Unmanned aerial vehicle image positioning and attitude determination method and unmanned aerial vehicle

Abstract

The embodiments of the present invention disclose an unmanned aerial vehicle image positioning and attitude determination method and an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles. The unmanned aerial vehicle image positioning and attitude determination method comprises: acquiring camera internal reference, images and on-board POS data; carrying out distortion correction on the images according to the camera internal reference to obtain distortion-free images; extracting the feature points and the feature descriptions from the distortion-free images;carrying out constraint by using the on-board POS data to complete the rough matching of the features; carrying out relative orientation to obtain the essential matrix between the images; extractingthe feature points and the feature descriptions from the distortion-free images; carrying out rapid high-precision matching by using the essential matrix in the rough matching as epipolar constraint;calculating the correlation between the images; obtaining a subgraph through a regional growth method; and carrying out incremental reconstruction in the subgraph, and then carrying out global optimization reconstruction, and adding the camera internal reference during the global optimization reconstruction so as to finally obtain the precise position and the precise attitude of the unmanned aerial vehicle image. With the method and the unmanned aerial vehicle of the present invention, the accuracy of the unmanned aerial vehicle image positioning and attitude determination can be improved.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicles, in particular to a method for positioning and attitude determination of an unmanned aerial vehicle image and an unmanned aerial vehicle. Background technique [0002] The rapid acquisition of images of regions of interest by UAVs has gradually become an important branch of the current development of aerial photogrammetry. Compared with traditional aerial photogrammetry images, the images acquired by UAVs have the advantages of high spatial resolution and high temporal resolution. [0003] However, limited by the safety and load capacity of the UAV system, the UAV is usually equipped with a relatively cheap non-measurement camera. This type of camera has the following characteristics: (1) The image size is small, generally no more than one 100 million pixels, so the number of images is particularly huge; (2) the amount of distortion is large, and the amount of distortion at the e...

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Problems solved by technology

[0003] However, limited by the safety and load capacity of the UAV system, the UAV is usually equipped with a relatively cheap non-measurement camera. This type of camera has the following characteristics: (1) The image size is small, generally no more than one 100 million pixels, so the number of images is particularly huge; (2) the amount of distortion is large, and the amount of distortion at the edge of the image can reach more than 200 pixels, which requires a high-order equation to express well; (3) poor consistency, different cameras of the same model It is difficult to adapt all cameras of the same model with a set of parameters.

For this reason, the processing of massive UAV images often has problems such as low efficiency, difficulty in correctly correcting distortion, and unstable processing results.

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