A U-Net conditional diffusion model synthesizes virtual high-grade IMU data from low-cost measurements, yielding improved positioning and attitude estimates plus better airborne point clouds.
Pedestrian Inertial Navigation Based on Full-Phase Constraints of Lower Limb Kinematics
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Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning
A U-Net conditional diffusion model synthesizes virtual high-grade IMU data from low-cost measurements, yielding improved positioning and attitude estimates plus better airborne point clouds.