionized particles. This delay can vary from 1 meter to over 100 meters, and is still one of the most significant error sources in GNSS positioning. In precise GNSS positioning applications, ionospheric errors must be accounted for. One way to do so is to treat unknown ionosphere delay as stochastic parameter, which can account for the ionospheric errors in the GNSS measurements as well as keeping the full original information. The idea is adding ionospheric delay from external sources as pseudo-observables. In this paper, the performance of ionosphere-weighted model is evaluated using real data sets, and the correctness of priori ionosphere variance is also validated.","PeriodicalId":237555,"journal":{"name":"Journal of Global Positioning Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Stochastic Ionosphere Models for Precise GNSS Positioning: Sensitivity Analysis\",\"authors\":\"Peiyuan Zhou, Jinling Wang\",\"doi\":\"10.5081/JGPS.12.1.53\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Global Navigation Satellite System (GNSS) positioning, ranging signals are delayed when travelling through the ionosphere, the layer of the atmosphere ranging in altitude from about 50 to 1000 km consisting largely of ionized particles. This delay can vary from 1 meter to over 100 meters, and is still one of the most significant error sources in GNSS positioning. In precise GNSS positioning applications, ionospheric errors must be accounted for. One way to do so is to treat unknown ionosphere delay as stochastic parameter, which can account for the ionospheric errors in the GNSS measurements as well as keeping the full original information. The idea is adding ionospheric delay from external sources as pseudo-observables. In this paper, the performance of ionosphere-weighted model is evaluated using real data sets, and the correctness of priori ionosphere variance is also validated.\",\"PeriodicalId\":237555,\"journal\":{\"name\":\"Journal of Global Positioning Systems\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Global Positioning Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5081/JGPS.12.1.53\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Positioning Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5081/JGPS.12.1.53","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic Ionosphere Models for Precise GNSS Positioning: Sensitivity Analysis
In Global Navigation Satellite System (GNSS) positioning, ranging signals are delayed when travelling through the ionosphere, the layer of the atmosphere ranging in altitude from about 50 to 1000 km consisting largely of ionized particles. This delay can vary from 1 meter to over 100 meters, and is still one of the most significant error sources in GNSS positioning. In precise GNSS positioning applications, ionospheric errors must be accounted for. One way to do so is to treat unknown ionosphere delay as stochastic parameter, which can account for the ionospheric errors in the GNSS measurements as well as keeping the full original information. The idea is adding ionospheric delay from external sources as pseudo-observables. In this paper, the performance of ionosphere-weighted model is evaluated using real data sets, and the correctness of priori ionosphere variance is also validated.