Path trajectory adjusting method and device

Abstract

The invention discloses a path trajectory adjusting method and device. The method comprises the following steps: obtaining a real-time coordinate value of each target position in a plurality of target positions of a current path and a neighbor coordinate value of a neighbor position adjacent to each target position; adjusting the real-time coordinate value by utilizing a target filter algorithm and the neighbor coordinate value to obtain a first target coordinate value of each target position; and carrying out adjustment on the current trajectory of the current path according to the first target coordinate value of each target position to obtain a first target trajectory of the current path. Through the technical scheme, the real-time coordinate value of each target position can be subjected to initial adjustment through the target filter algorithm, and then, real-time adjustment is carried out again on the first target trajectory through one or more algorithms of a wavelet transform algorithm and a Kalman algorithm to obtain a higher-accuracy higher-precision trajectory of the current path, thereby solving the problem of GPS longitude and latitude coordinate drift.

Description

technical field [0001] The invention relates to the technical field of path adjustment, in particular to a method and device for adjusting a path trajectory. Background technique [0002] The GPS sensor can be used to obtain the latitude and longitude coordinate information of the current location on the earth. According to the price of the GPS sensor, the positioning accuracy of the GPS sensor will vary greatly; the accuracy of professional GPS equipment is very high, and it can be accurate to within one meter. But the price is very expensive; and now smart phone manufacturers are equipped with GPS sensors inside the smart phone. In order to save costs, they usually use low-precision GPS sensors, which makes the tracking trajectory obtained inaccurate. The coordinates will drift greatly, resulting in very inaccurate movement distance of the measured tracking trajectory. [0003] At present, there are many solutions to the problem of GPS latitude and longitude coordinate dr...

AI Technical Summary

Problems solved by technology

However, there are certain defects in wavelet transform. The optimization effect of wavelet transform is very good, but wavelet transform is usually for data with a large amount of data, and the optimization effect for small data is relatively poor; although kalman filter can achieve the effect of real-time filtering, but kalman filter Only some fine-tuning of the data can be done, and the problem of drift suppression cannot be solved well. The two kalman filters have deviated from the main direction of motion, from figure 1 The results can be seen

The GPS latitude and longitude data is time series data, that is to say, the data is obtained in real time, and it is necessary to optimize the tracking trajectory in real time and calculate the movement distance, but the above solutions cannot meet the needs very well.

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