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Accelerometer + Tilt compensation

Discussion in 'Electronic Design' started by jdhar, Aug 21, 2008.

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  1. jdhar

    jdhar Guest

    I am looking for a method of compensating for tilt in an accelerometer-
    based application... lots of google searches show how to calculate
    tilt with an accelerometer ,but that is not quite what I am looking

    I need to measure 3-axis acceleration of a moving vessel with my
    device.. the problem is the device may not be mounted truly flat. For
    example, if it's tilted slightly on the X-axis, the X-axis will always
    read a slight gravity component at DC, and the Z-axis will have a
    little bit removed.

    The problem is this: If the vessel moves perfectly along the "flat x-
    axis", since my device is slightly tilted on the X-axis, this
    acceleration will result in a change in the Z-axis.

    So I am wondering if there is a way I can "rotate the device" to true
    0 degrees using post-processing/math. If I could do this, then that
    forward motion along the TRUE X-axis would result in a reading that
    only changed the X-axis, not the Z-along with it. I can get samples at
    DC, so I could easily calculate what the starting tilt is. So if at
    DC, the X-axis reads -0.1g and the Z-axis 0.98g for example, I don't
    think it's as simple as adding/subtracting those offsets all the time
    since that doesn't take into account the component of one into the

  2. Frank Buss

    Frank Buss Guest

    If you are using atan2 ( ) to calculate
    the angle between two axis, do this at calibration time and then subtract
    this value from the angle you measure.

    If you want to compensate all 3 axis, an nice solution might be using
    quaternions ( ). Quaternions are
    especially useful, if you want to track movements. A quarternion can be
    used to repesent orientation and rotations:

    E.g. the scripting language of Second Live uses quarternions, for
    controlling the orientation and movement of scripted objects in 3D.
  3. Rich Webb

    Rich Webb Guest

    You have six degrees of freedom that you need to be concerned with:
    translation along each unit vector and also rotation around each.
    Inertial measuring units typically do this with the second derivative of
    translation and the first of rotation, i.e., accelerometers and rate
    gyros. For an unconstrained system, you have to have all six.

    In a constrained system (e.g., it's not moving), you can infer
    orientation by measuring the three-axis acceleration, modulo a correct
    estimate for the local gravity vector and the bias and scale factors of
    your instruments. Well that and earth rate, non-aligned gravity and
    earth's rotational frames of reference, the shape of the geoid, etc.
    Search on "strapdown inertial navigation" ...
    .... but you still need gyros.
  4. neon


    Oct 21, 2006
    try laser diodes and detectors
  5. jdhar

    jdhar Guest

    So I get I can calculate the angle at calibration time... however,
    subtracting this from the angle I measure won't achieve what I need (I
    don't think at least). Once in motion, all I have are 3 forces in the
    X,Y,Z directions... I need a way to translate that initial angle to
    modify those 3 vectors, right?
    These look like an interesting tool... I will have to study it more,
    but thanks for the tip!
  6. Start with asking what you are trying to measure. If you don't need the
    DC, then high pass filtering is your easiest solution.

    Since gravity is just like any acceleration, once you start thinking
    about your problem, you'll see there are some ill-posed aspects. If you
    can find a situation where you can be assured that the platform has no
    acceleration other than gravity, you should be able to correct, but if
    you're talking about a ship, it will be rolling and heaving, so the
    problem is difficult. Consider moving up to a 6-degree of freedom
    system, that has three accelerometers and three gyros, if you can't just
    high-pass filter to remove the low frequency.
  7. jdhar

    jdhar Guest

    Got it. And for my own understanding, a "rate gyro" is simply
    something that measures the rate of change on an angular basis,
    Right, so this is what I could do when the system is at rest... I
    don't think I need to worry about all of those other factors since
    this doesn't have to be that precise.
    Did a quick search... I'm assuming you are referring to the concept as
    opposed to the Book title. Basically, that is what I'm trying to build
    (something fixed to the frame of the vessel)... I didn't think I would
    need a gyro for this application however, and I'm still not quite
    clear why I do. There is no way just knowing the acceleration vectors
    to compensate for an initial tilt?

    To maybe clarify my application, I don't need this INS (if you will)
    to calculate where I am going exactly. What I need is to measure and
    datalog the forces that are being applied in all 3 axis... that's it.
    I just need to remove the cross-coupling from one axis into the other
    due to mounting tilt. So if the vessel moves truly forward, it should
    register acceleration on X only, not X and Z (for eg.). Other than
    that, that's all I need.. I don't need to use that information to
    calculate where I am in reference to a start point.
  8. jdhar

    jdhar Guest

    Thanks Scott... I don't need DC, I'm concerned only with the delta in
    acceleration over time. I'm not sure if highpass will do exactly what
    I need however. If I simply just highpass filter all 3 axes, it won't
    help the fact that moving in one TRUE axis (say movement in true X)
    will couple into 2 axes on the accelerometer due to mounting tilt,
    It seems like 6-degree is where it's going, but I need to fully
    understand why first. The vessel is a boat, but this is for a sports-
    performance based application, so it's not a big ship that is in waves
    or anything. So in short, I could find a situation where there is
    "virtually" no acceleration other than gravity. The problem is I can't
    guarantee the situation where the sensor will be mounted such that
    gravity is only applied on the Z-axis.
  9. Frank Buss

    Frank Buss Guest

    If the sensor is moving in one direction, parallel to ground, you'll
    measure the same like when it is not moving. For simplifying, now one axis
    is in the direction of movement and one vertical. If it accelerates, it
    should be possible to calculate the accleration, if you first calculate
    atan2 of the vertical and the axis in the movement direction, then
    substract the calibration angle and then calculate the movement strength
    with sin or cos of the resulting angle, but I didn't proved it
    mathematically and physically, maybe I'm wrong.

    For 3 axis the same should be possible with quaternions when using
    calibration quaternions. With this concept it should be possible to
    calibrate roll, pitch and yaw, if you do two calibration measurements: one
    not moving and one accelerating in a known direction.

    Maybe some search with Google will get some papers, because I don't think
    you are the first person with such a problem.
  10. Rich Webb

    Rich Webb Guest

    Okay, think I understand what you're aiming for. Conceptually, mount the
    sensor block (the three accelerometers) in the center of a cube, find
    the apparent acceleration for each sensor at each of the six
    orientations, and work backwards from the local gravity vector to find
    the misalignments that would be necessary to yield the observed results.
    Could be done with three orthogonal faces but flipping it upside down
    helps to identify other error sources.
  11. jdhar

    jdhar Guest

    I think I understand what you are trying to say here.. I understand
    what needs to be done conceptually, in my head, the problem is with
    how to actually do the math. I think I may have figured it out though,
    and please correct me if I'm wrong.

    If we stick with the 2-D case of having only X and Y, if I orient the
    sensor incorrectly such that it's rotated by 10 degrees (since there
    is no Z-axis, we'll assume it's perfectly flat), then what I should do
    with any (X,Y) vector that I read out is effectively rotate the vector
    back by 10 degrees. And I think I can use a rotation matrix (http:// It seems to scale to the 3-
    D case too, but I haven't tried that yet. The Quaternions also seem to
    do the same thing in the 3-D case, with just a more compact
    representation and less calculations (which is a good thing!).

    So in the 2-D case, I obviously can't use local gravity to figure out
    the tilt angle since if it's perfectly flat, there will be no gravity
    component in the X or the Y. But in the 3-D case, the magnitude of
    (X,Y,Z) should yield close to 1g, and using these (and atan2), I
    should be able to figure out the 3 rotation angles (I hope), and apply
    the rotation matrix above.

    Nothing like a trip back to fundamental-land...
  12. You'll need to write a sim. The product/instrument
    you are ambiguously specifying needs hardening up.
    I write aerodynamic and astrodynamic sims so I
    might be able to serve as a consultant.
    Off hand, you'll need help with the initial specs,
    physically, and the desired output, defining clearly
    what your client wants, then see how to do the task,
    electronically, based on the sim.
    If your inexperienced with product developement
    then I can do project/program management, it's
    vital to divide the program into maesureable steps.
    Ken S. Tucker
  13. Frank Buss

    Frank Buss Guest

    Some math for the 2D case. First a sketch:

    Assume you have the angle "a" misalignment. Then the vector c is the
    calibration vector (normalize this to length 1 and normalize all other
    measurements with the same factor). You can calculate a=atan2(c_x, c_y). If
    a force in the direction of the x-axis is applied, e.g. the vector v,
    you'll measure m=c+v_rotated. v_rotated is v rotated by "a" and
    m=(c_x+v_x*cos(a)-v_y*sin(a), c_y+v_x*sin(a)+v_y*cos(a)). You can solve
    this for v_x and v_y:
    v_x = (m_x-c_x)*cos(a)+(m_y-c_y)*sin(a)
    v_y = (m_y-c_y)*cos(a)+(c_x-m_x)*sin(a)
    This should work for arbitrary vectors v, not just parallel to the x-axis.

    I hope there is no bug in my math, but looks like I have showed that you
    have to substract the calibration vector first, and then rotate the result

    Doing the math for the 3D case with quaternions is left as an exercise to
    the reader :)
  14. Why can't you just remove the offset as some calibration step? Once you do
    this it shouldn't effec the accelleration at all... after all it is
    independent of position.

    Basically you have two coordinate systems. Think of two axes, one for the
    sensor and one for the vessel. They should be fixed.

    So any change in position or acceleration of one will have the same effect
    on the other.

    Therefor you only need to rotate one to the other. Assuming the axis is
    orthogonal then there shouldn't be any problem as long as you get your
    rotations right.

    Basically rotate y axis to y, z to z, then x to x, or vice versa but don't
    mix x to y and so forth.

    Look up on the web for 3D rotating and probably euler angles, etc...
  15. jdhar

    jdhar Guest

    Frank, firstly, thank you so much for the assistance. I appreciate
    being able to think this through :)
    What I was thinking is this... I take my readings, (X1, Y1), which are
    uncorrected and are rotated by a certain angle. Can't I just multiply
    it by the 2-D rotation matrix to get new values? IE:

    [X2, Y2] = [cos -sin ; sin cos][X1 Y1] (where the sin/cos angles are
    the rotation angle)

    I tried this out in Matlab, and it seems to work. It looks almost
    similar to your equations, it's just you subtract the calibration
    components (c_x and c_y). Is just multiplying it by the rotation
    matrix incorrect?? The rotation matrix is in essence defined by the
    calibration since I need to figure out the angle from the X and Y

    ....or they might both be equal to eachother :)
  16. jdhar

    jdhar Guest

    What method do you recommend... this is the tricky part in effect.
    It's not as simple as reading the (X,Y) values at steady-state, and
    then subtracting them to obtain a zero-offset calibrated value. I
    still have to deal with the fact that the sensor is rotated, and a
    motion in one direction will affect the other (due to rotation).
    I personally don't think this would work.. again, think about it this
    way... lets say the sensor is mountd perfectly. Then a movemente in
    direction X will yield a non-zero X reading (call it X1), and Y will
    yield zero. However, if the sensor is rotated even the slightest
    amount, a movement in THAT SAME X-direction will now yield non-zero X
    AND Y (call them X2 and Y2). Now I need some way to transform (X2,Y2)
    to match (X1,Y1). The X2 component needs the Y2 component to determine
    the proper translation to X1... so I can't just "rotate y axis to y
    and x to x"... unless I am misunderstanding you. In short, I need to
    treat the pair as a vector, and not individual axes.

    Moreover, this isn't something I can calibrate it; it has to be
    applied to each sample that I read.
  17. You must calibrate it out in some way. You must somehow measure the axis
    then use that.

    You don't realize that rotating the axis will fix it up properly.

    Take 2D for example.

    The transformation equations are

    r = x*cos(t) - y*sin(t)
    s = x*sin(t) + y*cos(t)

    suppose they are depenent on time(t is angle of rotation between axis)


    r' = x'*cos(t) - y'*sin(t)
    s' = x'*sin(t) + y'*cos(t)

    r'' = x''*cos(t) - y''*sin(t)
    s'' = x''*sin(t) + y''*cos(t)

    So your derivatives transform exactly the same way.

    e.g., normally in vector notation it is

    Y = R*X
    Y' = R*X'
    Y'' = R*X''

    This means that if you have the inverse matrix R, call it S


    S*Y = X
    S*Y' = X'
    S*Y'' = X''

    e.g., you can "unrotate" to get back the original system.

    It works and I think your making it more complicated than it is.

    The only real issue is that in 3D it's a bit harder since you have 3 angles
    of rotation that you have to deal with.

    In fact, in 3D graphics they almost always use a 4D rotation matrix because
    it's much easier to do. The problem is that to get an arbitrary rotation in
    3D you have to rotate 3 orthogonal directions. This causes problems because
    the order maters. (R = A*B*C != B*C*A)

    Another option is quaternions which also handle the rotations in a
    relatively simple way.

    BUT!!! You have to somehow figure out how "off it is.

    This shouldn't be too hard though. Measure the vehicle's position when it is
    in the perfered axis along one axis only!! (that is important)

    To get one of the angles: (example in 2D)

    1. Measure the acceleration along the x axis of the vessel. You will get an
    r and s value for the acceleration of the accelerometers.

    2. Use the equations given above to solve for the angle

    r'' = x''*cos(t) - y''*sin(t)
    s'' = x''*sin(t) + y''*cos(t)

    y'' = 0 since we only moved the vessel in the x direction.


    r'' = x''*cos(t)
    s'' = x''*sin(t)


    tan(t) = s''/r''

    So you have the angle t when then allows you to "undo" the rotation by the
    accelerometer.(just rotate the opposite way)

    Its very simple to do for 2D because there is only one angle of rotation. In
    3D there are 3 so you have to solve a system of linear equations. It's no
    big deal though but just make sure that the get the order of rotations

    (normally one rotates about different axis. Y = A*B*C*X. So X = c*b*a*Y.)

    Unless I'm totally misunderstanding your problem. Simple question: Suppose
    you could orient your accelerometer perfectly and in any way you want, could
    you then eliminate the problem?
  18. jdhar

    jdhar Guest

    Unless I'm totally misunderstanding your problem.  Simple question: Suppose
    I need to read your post 10 times before I comment on it... but I'll
    answer this quickly. If I could orient the accelerometer such that it
    is perfectly flat (ie: perpendicular to gravity), meaning X and Y read
    0 and Z reads 1 at steady-state... AND... if I could orient it such
    that movement of the vessel in a perfectly straight line only results
    in an acceleration on the X-axis, then yes, the problem that I am
    describing would not be there.

    I actually thought of another issue that I don't think I can solve
    easily. I don't know if there is a way I can figure out the YAW angle.
    IE: If the sensor is perfectly flat such that X=Y=0 and Z=1, the
    sensor can still be rotated around the Z-axis (YAW) and there would be
    no way of me knowing, correct? In that case, I wouldn't know the angle
    to de-rotate the readings by....

    So all of this discussion would not apply to a Yaw offset I think....
  19. Frank Buss

    Frank Buss Guest

    No, I don't think this works. Your readings are the sum of the acceleration
    in one direction and the earth gravitation, which gives a vector, which is
    not in the direction of the accleration. But when subtracting the earth
    gravitation, you can rotate it. If you rotate it before, I think you'll get
    the wrong result.

    As Ken wrote: A good idea would be to write a simulation program. You could
    try it in Second Life, which has already a physical engine and a simple
    scripting language, or you could use PyOpenGL or similiar systems for
    prototyping. I don't like Python, but you can try a Google search with your
    favorite language, in combination with OpenGL, and chances are good that
    you'll get a result, e.g. for JavaScript.
  20. Frank Buss

    Frank Buss Guest

    The sensor needs not to be mounted perfectly flat. You can't detect
    rotating about the z-axis, regardless of the orientation of the sensor.
    This is the reason why I'm currently evaluating this sensor, in addition
    with a 3-axis accelerometer:

    This is much cheaper than currently available 3-axis gyros and has the
    additional advantage to give absolute orientation measurements (if the
    earth magnetic field can be measured and is not distorted too much by
    external magnets) and you can move it as slowly as you want (some gyros
    have lower limits on how slow you can rotate it for good detection).
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