---
license: apache-2.0
task_categories:
  - robotics
language:
  - en
tags:
  - dmian
  - navigation
  - imu
  - dvl
  - marine
---
# DMIAN Dataset

Navigation dataset consisting of synchronized IMU, DVL, and ground truth data collected on the H2OmniX ASV. It was used in the following paper: "DMIAN: Deep Learning-Based Multi-IMU Fusion for Enhanced Marine Aided Navigation".

## Dataset Details
 
| Sensor | Rate | Fields |
|--------|------|---------|
| IMU (x3) | 100 Hz | acc_x, acc_y, acc_z, gyro_x, gyro_y, gyro_z, timestamp |
| DVL | 5 Hz | vx, vy, vz, cov_xx, cov_xy, cov_xz, cov_yx, cov_yy, cov_yz, cov_zx, cov_zy, cov_zz, timestamp |
| Ground truth | 10 Hz | vel_x, vel_y, vel_z, pos_x, pos_y, pos_z, qw, qx, qy, qz, ang_vel_x, ang_vel_y, ang_vel_z, timestamp |
 
All sensor data are expressed in the vehicle base frame, and each file is in `.npy` format.

## Citation

If you use this dataset, please cite:

```bibtex
@article{batos2026dmian,
  title = {{DMIAN}: deep learning-based {Multi-IMU} fusion for enhanced marine aided navigation},
  author = {Bato\v{s}, Matko and Na\dj{}, \DJ{}ula},
  journal = {Control Engineering Practice},
  volume = {173},
  pages = {106991},
  year = {2026},
  issn = {0967-0661},
  doi = {10.1016/j.conengprac.2026.106991},
  url = {https://www.sciencedirect.com/science/article/pii/S0967066126002352}
}
```

### Contact

For questions or collaborations, contact: 
[Matko Batoš](mailto:matko.batos@fer.unizg.hr)