pywayne-calibration-magnetometer-calibration

Pywayne Calibration

pywayne.calibration.MagnetometerCalibrator provides magnetometer calibration using sensor data (accelerometer, gyroscope, magnetometer).

Quick Start

from pywayne.calibration import MagnetometerCalibrator
import numpy as np

# Sensor data: ts (N,), acc (N,3), gyro (N,3), mag (N,3)
calibrator = MagnetometerCalibrator(method='close_form')
Sm, h = calibrator.process(ts, acc, gyro, mag)

# Sm: Soft-iron matrix (3x3)
# h: Hard-iron offset vector (3,)

Input Data Format

Sensor data must be numpy arrays with matching sample counts:

ts   # (N,)     - Timestamps (seconds)
acc  # (N, 3)   - Accelerometer [ax, ay, az]
gyro # (N, 3)   - Gyroscope [gx, gy, gz]
mag  # (N, 3)   - Magnetometer [mx, my, mz]

Data requirements:

• Sensor data should cover various orientations for effective calibration
• Minimum data points required (exact number depends on calibration stability)
• Arrays must be C-contiguous (auto-converted internally)

Calibration Parameters

process() returns:

Parameter	Shape	Description
Sm	(3, 3)	Soft-iron matrix
h	(3,)	Hard-iron offset vector

Usage in Application

Apply calibration to raw magnetometer readings:

# Calibrated reading
m_calibrated = Sm @ (m_raw - h)

Temporal Calibration

Temporal calibration module exists but is reserved for future expansion. Currently no functionality is implemented.

Important Notes

• Dependencies: Requires vqf (VQF quaternion filter) and qmt (quaternion math) modules
• Method: Currently only supports close_form method
• Orientation: Uses VQF for sensor fusion and orientation estimation during calibration
• Performance: process() uses VQF/qmt batch operations and solves the final accumulated calibration matrix once
• Output: Prints calibration parameters during processing