In mobile phones and other devices using a 3-axis electronic compass, a ∞/8/S shaped movement is used to calibrate the magnetometer as shown in these videos.

Why is this movement performed, what is the theory, and can anyone give some example C code to implement it?

You must have to go through my another similar question containing more info.

Some additional info for this particular question:

The platform is 8-bit AtMega32, using AVR Studio 5.

Till now I've tried:

I tried **dividing the average by 2** of vector values of the Magnetometer making the shape. Thinking might help in calculating offsets. I think some how the two identical parts/sides of the shape is cancelling the earth's magnetic field and giving out the offset values. I might be wrong. But particularly for the shape based calibration this is where I am currently. I think the calibration works out this way. The idea is to find out does that work out this way?

Ok the code by which I can calculate the offsets and later simply subtract those from the Raw magnetic 3D vector. I might be totally wrong and have no explanation how it works. Seeing after the video and the data plotted on the sphere, somehow has accelerated my thought and I used that thought on form of equation. B)

Code:

The `Read_accl();`

and `Read_magnato(1);`

functions are reading the sensor data. I hope the code is self explanatory. Hoping wise ppl will surely be using this in much better ways. :\

```
void InfinityShapedCallibration()
{
unsigned char ProcessStarted = 0;
unsigned long cnt = 0;
while (1)
{
Read_accl();
// Keep reading Acc data
// Detect Horizontal position
// Detect Upside down position
// Then detect the Horizontal position again.
// Meanwhile an infinity shaped movement will be created.
// Sum up all the data, divide by the count, divide by 2 .
// !We've offsets.
if (ProcessStarted!=3)
{
//
//USART_Transmit_String("\r");
//rprintfFloat(4, g_structAccelerometerData.accx_RAW);
//USART_Transmit_String(",");
//rprintfFloat(4, g_structAccelerometerData.accy_RAW);
//USART_Transmit_String(",");
//rprintfFloat(4, g_structAccelerometerData.accz_RAW);
}
if (
abs( g_structAccelerometerData.accx_RAW) < 100
&& abs(g_structAccelerometerData.accy_RAW) < 100
&& g_structAccelerometerData.accz_RAW < -350
&& ProcessStarted != 2 && ProcessStarted != 3 && ProcessStarted != 1 )
{
ProcessStarted = 1;
}
if (ProcessStarted==1)
{
Read_magnato(1);
structMagnetometerOffsetDataToEEPROM.Off_X += g_structMegnetometerData.magx_RAW;
structMagnetometerOffsetDataToEEPROM.Off_Y += g_structMegnetometerData.magy_RAW;
structMagnetometerOffsetDataToEEPROM.Off_Z += g_structMegnetometerData.magz_RAW;
cnt++;
}
if ( g_structAccelerometerData.accz_RAW > 350
&& ProcessStarted==1)
{
ProcessStarted = 2;
}
if ( g_structAccelerometerData.accz_RAW < -350
&& ProcessStarted == 2 )
{
ProcessStarted=3;
structMagnetometerOffsetDataToEEPROM.Off_X /= cnt;
structMagnetometerOffsetDataToEEPROM.Off_X /= 2;
structMagnetometerOffsetDataToEEPROM.Off_Y /= cnt;
structMagnetometerOffsetDataToEEPROM.Off_Y /= 2;
structMagnetometerOffsetDataToEEPROM.Off_Z /= cnt;
structMagnetometerOffsetDataToEEPROM.Off_Z /= 2;
UpdateOFFSETDATAinEEPROM();
break;
}
}
}
```

After getting these offsets I used them as follows:

```
void main()
{
...
Read_magnato(1);
g_structMegnetometerData.magx_RAW -= structMagnetometerOffsetDataToEEPROM.Off_X ;
g_structMegnetometerData.magy_RAW -= structMagnetometerOffsetDataToEEPROM.Off_Y ;
g_structMegnetometerData.magz_RAW -= structMagnetometerOffsetDataToEEPROM.Off_Z ;
...
}
```

As I mentioned.

## Best Answer

The 8/S shaped pattern is used to calibrate magnetometers in mobile phones and other devices.

BackgroundTypical mobile phone era magnetometers measure the magnetic field strength along three orthogonal axes, e.g.:

\$\textbf{m} = m_x\boldsymbol{\hat{\imath}} + m_y\boldsymbol{\hat{\jmath}} + m_z\boldsymbol{\hat{k}}\$

With the magnitude of the field given by,

\$\|\textbf{m}\| = \sqrt{m_x^2 +m_y^2 + m_z^2}\$

and the angle of rotation from each axis as

\$ \theta_k = \cos^{-1} \frac{m_k}{ \| \textbf{m} \| }, \text{ where } k \in [x,y,z] \$

CalibrationSince the magenetic field of the earth is relatively constant, the magnitude of the as field measured by the magnetometer should also be constant,

regardlessof the orientation of the sensor. i.e. if one were to rotate the sensor around and plot \$m_x\$, \$m_y\$, and \$m_z\$ in 3D, the paths should plot out the surface of a sphere with constant radius.Ideally it should look somthing like this:

However due to hard and soft iron effects and other distortions, it ends up looking like a deformed sphere:

This is because the magnitude of the magnetic field as measured by the sensor is changing with orientation. The result being that the direction of the magnetic field when calculated according to the formulas above is different from the true direction.

Calibration must be performed to adjust each of the three axis readings so that the magnitude is constant regardless of orientation - you can think of it as the deformed sphere must be warped into a perfect sphere. The LSM303 application note has lots of detailed instructions on how to perform this.

So what about the figure 8 pattern!?Performing the figure 8 pattern 'traces out' part of the deformed sphere above. From the coordinates obtained, the deformation of the sphere can be estimated, and the calibration coefficients obtained. A good pattern is one that traces through the greatest range of orientations and therefore estimates the greatest deviation from the true constant magnitude.

To estimate the shape of the deformed sphere, least squares ellipse fitting can be used. The LSM303 application note also has information on this.

A simple method for a basic calibrationAccording to the app note if you assume no soft-iron distortion, the deformed sphere will not be tilted. Therefore a simple method for a basic calibration may be possible:

\$r_k = \tfrac{1}{2} (\max(m_k) - \min(m_k))\$

\$z_k = \max(m_k) - r_k\$

\$m_k' = \frac{m_k - z_k}{r_k}\$

This is based off the code found here.

Solving using least squaresMATLAB code to solve using least squares is shown below. The code assumes a variable

`mag`

where the columns are the x y z values.To do a dynamic figure 8 calibration, you could run the least squares routine with every new reading and terminate when the offset and scale factors have stabilised.

Earth's Magnetic FieldNote, the Earth's magnetic field is usually

notparallel to the surface and there may be a large down component.