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Thus an accelerometer and a magnetometer alone can give us the DCM matrix , expressed either as DCM B or DCM G DCM matrix start with [1,0,0][0,1,0][0,0,1] and change a few from the first 10-20 seconds. Then first and second row's start to change. I.i vector start to decrease while I.j vector increase. normalization is ok, becouse module of each row is 1. and orthonormalization is ok too becouse de cross product of first and second row is equal to 3rd row:

I tried to implement the code you provide in Java. I display the rotation using a cube in openGL. But I’m running into a some problem: As shown is this figure : http://1.bp.blogspot.com/-Pbm54grQzxo/T_YOtu6wsyI/AAAAAAAABD0/hr3CRHdzzu8/s1600/imu_est2.pngTo analyze the data I have developed a small utility called SerialChart. It is open-source so feel free to customize it for your own needs. Big thanks for this tutorial. I’ve been brought here because I’m developing an Android app that is trying to calculate best YAW (azimuth) angle possible. The Android SDK provide a method to get the OrientationMatrix but it’s really buggy. This is way I wanted to give a try to the DCM. My phone is 9DOF (3axes accel + gyro + magneto) We’ll work with the DCM matrix that consists of the versors of the global (earth’s) coordinate system aligned on each row:

Note: we use {…} T notation to denote a column vector, in other words a column vector is a translated row vector. The orientation of vectors (row/column) will become relevant once we start multiplying them by a matrix later on in this text. if a shake a bit the phone “sometimes” it stabilies !! and seemed to work really well “visualy” the cube behave exactly how I want (pitch, roll yaw)

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It is now easy to notice that DCM B = (DCM G) T or DCM G = (DCM B) T , in other words the two matrices are translates of each other, we’ll use this important property later on.