User terminal positioning method and system, electronic device and storage medium

Abstract

The invention provides a user terminal positioning method and system, an electronic device and a storage medium. The user terminal positioning method comprises the steps of determining target cells corresponding to target sampling points in an LTE network according to MRO data; if all target cells are outdoor cells, determining whether the number of target sampling points that do not coincide is less three; if yes, acquiring primary positioning information of the target sampling points by using an outdoor positioning method and a distance between the target sampling point and the correspondingtarget cell; if not, performing three-point positioning on the target sampling points according to a least square method so as to obtain the primary positioning information of the target sampling points; and if the primary positioning information of the target sampling points has an error greater than a preset error threshold, performing error regulation on the primary positioning information byusing a machine learning method, so as to obtain secondary positioning information of the target sampling points. Through adoption of the method, the user in the wireless network can be positioned accurately, data requirements are lowered effectively, and the positioning process is reliable and fast.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a user terminal positioning method, system, electronic equipment and storage medium. Background technique [0002] With the rapid development of communication technology, user positioning in wireless networks has become an effective means to provide users with precise services. At the same time, user positioning can also effectively improve user experience. [0003] At present, one of the user positioning methods in the wireless network is to use a simulation model to calculate the position; the other is to realize it through the time advance Tadv and the eNB antenna angle of arrival AOA in the MRO data. [0004] Wherein, the method of using the simulation model to estimate the position specifically includes: the calculation of the simulation model is performed by using a ray propagation model. The ray propagation model is a physical model abstracted by business e...

AI Technical Summary

Problems solved by technology

This kind of physical theoretical model has a certain theoretical support for its strong interpretability; but at the same time, because the model is given under various assumptions, the real status of the network is ever-changing, which leads to a gap between this simulation model and the real status of the network. big difference

The actual use in actual business results in large positioning errors and requires high quality of actual data

[0005] Wherein, the method of positioning the user through the time advance Tadv in the MRO data and the eNB antenna angle of arrival AOA specifically includes: Tadv: time advance, which can be used to estimate the distance from the user to the base station; Tadv=1 means the distance is 78m; AOA: eNB antenna angle of arrival, which defines the estimated angle of a user relative to the reference direction, counterclockwise; this can estimate the position and direction of the user and the main cell; at the same time, since the accuracy of Tadv is 78m, this method can only do Accuracy to 78m; no more precise positioning possible

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