Unmanned aerial vehicle target positioning method and system

Abstract

The invention provides an unmanned aerial vehicle target positioning method and system. The method comprises the steps that an image feature database of a satellite remote sensing image is established; an unmanned aerial vehicle reconnaissance image is acquired and preprocessed; multi-scale image feature extracting is carried out on the preprocessed unmanned aerial vehicle reconnaissance image; an image retrieval similarity measurement model based on granular computing is established, and matching computing is carried out on the extracted image features and image features in the image feature database according to the image retrieval similarity measurement model to acquire a similarity measurement value; and the geographic position corresponding to the satellite remote sensing image with the similarity measurement value satisfying a preset threshold value is determined as the unmanned aerial vehicle target position. The method and system can accurately position an unmanned aerial vehicle target.

Description

technical field [0001] The invention relates to the field of UAV target positioning, in particular to a method and system for UAV target positioning. Background technique [0002] The dependence of modern warfare on information makes drones play an increasingly important role. The outstanding performance of drones in several high-tech local wars has attracted great attention from all countries in the world. Many countries have begun to vigorously develop military drones. technology. In order to meet the requirements of precise strikes in modern information warfare, the use of UAV reconnaissance images to achieve precise positioning of the detection target area in geospatial position is the key technology. The principle is to first model the electronic satellite remote sensing map data and build a database module , and then match the current image taken by the UAV to the corresponding satellite map module information from the massive electronic satellite remote sensing image...

AI Technical Summary

Problems solved by technology

[0003] However, since the UAV is a special flight carrier with complex flight characteristics, high flight speed, and variable imaging conditions, it has more complex image motion characteristics, because it is affected by external factors such as weather, light, and noise. Human-machine reconnaissance images inevitably have low contrast, blur or even occlusion, and due to differences in image acquisition devices, there are inevitably scale changes, rotation changes, and illumination changes between UAV reconnaissance images and remote sensing images in the database.

The target image information cannot be quickly and accurately matched from the massive remote sensing image data, that is, the UAV target positioning in the prior art has a technical defect of low positioning accuracy

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