We have used an SMC-108 IMU sensor in a hydrographic survey. This was our first time using this sensor. While processing the data, we noticed that the roll, pitch, and heave values were not right. Turns out, this IMU sensor has to be aligned in a specific orientation to be giving the correct values. We had our IMU oriented in a different direction from what it should be (See image below).

Is there any way we can correct for this misalignment and get the correct roll, pitch and heave information?

Thanks in advance.enter image description here

  • $\begingroup$ What prevents you from reinstalling the IMU in the correct orientation? $\endgroup$
    – goddar
    Mar 28, 2018 at 1:50
  • $\begingroup$ @goddar- The survey has been done in the past. The data currently has wrong roll, pitch and heave values. I need to get the correct values into the data to process and make some meaningful interpretations. $\endgroup$
    – Thoram
    Mar 28, 2018 at 1:57
  • $\begingroup$ You could convert them to a rotation matrix or unit quaternion, apply the rotation of the sensor (and optionally convert them back to roll pitch yaw). $\endgroup$
    – fibonatic
    Mar 28, 2018 at 2:29

1 Answer 1


It seems that only the orientation is not the desired one. Hence you get correct values but they are not the one you expected.

To make it systematic I would propose you to build the transformation matrix between your desired sensors location and the one what was used in the survey. This way you get a framework also working if the position of the sensor is off. see http://www.diag.uniroma1.it/~deluca/rob1_en/08_EulerRPYHomogeneous.pdf for some theory

Then you can build the transformation matrix of your sensor reading, aka a rotation matrix construct from the angles, then by multiplying the two transformation matrix you wold get the transformation matrix of your measurements at the give point. It is up to you to go back to roll, pitch, yaw angles. Note that RPY are ambiguous and subject to gimbals lock phenomena, hence rotation matrices are preferred even if they are less compact.

A comprehensive guide to go from one orientation representation to the next, https://www.swarthmore.edu/NatSci/mzucker1/papers/diebel2006attitude.pdf


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