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Noise modeling with Markov modeling

  1. Jul 21, 2015 #1
    Hi
    I'm using accelerometer & horizontal gyroscope in order to replace GPS. Now, I'want to model the noise with first order markov process, to use it in kalman filter.
    I recorded measurement on all axes and computed auto-correlation.
    This picture represents auto-correlation on one of axes.
    http://picpaste.com/pics/autocorrelation_x-qjpnbYJk.1437477728.png [Broken]

    Now, I know that the first order markov process takes the following equation :
    w = white noise which has the same variance.
    and P is the correlation

    My problem is how to fix the value of "P" (know as correlation) ?
    thank you
     
    Last edited by a moderator: May 7, 2017
  2. jcsd
  3. Jul 21, 2015 #2

    mathman

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    Noise is usually modeled as a stationary process, not a Markov process.
     
  4. Jul 22, 2015 #3
    Gauss-Markov process ?
     
  5. Jul 22, 2015 #4

    mathman

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    In general, a noise process has a mean of 0. A Markov process has a mean, at a given time, the value at the last known sample.
     
  6. Jul 27, 2015 #5
    The Gauss-Markov process gives a good result as you see in this picture.
    Now, I don't understand why I need to use kalman filter in-order to estimate the position's error ?
    why we don't integrate directly the Gauss-Markov sequence ?
    2A5Bmqzc2uO9.png
     
  7. Jul 27, 2015 #6

    mathman

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    Sorry - Ican't answer your specific questions. I have not worked with the specific process or Kalman filters.
     
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