New UAV Navigation Estimator version: now with OLHIC

UAV Navigation is proud to present its latest Estimation software update (v5.54), featuring the Online Hard Iron Calibration (OLHIC) capability.


1.   The ability to perform on-board, autonomous magnetometer calibration in real time without ground support is a challenge for all modern aircraft, including UAVs.

2.   In UAV Navigation autopilots the magnetometer is integrated into the IMU to assist with computing attitude and heading. It measures the x y and z components of the Earth's magnetic field, which is well known and modelled. See for more detail.  

3.   Measurements taken by the magnetometer are affected by the platform on which it is installed, producing an offset and a distortion named hard iron and soft iron respectively. The more ferromagnetic parts the platform has, the stronger the hard and soft iron effects are.

4.   Following installation, the magnetometer must be calibrated to offset hard and soft iron variations before it can produce reliable readings. Calibration involves physically moving the platform in all possible orentations in order to collect magnetic sensor measurements and to perform a mathematical regression. This is a process that is performed once and remains valid as long as the magnetic environment of the platform is not changed. Practice shows that magneto-resistive sensor (commonly used in Attitude and Heading Reference Systems AHRS) scale factors and distortion (soft iron) are very stable with time.

5.   On the other hand, sensor bias is subject to temperature variation and is not very stable. It may change slowly in flight or might change with the passage of time. This behaviour is inconvenient with regards to the calculations performed by the autopilot. The changes may prevent the AHRS from working or might even produce a significant error in heading. If this sensor bias occurs, the user is forced to perform a complete calibration again just to correct sensor bias. Rotating a small aircraft in all orientations can be done, even if it takes time. However it is not practical for larger platforms.

6.   From the above it can be concluded that there is a clear need to compensate for this offset random variation. The best way to do it is by using an online algorithm that is kept running in the background of the AHRS real time processor. Just by flying and changing heading every once in a while it is possible to identify and compensate the sensor offset (hard iron).

7.   In summary, the first time an AHRS is installed in an aircraft a full magnetic calibration (soft iron and hard iron) must be carried out. This full calibration must be repeated should the aircraft's magnetic environment change, which in practice is very unusual. From this point onwards, the OLHIC system will automatically correct any magnetic offset.


8.   OLHIC is a lightweight, recursive algorithm based on a simple idea: regardless of aircraft orientation (pitch, roll and heading) the magnetic field module remains constant (i.e. World Magnetic Model - WMM). If in any particular orientation the magnetic field is greater than expected, then sensor bias (hard iron) can be corrected in the opposite direction. Therefore simply by flying and changing heading every so often the correct hard iron value is achieved.




9.   Other autopilots generally do not use internal, integrated magnetometers as part of their AHRS. In those cases where an internal magnetometer is present it is generally only used in a secondary role to estimate the heading of the platform in 2D. The reason that this simplistic approach is used is probably to do with the difficulties associated with calibration.

10.   UAV Navigation's OLHIC solution overcomes the problems associated with calibration in order to provide useful magnetometer information in 3D (Roll, Pitch and Yaw).

11.   The main advantages of using a 3D internal magnetomer are:

  • Attitude estimation is more precise in every orientation: roll, pitch and especially in yaw.
  • The attitude provided is more robust in the presence of sensor failures (i.e. GPS or other IMU sensor failure).  
  • It allows the autopilot to continue to function in a GPS denied environment by continuing to provide excellent heading estimation. This crucial strength of the UAV Navigation system is one of the weaknesses found in other AHRS units on the market.
  • UAV Navigation's Estimator uses an embedded model of the global magnetic field. This model provides information about the theoretical magnetic field for any location on the Earth's surface and also the magnetic declination and inclination. This information is used to calculate and reduce any existing error in the measurements provided by the magnetometer.
  • The magnetometer, combined with the information provided by the ADS (Air Data System), allows a very accurate calculation of wind direction and speed to be obtained. Using this information, the slip angle can be accurately obtained (slip angle is that formed between wind and body axes). This additional advantage of the UAV Navigation system provides improved navigation for all types of platform by reducing the slip angle; in contrast competitor products use only GPS information and the influence of the wind is not evaluated.