Target geolocation system and method based on drone imagery

By using a target geolocation system based on UAV imagery and employing a 2.5D reference map and PnP ray projection algorithm, the problem of limited accuracy in UAV target geolocation was solved, achieving high-precision and robust geolocation and promoting the standardization of the technology.

CN122108064APending Publication Date: 2026-05-29NAT UNIV OF DEFENSE TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
NAT UNIV OF DEFENSE TECH
Filing Date
2026-02-06
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing UAV target geolocation methods are limited by UAV attitude estimation errors and the availability of accurate altitude prior data, resulting in limited positioning accuracy and difficulty in achieving efficient and accurate target geolocation in complex environments.

Method used

A target geolocation system based on UAV imagery is adopted, including a data acquisition module, an end-to-end geolocation module, and a benchmark testing and evaluation module. It utilizes a 2.5D reference map, feature matching, and a PnP-based ray projection algorithm, combined with a RANSAC attitude estimation strategy, to achieve high-precision 3D geolocation.

Benefits of technology

It improves geolocation accuracy and system robustness, adapts to multiple scenarios and environmental conditions, provides objective evaluation standards, and promotes the standardized development of target geolocation technology.

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Abstract

The present application belongs to the field of computer vision and remote sensing photogrammetry, aiming at the problem of being limited by the attitude estimation error of unmanned aerial vehicle and the altitude prior data in the prior art, a target geolocation system and method based on unmanned aerial vehicle image are proposed, the system at least includes a data acquisition module, an end-to-end geolocation module and a benchmark test evaluation module. The method uses the data acquisition module to obtain a data set containing a reference map, a query image and target label information as the data basis and evaluation benchmark of the target geolocation system; the end-to-end geolocation module receives the reference map and the query image, designs a target positioning algorithm, and calculates the geographic coordinates of the target points in the query image; the benchmark test evaluation module quantitatively evaluates the geolocation performance based on the RANSAC homography and the PnP-based pose estimation strategy. The present application improves the geolocation accuracy and reliability by using the system and method.
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