Positioning drift data filtering system and method for vehicle

Abstract

The invention relates to the technical field of signal positioning monitoring, in particular to a positioning drift data filtering system and method for a vehicle, and the system comprises a data extraction module, a speed calculation module, an acceleration calculation module, a first judgment module, a second judgment module, a track generation module and a data collection module. A signal position drift point is judged according to the numerical relationship between the acceleration and a preset acceleration threshold value, or the actual situation of the position point is judged according to the change degree of the gyroscope and the comparison of the acceleration ax and ay of the triaxial accelerometer along the X axis and the Y axis, the state of the position point is judged, and finally a judgment result is sent. When the GSP position drift point is judged, the GSP position drift point is directly abandoned; and when a non-signal position drift point is judged, reporting is carried out, and data of the driving condition is collected. The method is used for accurately filtering the signal drift point and judging the actual driving condition corresponding to the data of the signal drift point.

Description

technical field [0001] The invention relates to the technical field of signal positioning monitoring, in particular to a positioning drift data filtering system and method for vehicles. Background technique [0002] Signal drift means that when the signal is positioned, there is a large gap with the actual position, and there is a continuous trajectory with a certain distance from the actual route during the movement. If it happens once in a long time, it won't have much impact, but if it happens more frequently, or if there is an emergency that requires accurate positioning, the results will drift and cause positioning errors, it will bring more problems. serious impact. [0003] In the prior art, an autocorrelation algorithm based on time series is generally used to find singular points (points where drift occurs) for correction. However, this algorithm can only be performed after collecting all the geographic location information, and cannot correct the geographic locat...

AI Technical Summary

Problems solved by technology

However, this algorithm can only be carried out after collecting all the geographic location information, and cannot correct the geographic location information in real time; moreover, its calculation process is complex and time-consuming, and it is difficult to meet the real-time requirements of users

At the same time, most of the existing drift data filtering methods can only judge whether it is a signal drift point, but cannot understand the actual situation and the cause of the suspected drift based on the data, and then the next time you drive to this point, you cannot provide more accurate data. And the driving data of valid driving trajectory

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