Kalman filter design for impedance measurement data

north2012 · May 21, 2016

Hello,

I am trying to implement Kalman fiter to remove some Gaussian white noise. I have succesfully implemented moving average filter but I would like to compare them in Matlab.

Lets assume that I have nominal values for model parameters:

Code:

Re = 917.5;
Ri = 629.0;
Cm = 3.42e-9;

while model is described with

Code:

Z = Re*(1+1i*w*Ri*Cm)./(1+1i*w*(Re+Ri)*Cm);

where

Code:

w = 2*pi*f;

and

Code:

f = linspace(10e3, 100e3, 100);

Then I would like to add some noise:

Code:

rng(0,'twister');
a = -1;
b = 1;
r = (b-a).*rand(100,1) + a;

Can anyone help me with Kalman filter code for white noise cancellation?

Thanks in advance.

KlausST · May 21, 2016

Hi,

I can't help you with kalman filter.

I'd use a single frequency DFT.

Klaus

ahme0307 · May 21, 2016

Hi,
To Model your model with Kalman filter, You will need state transition matrix and variance of measurement and process noises.
If you are looking only for comparison purpose, Kalman filter is already implemented in matlab package.
Check this link:
https://se.mathworks.com/help/control/examples/kalman-filter-design.html

north2012 · May 21, 2016

Thank you very much, but how to recognize matrices A, B, C and D from my data?

Thanks...

Kalman filter design for impedance measurement data

north2012

Member level 3

KlausST

Advanced Member level 7

ahme0307

Member level 1

north2012

Member level 3

Similar threads

Kalman filter design for impedance measurement data

north2012

Member level 3

KlausST

Advanced Member level 7

ahme0307

Member level 1

north2012

Member level 3

Similar threads

Privacy & Transparency

Privacy & Transparency