A method, medium and terminal for denoising mobile signal traces

Abstract

The present invention provides a method, medium and terminal for denoising mobile signal tracks. The method includes: obtaining original mobile track data; acquiring the track point confidence of each track point according to historical data; Perform screening to obtain the final trajectory; the confidence of the trajectory point includes at least the confidence of the speed, and the confidence of the speed is determined by taking the probability distribution of the speed in the historical data as the standard deviation, taking the maximum normal moving speed as the expected parameter, and taking the speed as the normal of the random variable Obtained in a distributed manner; the present invention introduces the confidence degree of the trajectory point, and finally displays the trajectory information by screening the confidence degree. The present invention can effectively process the abnormal trajectory point after passing the trajectory denoising process for the moving trajectory data, and the trajectory can be described It can visually display the movement trajectory of personnel, optimize the movement trajectory, and have an optimization effect on model calculations such as footholds and stay points after eliminating abnormal points.

Description

technical field [0001] The present invention relates to the communication field, in particular to a method, medium and terminal for denoising mobile signal traces. Background technique [0002] Movement trajectory is the way to analyze and display the activity area of ​​control personnel. Currently, due to the limitations of portrait capture, it is impossible to fully display the movement trajectory information of personnel. Therefore, mobile signal collection data is introduced. For example, the currently common mobile phone 4G signal collection data, However, mobile phone mobile data is more complicated. In actual work, due to reasons such as base station drift, acquisition frequency, and multiple acquisition base stations, the application effect of the data is not ideal. However, if the original 4G trajectory data is used directly, the trajectory lines will appear chaotic. The route is not intuitive, therefore, the trajectory data needs to be denoised. [0003] At presen...

AI Technical Summary

Problems solved by technology

[0002] Motion trajectory is the way to analyze and display the activity area of ​​control personnel. At present, due to the limitation of portrait capture, it is impossible to fully display the movement trajectory information of personnel. Therefore, mobile signal collection data is introduced. For example, the currently common mobile phone 4G signal collection data, However, mobile phone mobile data is relatively complex. In actual work, due to reasons such as base station drift, acquisition frequency, and multiple acquisition base stations, the application effect of the data is not ideal. However, if the original 4G trajectory data is used directly, the trajectory lines will appear chaotic. The route is not intuitive, therefore, the trajectory data needs to be denoised

[0003] At present, in the existing technology, it is usually to detect the abnormality of the velocity and direction of the trajectory points, use the threshold method to directly clear the trajectory points with abnormal velocity, and then use the abnormal detection of the forward direction to clear the remaining trajectory points, but this way Unable to meet the complexity of 4G trajectory, and the accuracy is not high

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