Running track algorithm based on satellite positioning

Abstract

The invention discloses a running track algorithm based on satellite positioning. Calculation comprises the following steps: A, obtaining stable positioning points through a GPS; B, calculating whether positioning is temporary or not; C, calculating whether positioning is just suspended or not; D, calculating whether the positioning point is just recovered or not; E, calculating and filtering running positioning points; F, calculating a filtering positioning point to realize a smooth curve; G, calculating corresponding data such as matching speed, distance and the like; H, drawing a map. According to the method, the first point appears at the position close to the real position, the accuracy of the first point is improved, and the running track length error is reduced. Large-amplitude track distortion is avoided; and if no positioning exists for a period of time, the obtained stable point is subjected to smooth calculation again, and the position of the positioning point is changed within a certain range, so that the running track displayed on the APP interface is smoother and more attractive when being observed by naked eyes, and is closer to a real value in total mileage, and a powerful technical support is provided for ensuring effective application of the running APP.

Description

technical field [0001] The invention relates to the technical field of algorithms used in mobile phone APP positioning technology, in particular to a running track algorithm based on satellite positioning. Background technique [0002] With the popularization of smart phones, there are more and more mobile apps, among which sports apps are one of them. In order to ensure the effective application of sports APP, the motion trajectory calculation method is widely used in sports APP. Due to the limitation of the calculation method adopted by the existing sports APP, in the actual application of the APP, it is affected by the problems of bad weather, buildings, mountains and other obstacles in the surrounding environment, and the accuracy of monitoring the user's motion positioning point based on satellite positioning is not good. question. The main manifestations include the following three types: 1. The first point positioning is not accurate enough. When the user opens the ...

AI Technical Summary

Problems solved by technology

Due to the limitation of the calculation method adopted by the existing sports APP, in the actual application of the APP, it is affected by the problems of bad weather, buildings, mountains and other obstacles in the surrounding environment, and the accuracy of monitoring the user's motion positioning point based on satellite positioning is not good. question

The main manifestations include the following three types: 1. The first point positioning is not accurate enough. When the user opens the APP and the GPS positioning of the APP is working, if there are high-rise buildings or cloudy weather around, the GPS positioning is far from the actual real positioning point. 2. Large-scale trajectory distortion. During running, if the GPS signal suddenly becomes weak, there will be occasional large-scale trajectory distortion, and this distortion will cause a large deviation in the running mileage.

3. The running trajectory generated by the APP interface has a toothed trajectory, so the trajectory is not smooth enough. If you draw a straight line between two points according to the points given by the GPS, since there are more than two points, the movement trajectory will appear broken line segments. , the entire trajectory looks like a multi-point figure with a rectangular tooth shape

For the above three problems, because the existing algorithm cannot be optimized, the track distortion drawn (displayed) on the APP interface is relatively serious, and the mileage deviation is large, which restricts the effective application of sports APP

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