Scale invariant feature transform-based unmanned aerial vehicle scene matching positioning method

Abstract

The invention relates to a scale invariant feature transform-based unmanned aerial vehicle scene matching positioning method. The scale invariant feature transform-based unmanned aerial vehicle scene matching positioning method is characterized by comprising the following steps of 1, extracting feature description vectors of an image of a matching target and a front-lower view of an unmanned aerial vehicle by a scale invariant feature transform algorithm, 2, determining if the front-lower view in the frame and the image of the matching target are matching or not, and 3, if the front-lower view and the image of the matching target are matching, recording coordinates of a matching point in a satellite map comprising the image of the matching target and the matching target, in the front-lower view of the unmanned aerial vehicle, calculating current position coordinates of the unmanned aerial vehicle in the satellite map according to the coordinates of the matching point and carrying out positioning of the unmanned aerial vehicle, and if the front-lower view and the image of the matching target are not matching, reading an unmanned aerial vehicle front-lower view in the next frame and sequentially carrying out matching. The scale invariant feature transform-based unmanned aerial vehicle scene matching positioning method realizes accurate matching of a front-lower view of an unmanned aerial vehicle and a matching target in a satellite map, determination of current position coordinates of the unmanned aerial vehicle according to a built unmanned aerial vehicle front-lower view model, and positioning of the unmanned aerial vehicle.

Description

technical field [0001] The invention relates to a scene matching and positioning method of an unmanned aerial vehicle based on scale-invariant feature transformation, which is applied to the scene matching and positioning of the unmanned aerial vehicle. Background technique [0002] With the rapid development of aviation technology, unmanned aerial vehicles and related technologies have become the focus of competing research in various countries. Unmanned aerial vehicles, with their stronger maneuverability, smaller weight, better aerodynamic performance, and lower cost , Better environmental adaptability. At present, in addition to the unmanned aerial vehicles already in use, European and American countries are still researching new unmanned aerial vehicle technologies, and my country is also engaged in research on related technologies. [0003] Among the many technologies involving unmanned aerial vehicles, the positioning technology of unmanned aerial vehicles is an extr...

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Problems solved by technology

[0004] Scholars at home and abroad have also carried out some research on scene matching and positioning, such as using continuous multi-frame matching to reduce matching errors. This method can improve matching efficiency, but because it is multi-frame matching, it will increase the time consumption of matching; there is also a This type of method is based on single-frame matching, which takes less time to match, but it is easy to cause matching errors. In this case, finding accurate image feature extraction methods and similarity measurement methods becomes the key point of single-frame matching.

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