{"title":"Precise position estimation methods for differential-IRNSS using iterative algorithm","authors":"Nageena Parveen Syed, Thaherbasha SK","doi":"10.1007/s12518-024-00588-1","DOIUrl":null,"url":null,"abstract":"<div><p>The Indian Regional Navigation Satellite System (IRNSS) is an elegant system for positioning of users in India. It also provides its services to an extended region. In the IRNSS, to find the unknown user location, the used pseudo range method gives only meter-level accuracy. In order to reduce the noise impacts on measurement, and to improve position accuracy (meter-level to centimeter-level) for IRNSS, in this paper, carrier phase (CP) measurement technique is employed. Here, CP-based differential techniques are proposed to find the unknown user/rover receiver position. The corresponding incremental position (positional error) is computed in both double difference (DD) and triple difference (TD) techniques (with and without filter). In this paper, the CP measurement-based differencing techniques (DD/TD) supported with recursive filter (Kalman) is analyzed. This type of methodology is mostly useful in surveying applications. With this approach, the errors are reduced greatly, and the obtained accuracy is in centimeters. The filter utilizes and projects the previous and current activity data to estimate the float response. In this work, an iterative algorithm is used to find the precise position of the rover. For a short baseline, the obtained positional errors are compared for DD and TD with/without recursive filter. To simulate the real-time data, MATLAB programming is used. The obtained root mean square error (RMSE) in position estimation in IRNSS is 2.3391 m and 0.6901 m with DD, and 0.1079 m and 0.0518 m with TD without and with filter respectively.</p></div>","PeriodicalId":46286,"journal":{"name":"Applied Geomatics","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s12518-024-00588-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
The Indian Regional Navigation Satellite System (IRNSS) is an elegant system for positioning of users in India. It also provides its services to an extended region. In the IRNSS, to find the unknown user location, the used pseudo range method gives only meter-level accuracy. In order to reduce the noise impacts on measurement, and to improve position accuracy (meter-level to centimeter-level) for IRNSS, in this paper, carrier phase (CP) measurement technique is employed. Here, CP-based differential techniques are proposed to find the unknown user/rover receiver position. The corresponding incremental position (positional error) is computed in both double difference (DD) and triple difference (TD) techniques (with and without filter). In this paper, the CP measurement-based differencing techniques (DD/TD) supported with recursive filter (Kalman) is analyzed. This type of methodology is mostly useful in surveying applications. With this approach, the errors are reduced greatly, and the obtained accuracy is in centimeters. The filter utilizes and projects the previous and current activity data to estimate the float response. In this work, an iterative algorithm is used to find the precise position of the rover. For a short baseline, the obtained positional errors are compared for DD and TD with/without recursive filter. To simulate the real-time data, MATLAB programming is used. The obtained root mean square error (RMSE) in position estimation in IRNSS is 2.3391 m and 0.6901 m with DD, and 0.1079 m and 0.0518 m with TD without and with filter respectively.
期刊介绍:
Applied Geomatics (AGMJ) is the official journal of SIFET the Italian Society of Photogrammetry and Topography and covers all aspects and information on scientific and technical advances in the geomatics sciences. The Journal publishes innovative contributions in geomatics applications ranging from the integration of instruments, methodologies and technologies and their use in the environmental sciences, engineering and other natural sciences.
The areas of interest include many research fields such as: remote sensing, close range and videometric photogrammetry, image analysis, digital mapping, land and geographic information systems, geographic information science, integrated geodesy, spatial data analysis, heritage recording; network adjustment and numerical processes. Furthermore, Applied Geomatics is open to articles from all areas of deformation measurements and analysis, structural engineering, mechanical engineering and all trends in earth and planetary survey science and space technology. The Journal also contains notices of conferences and international workshops, industry news, and information on new products. It provides a useful forum for professional and academic scientists involved in geomatics science and technology.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements