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Optimization of Positioning Error and Time for UWB and Virtual-Real Scenes Similarity Measure Based on Error Model

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To overcome the problem of large UWB positioning errors caused by obstacles and other factors in the complex environment of substations, a positioning method combining UWB and virtual-real scene similarity… Click to show full abstract

To overcome the problem of large UWB positioning errors caused by obstacles and other factors in the complex environment of substations, a positioning method combining UWB and virtual-real scene similarity measures is proposed, which effectively improves the positioning accuracy of substation operation and maintenance personnel. To further improve the positioning accuracy of the operation and maintenance personnel in the complex environment of the substation, and reduce the positioning time, this paper analyzes the influence of the virtual scene image acquisition step (x, y, yaw, pitch) on the positioning error. Firstly, the mathematical relationship between the step size parameter and the positioning error as well as the positioning time is quantified using the spatial geometric relationship and probability error theory, and the spatial error model of the fusion positioning algorithm is established; then, based on the established spatial error model, the acquisition step size and the positioning error and positioning time have been optimized to make the positioning time the shortest under the conditions of allowable positioning error. The experimental results show that the spatial error model established in this paper has high accuracy and the optimization results are reliable; the spatial error model is used to optimize the acquisition step parameters, which can ensure the UWB and virtual-real scenes similarity measurement fusion positioning algorithm with positioning error less than 0.2 m (with confidence greater than 0.95) and positioning time of 0.173 s, which significantly improves the positioning speed.

Keywords: time; uwb virtual; positioning error; error; error model

Journal Title: IEEE Access
Year Published: 2023

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