{"title":"GPS Slant Path Residuals for Rainfall Detection","authors":"Shilpa Manandhar, J. Tan, Y. Lee, Y. S. Meng","doi":"10.1109/USNC-URSI.2019.8861697","DOIUrl":null,"url":null,"abstract":"In this paper, Global Positioning System (GPS) derived slant path residual values are studied with respect to a rainfall event. Slant path residuals can be defined as the difference between the slant path wet delay at a particular elevation angle and the zenith wet delay projected to that elevation angle. The slant path residual values are corrected for multipath using multipath stacking algorithm. The corrected residuals show a good correlation with a rainfall event. It is observed that the standard deviation (SD) of the residuals is higher during a rainy time period. The slant path residuals can be used as an added feature in the existing algorithms to improve the rainfall prediction results.","PeriodicalId":383603,"journal":{"name":"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 USNC-URSI Radio Science Meeting (Joint with AP-S Symposium)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USNC-URSI.2019.8861697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, Global Positioning System (GPS) derived slant path residual values are studied with respect to a rainfall event. Slant path residuals can be defined as the difference between the slant path wet delay at a particular elevation angle and the zenith wet delay projected to that elevation angle. The slant path residual values are corrected for multipath using multipath stacking algorithm. The corrected residuals show a good correlation with a rainfall event. It is observed that the standard deviation (SD) of the residuals is higher during a rainy time period. The slant path residuals can be used as an added feature in the existing algorithms to improve the rainfall prediction results.