Simulated Dataset Calibration

We provide two examples for calibration and evaluation of the MAGYC and benchmark methods as jupyter notebooks. The notebooks are available in the examples directory, and to use them is neccesary to build poetry as:

poetry build

Then, you will have all the required dependencies installed.

MAGYC Example - Simulated Data Calibration & Self Evaluation

Jupyter Notebook

This notebook demonstrates how to use the MAGYC algorithms to calibrate a magnetometer and gyroscope using simulated data and provides a comparison with benchmark methods for calibration. Then, the results are self evaluated.

The calibration dataset corresponds to the simulated data used in the paper: "Full Magnetometer and Gyroscope Bias Estimation Using Angular Rates: Theory and Experimental Evaluation of a Factor Graph-Based Approach" by S. Rodríguez-Martínez and G. Troni, 2024. The dataset is available on Google Drive.

MAGYC Example - Simulated Data Cross-Validation

Jupyter Notebook

This notebook evaluates the MAGYC and benchmark algorithms formagnetometer and gyroscope calibration using simulated data. The calibration dataset corresponds to the simulated data used in the paper: "Full Magnetometer and Gyroscope Bias Estimation Using Angular Rates: Theory and Experimental Evaluation of a Factor Graph-Based Approach" by S. Rodríguez-Martínez and G. Troni, 2024. The dataset is available on Google Drive.