An Autonomous Positioning Method for Drones in GNSS Denial Scenarios Driven by Real-Scene 3D Models
Drones are extensively utilized in both military and social development processes. Eliminating the reliance of drone positioning systems on GNSS and enhancing the accuracy of the positioning systems is of significant research value. This paper presents a novel approach that employs a real-scene 3D m...
Saved in:
| Main Authors: | Yongqiang Cui, Xue Gao, Rui Yu, Xi Chen, Dingwen Wang, Di Bai |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/1/209 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Entity-Driven New Paradigm of Mine Data: Model Construction and Application
by: Wenjing Li, et al.
Published: (2024-12-01) -
Accelerated Reconstruction of Scenes Using CUDA-Based Parallel Computing
by: Gui Zou, et al.
Published: (2025-01-01) -
Semantic Segmentation and Reconstruction of Indoor Scene Point Clouds
by: HAO, W., et al.
Published: (2024-08-01) -
A Method for Measuring the Error Rules in Visual Inertial Odometry Based on Scene Matching Corrections
by: Haiqiao Liu, et al.
Published: (2024-11-01) -
An automated construction method of 3D knowledge graph based on multi-agent systems in virtual geographic scene
by: Yukun Guo, et al.
Published: (2025-12-01)