Target positioning and correction method for UAV multi-frame images based on continuity between frames

Abstract

The invention provides a multi-frame image target positioning and correction method of an unmanned aerial vehicle based on the continuity between frames, and belongs to the technical field of remote sensing image processing. The present invention aims at continuous frames of aerial images that meet the requirements of inter-frame overlap rate, and makes full use of the telemetry parameters provided by the drone to calculate the overlap rate of adjacent frame images. When the overlap rate is greater than the set minimum threshold value, according to the common point The corresponding two rays of the same name in the continuous frame images meet the coplanar condition to establish constraints, and the relative-absolute positioning method is combined with the telemetry information of the UAV to realize the compensation of the error of the attitude information. The present invention maintains the accuracy of the first image with ground control points to subsequent images with overlapping areas, so that subsequent images that do not contain ground control points can still have high positioning accuracy, and the number of iterations is reduced through coarse correction, integrating The determination of the geometric model and the calculation of the geographical location reduce the amount of calculation and realize the real-time performance of data calculation.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a target positioning and correction method for multi-frame images of an unmanned aerial vehicle based on the continuity between frames. Background technique [0002] With the continuous development of electronic information technology, UAVs have gradually been widely used in military and civilian fields. Among them, an important one is to use drones to target the ground. However, in most cases, due to some objective limitations, such as installation errors and low accuracy of measurement units, the attitude information of UAVs often contains certain errors, resulting in low target positioning accuracy. The freedom of the shooting attitude of the drone often makes the obtained aerial images have certain distortions. This not only affects the intuitive cognition of the detection area, but also has a great impact on subsequent related image proc...

AI Technical Summary

Problems solved by technology

However, due to the limitation of the accuracy of input data such as UAV position and orientation information, the accuracy of target positioning is low.

And, if figure 1 As shown, for the overlapping characteristics of adjacent frames in the aerial photography process of UAV, the above methods do not make good use of this characteristic

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