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I currently have an error state Kalman filter with the state vector $(p, v, q, \omega, a, g)$ where $q$ is the quaternion orientation. I would like to add the information coming from a magnetometer to this sensor fusion.

I have calibrated the magnetometer and we can assume that we are getting processed data at the point of input to the filter.

  1. How do I extend my state vector to account for the new input, or since I do not directly care about estimating it, should I not include it?
  2. I think that I can initialize my initial state vector correctly by performing TRIAD using the magnetic field vector, is this the right approach?
  3. How does the magnetic field vector help in stabilizing my quaternion attitude?

I tried to search around but I didn't find many resources on how the math works when I include the magnetometer. Any links would be very helpful as well.

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    $\begingroup$ what is the state you are estimating? what is TRIAD? $\endgroup$
    – holmeski
    Nov 2, 2016 at 0:35
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    $\begingroup$ Have you considered the Madgwick filter? A free, open-source filter with code already provided in C, C#, and Matlab, that does quaternion-based pose estimation from an IMU and magnetometer, and performs as well as or better than a Kalman filter? From the paper, "Empirical testing and benchmarking has shown that the filter performs as well as a high quality commercial Kalman-based system, even with a full order of magnitude in reduction of sampling rate." $\endgroup$
    – Chuck ♦
    Nov 2, 2016 at 13:38

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I doubt you need to add anything to the state vector regarding the magnetometer calibration. The magnetometer measurement should just be treated at another signal that triggers a measurement/correction update.

Adding the magnetometer makes yaw ( how much you've turned) observable. Without the mag you will just be integrating gyro measurements.

"Three-axis attitude determination via Kalman filtering of magnetometer data"

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  • $\begingroup$ Are you aware of any papers that describe the process (i.e. magnetometer readings to state vector). Thank you! $\endgroup$
    – Nopestradamus
    Nov 2, 2016 at 9:35
  • $\begingroup$ @Nopestradamus, you apply an update step, just like any other measurement. $\endgroup$
    – Josh Vander Hook
    May 6, 2017 at 7:22

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