A novel calibration method for gyroscopes and accelerometers. Contrary to existing methods the proposed one does not require a rotating table or other special equipment. To perform the calibration a user needs to make a series of sequential rotations of inertial measurement unit (IMU) separated by standstill periods.
This is the supplementary code and the implementation of the ideas, presented in IEEE paper [IEEE link].
The proposed approach allows to perform full IMU calibration: scale factors, non-orthogonalities and biases of accelerometer and gyroscope triads and misalignment between them.
The proposed method is quite accurate: the differences between true and estimated sensor errors were less than 0.1% of their true value.
The importance of full gyroscope calibration can be shown through orientation difference between true and gyroscope-integrated orientations. The three cases are shown on the plot:
- No corrections of gyroscope raw data.
- Only gyroscope bias was corrected.
- Gyroscope scale, cross-coupling and bias were corrected.
After the calibration the orientation error is almost zero.
To run the monte-carlo simulations please issue the following command:
python3 run_monte_carlo.py --plot=True
As the output, you will see the true and estimated sensor error parameters and uncalibrated/calibrated measurements for both sensors.
IMUs calibration results for five real sensors (MPU-9150) are shown here:
For real IMU calibration we provide the datasets from five different InvenSense MPU-9150 IMUs. Please note, one important requirement: the sensor has to be kept static after each rotation. The standstill flags are generated automatically from the data using generate_standstill_flags function. To find the calibration parameters issue the following command:
python3 calibrate_real_imu.py --sampling_frequency=100 --file=data/imu0.log
and see the found parameters as the output.
The jupyter notebook is here.
The proposed method has been proven to be unbiased via numerical simulations.
The differences between true and estimated sensor error parameters for 200 Monte-Carlo simulations are shown in the following table:
IMUs calibration results for five real sensors (MPU-9150) are shown here:
This is the accompanying code for "In-situ gyroscope calibration based on accelerometer data" paper that was presented on 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS).
If you use the code, the authors will be grateful for citing:
@inproceedings{mikov2020situ,
title={In-situ Gyroscope Calibration Based on Accelerometer Data},
author={Mikov, Aleksandr and Reginya, Sergey and Moschevikin, Alex},
booktitle={2020 27th Saint Petersburg International Conference on Integrated Navigation Systems (ICINS)},
pages={1--5},
year={2020},
organization={IEEE}
}