A Multi-Sensor Fusion Approach for Rapid Orthoimage Generation in Large-Scale UAV Mapping
Journal:
arXiv
Published Date:
Mar 3, 2025
Abstract
Rapid generation of large-scale orthoimages from Unmanned Aerial Vehicles
(UAVs) has been a long-standing focus of research in the field of aerial
mapping. A multi-sensor UAV system, integrating the Global Positioning System
(GPS), Inertial Measurement Unit (IMU), 4D millimeter-wave radar and camera,
can provide an effective solution to this problem. In this paper, we utilize
multi-sensor data to overcome the limitations of conventional orthoimage
generation methods in terms of temporal performance, system robustness, and
geographic reference accuracy. A prior-pose-optimized feature matching method
is introduced to enhance matching speed and accuracy, reducing the number of
required features and providing precise references for the Structure from
Motion (SfM) process. The proposed method exhibits robustness in low-texture
scenes like farmlands, where feature matching is difficult. Experiments show
that our approach achieves accurate feature matching orthoimage generation in a
short time. The proposed drone system effectively aids in farmland detection
and management.
