Network access point position estimation method and device

Abstract

The embodiment of the invention provides a network access point position estimation method and device. The method comprises: acquiring a data sample set based on an identifier of a network access point to be estimated, and each data sample comprising position information of external terminal device connected to the network access point; based on the position information of the external terminal device, calculating the physical distance between the physical positions of the two external terminal device related to each two data samples; based on the physical distance, performing clustering processing on the data sample set to generate at least one candidate cluster; and taking the geometric center of the target cluster meeting a predetermined evaluation condition in the at least one candidate cluster as the geographic position of the network access point, wherein the geometric center is the geographic center of the position of the external terminal device involved in each data sample inthe target cluster.

Description

technical field [0001] The present invention relates to geographic positioning, in particular to the positioning technology of network access points. Background technique [0002] In mobile Internet applications, it is often necessary to make personalized recommendations or risk control decisions based on the user's geographical location. Generally, methods for obtaining a user's geographic location are divided into direct positioning methods and indirect positioning methods. The direct method is to directly read the GPS latitude and longitude readings of the user device. Although this method is simple and accurate, it will be affected by factors such as buildings blocking GPS signals, device GPS functions being turned off, and users maliciously tampering with GPS readings, so the use scenarios are limited. Another indirect positioning method is to first obtain the possible positions of many mobile base stations, wireless access points and other network access points in adv...

AI Technical Summary

Problems solved by technology

However, due to the influence of data drift interference, there is a large error in the estimated mean value, which affects the positioning effect

In addition, this method is not suitable for estimating the position of the mobile base station, because when the position of the mobile base station moves, there must actually be multiple physical locations in multiple observation periods, so obviously based on the data collected in multiple observation periods to establish Two-dimensional Gaussian distribution model, and selecting the median value of the model as the location estimate of the access point will produce serious errors

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