nliaudat / magnetometer_calibration

Ellipsoid fitting using python numpy to calibrate magnetometers

Magnetometer calibration

Ellipsoid fitting using python numpy to calibrate magnetometers

Usage :

1. output you raw data from sensor and name it mag_out.txt in format x,y,z (uT)

2. change the "MField" value (line 42) in calibrate.py according to your sensor value (calculation available at begining of calibrate.py)

3. run script and get "Hard Iron Bias" and "Soft Iron bias" matrixes (and c++ according code)

   // Taken from calibrate.py or magcal
    float hard_iron_bias_x =  41.45884154873271 ;
    float hard_iron_bias_y =  -87.79628696573607 ;
    float hard_iron_bias_z =  569.4171225039286 ;
   
   
    double soft_iron_bias_xx =  0.5823136909144911 ;
    double soft_iron_bias_xy =  0.007124620314368133 ;
    double soft_iron_bias_xz =  -0.024442807568982334 ;
   
   
    double soft_iron_bias_yx =  0.00712462031436818 ;
    double soft_iron_bias_yy =  0.5906868599676302 ;
    double soft_iron_bias_yz =  0.005356720947343228 ;
   
   
    double soft_iron_bias_zx =  -0.024442807568982372 ;
    double soft_iron_bias_zy =  0.005356720947343263 ;
    double soft_iron_bias_zz =  0.7210550285247264 ;
    
    // get values x,y,z and subtract the hard iron offset
    float xm_off = id(hmc5883l_x).state - hard_iron_bias_x;
    float ym_off = id(hmc5883l_y).state - hard_iron_bias_y;
    float zm_off = id(hmc5883l_z).state - hard_iron_bias_z;
    
    // multiply by the inverse soft iron offset 
    float xm_cal = xm_off *  soft_iron_bias_xx + ym_off *  soft_iron_bias_yx  + zm_off *  soft_iron_bias_zx;
    float ym_cal = xm_off *  soft_iron_bias_xy + ym_off *  soft_iron_bias_yy + zm_off *  soft_iron_bias_zy;
    //not needed : float zm_cal = xm_off *  soft_iron_bias_xz + ym_off *  soft_iron_bias_yz  + zm_off *  soft_iron_bias_zz;
    
    //float heading = atan2(ym_cal, xm_cal);
    float heading = atan2(0 - xm_cal, ym_cal);
    
    //heading += id(magnetic_declination); 
    
    if(id(enable_magnetometer_serial_output) == true){
    ESP_LOGD("main", "%.1f,%.1f,%.1f", id(hmc5883l_x).state, id(hmc5883l_y).state, id(hmc5883l_z).state);
    }
    // Correct for when signs are reversed.
    if (heading < 0) {
    heading += 2*PI;
    }
    // Check for wrap due to addition of declination.
    if (heading > 2*PI) {
    //heading -= 2*PI;
    }
    float headingDegrees = heading * 180/M_PI; // Convert radians to degrees.
    return headingDegrees;
   

---

If you run esphome, a sample code is included to output raw data and get corrected values.

Working demo

If you want a sample or a working demo, look at https://github.com/nliaudat/weatherstation

Requirements :

calibrate.py requires numpy,scipy and optional matplotlib to plot the graph

Thanks :

John zhang12300 for issuing the bug

jremington for fixing the bug

Sources :

    -  https://teslabs.com/articles/magnetometer-calibration/      
    -  https://www.best-microcontroller-projects.com/hmc5883l.html

magnetometer_calibration's Issues

v_1[3] corresponds to the item xy?

I amd phD candinate John. Recently I studied your code, and I found that there is some unconsistency between the description in https://teslabs.com/articles/magnetometer-calibration/ and your code .
In the decription, the fourth of the v_1, i.e., v_1[3] corresponds to the item yz. However, in your code, v_1[3] corresponds to the item xy. It confused me a lot. Hopefully you can check it and looking forward to receiving your reply soon. Thank you!
M = np.array([[v_1[0], v_1[3], v_1[4]],
[v_1[3], v_1[1], v_1[5]],
[v_1[4], v_1[5], v_1[2]]])

Raw Gravitation Field Value

Hi,
I'm using Wheeltec N100 IMU for the sensor, but i can't find gain value that the sensor use
Is there any chance that i can find Raw Gravitation Field Value (MField) without gain?
or i could find the gain value myself?

Thanks