Noise modeling with Markov modeling

AI Thread Summary
The discussion focuses on using accelerometer and gyroscope data to model noise with a first-order Markov process for a Kalman filter application. The user has recorded measurements and computed auto-correlation but is uncertain about determining the correlation value "P." It is noted that noise is typically modeled as a stationary process rather than a Markov process, with the Gauss-Markov process being suggested as a viable alternative. There is confusion regarding the necessity of using a Kalman filter to estimate position error instead of directly integrating the Gauss-Markov sequence. Overall, the conversation highlights the complexities of noise modeling and the application of Kalman filters in this context.
ramesses
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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

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
 
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Noise is usually modeled as a stationary process, not a Markov process.
 
Gauss-Markov process ?
 
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.
 
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
 
Sorry - Ican't answer your specific questions. I have not worked with the specific process or Kalman filters.
 
So I know that electrons are fundamental, there's no 'material' that makes them up, it's like talking about a colour itself rather than a car or a flower. Now protons and neutrons and quarks and whatever other stuff is there fundamentally, I want someone to kind of teach me these, I have a lot of questions that books might not give the answer in the way I understand. Thanks

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