S. V. Sokolov, V. A. Pogorelov, A. L. Okhotnikov, M. V. Kurinenko
{"title":"A Method of Combining Data from Electronic Maps and Satellite Measurements for High-Precision Positioning of Moving Objects","authors":"S. V. Sokolov, V. A. Pogorelov, A. L. Okhotnikov, M. V. Kurinenko","doi":"10.17587/mau.24.551-559","DOIUrl":null,"url":null,"abstract":"A new approach to the processing of satellite navigation measurements for high-precision positioning of moving objects moving along a priori (program) trajectories is considered. Existing methods of processing satellite information using the least squares method or its various modifications provide the required positioning accuracy mainly only for stationary objects. At the same time, to assess the state of highly dynamic objects, taking into account the noise of satellite measure- ments, it is very effective to use modern methods of stochastic filtering theory, taking into account both the unevenness of the movement of a transport object and errors in the processing of measurements. The considered approach is based on the use of these methods of nonlinear stochastic filtering. It is proposed to increase the accuracy of positioning a moving object using electronic maps. The use of a digital path model makes it possible to approximate with a given accuracy the a priori (program) trajectory of a moving object with a set of trajectory intervals — orthodromies. These intervals allow you to establish an analytical dependence on the navigation parameters, which ensures high positioning accuracy and a significant reduction in computational costs. The integration of information from electronic maps and stochastic filtering algorithms for dynamic processing of satellite measurements made it possible to significantly reduce computational costs when estimating the current coordinates of a moving object and at the same time significantly improve positioning accuracy compared to traditional methods of processing satellite messages.","PeriodicalId":36477,"journal":{"name":"Mekhatronika, Avtomatizatsiya, Upravlenie","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mekhatronika, Avtomatizatsiya, Upravlenie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17587/mau.24.551-559","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
A new approach to the processing of satellite navigation measurements for high-precision positioning of moving objects moving along a priori (program) trajectories is considered. Existing methods of processing satellite information using the least squares method or its various modifications provide the required positioning accuracy mainly only for stationary objects. At the same time, to assess the state of highly dynamic objects, taking into account the noise of satellite measure- ments, it is very effective to use modern methods of stochastic filtering theory, taking into account both the unevenness of the movement of a transport object and errors in the processing of measurements. The considered approach is based on the use of these methods of nonlinear stochastic filtering. It is proposed to increase the accuracy of positioning a moving object using electronic maps. The use of a digital path model makes it possible to approximate with a given accuracy the a priori (program) trajectory of a moving object with a set of trajectory intervals — orthodromies. These intervals allow you to establish an analytical dependence on the navigation parameters, which ensures high positioning accuracy and a significant reduction in computational costs. The integration of information from electronic maps and stochastic filtering algorithms for dynamic processing of satellite measurements made it possible to significantly reduce computational costs when estimating the current coordinates of a moving object and at the same time significantly improve positioning accuracy compared to traditional methods of processing satellite messages.