Self-learning abnormal position tracing point filtering method

Abstract

The invention discloses a self-learning abnormal position tracing point filtering method. The obtained current position information of an intelligent positioning terminal is compared with historical position information in a database, under the condition that the historical position information uploaded at the time, close to the time of the current position information, is recorded in the database, the following steps are carried out, namely, calculating a distance between two adjacent points, so that noise points with larger deviation are filtered out; under the condition that the location mode is not a GPS (Global Position System), obtaining corresponding longitude and latitude data through a base station ID; under the condition that speed information does not exist in the uploaded position information, filtering through distance and time interval between two adjacent positions. The self-learning abnormal position tracing point filtering method provided by the invention can quickly and effectively filter out an abnormal position offset point, so that a better user experience is realized.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a self-learning method for filtering abnormal position track points. Background technique [0002] With the rapid development of positioning technology, people have more and more demand for location-based location services, such as vehicle anti-theft, child location monitoring, company vehicle or important equipment management, etc. Through GPS, base station, Beidou positioning and other technologies, the terminal can obtain the current location information. By displaying the uploaded location information, users can check the location information they care about at any time, such as real-time location information of vehicles and family members. Provide protection for the safety of personnel and property. However, due to the limitations of existing technologies and the influence of external environmental interference factors, the positioning positions uploaded by the devic...

AI Technical Summary

Problems solved by technology

However, due to the limitations of existing technologies and the influence of external environmental interference factors, the positioning positions uploaded by the device cannot be completely correct, and there are some abnormal deviations, which affect the accuracy of the data and the judgment of the user.

[0003] Based on the above problems, how to quickly and effectively filter abnormal position offset points will directly affect the user experience

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