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Spatial selection of solution errors of a mobile device location by distance measurement in a local terrestrial radio navigation system


A.V. Zhuravlev – Ph. D. (Eng.), Senior Research Scientist, Main Designer – Deputy General Director, JSC SPE «PROTEK» (Voronezh)
V.G. Markin – Leading Engineer, JSC SPE «PROTEK» (Voronezh)

One of the most significant problems of mobile devices (MD) control is the issue of the determination of their locations. The problem can be solved by a number of various methods, including the measurement of the distances between MD and the base stations of a local terrestrial radio navigational system (LRNS) with the further processing in order to determine the location with the use of algorithms typical of the distance measuring systems.
However, any measurements are accompanied with errors, which lead to the mistakes in locating. The errors can be conditioned by: the inaccuracy of the source mathematical models, measure methods imperfections, the signaling conditions, MD motion on complicated terrain, etc. In other words, inaccuracy in the source data can be caused by a large number of reasons, which affect every particular measurement in a different way. Herein, in some cases the error can be fairly poor.
To estimate the location data, the author looks into the direct determination of mobile devices location procedure using the measured distances to the base stations with the known location data.
The measured distances filtration was provided by the nonconditional measurements attrition with the use of the base stations re-dundancy, whose signals were accessible to solve the problem of a particular mobile device positioning. In other words, the esteem accuracy was enhanced by the spatial selection of the base stations, the distances measurements to which are the least corrupted by the errors.
The results of the numerical modelling showed the high effectivity of estimation of mobile devices location by the direct method of lo-cation data calculation and the spatial selection of the measured distances.

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June 24, 2020
May 29, 2020

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