RTK Kalman filtering optimization method for unmanned aerial vehicles

Abstract

The invention provides an RTK Kalman filtering optimization method for unmanned aerial vehicles, which comprises the following steps: an acquisition terminal located on an unmanned aerial vehicle acquires a plurality of geodetic coordinates of the unmanned aerial vehicle under a WGS-84 coordinate system, a state equation and an observation equation of Kalman filtering under a nonlinear dynamic system are established, and a Kalman filtering model is established according to the state equation and the observation equation of Kalman filtering; an initial state of the nonlinear dynamic system is determined, namely, a state parameter initial value, a variance matrix initial value and a dynamic noise initial variance matrix of an initial epoch are confirmed; and based on the state equation and the observation equation of the initial epoch, the state parameter initial value, the variance matrix initial value and the dynamic noise initial variance matrix are filtered by a Kalman filtering recursion equation to obtain a filtering value. The positioning precision of unmanned aerial vehicles can be improved.

Description

technical field [0001] The invention relates to the technical field of UAV positioning, in particular to an RTK Kalman filter optimization method and system for UAVs. Background technique [0002] With the development of industrial automation and UAV technology, the traditional manual power inspection method can no longer meet the current real-time, efficient and accurate operation requirements of the power grid. Processing efficiency is extremely low. The development of science and technology drives the transformation of operation methods. UAV inspection will become the mainstream method of power inspection in the future. However, there are still certain technical difficulties in UAV inspection at present, such as automatic positioning, automatic navigation, image processing, etc. At present, The positioning technology and method used usually have the problem of large deviation of elevation information and inaccurate positioning, and the Kalman filter algorithm is a good s...

AI Technical Summary

Problems solved by technology

[0002] With the development of industrial automation and UAV technology, the traditional manual power inspection method can no longer meet the current real-time, efficient and accurate operation requirements of the power grid. Very low processing efficiency

The development of science and technology drives the transformation of operation methods. UAV inspection will become the mainstream method of power inspection in the future. However, there are still certain technical difficulties in UAV inspection at present, such as automatic positioning, automatic navigation, image processing, etc. At present, The positioning technology and method used usually have the problem of large deviation of elevation information and inaccurate positioning, and the Kalman filter algorithm is a good solution

Images