Kalman filter design for impedance measurement data
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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. Lets assume that I have nominal values for model parameters:
Re = 917.5;
Ri = 629.0;
Cm = 3.42e-9;
while model is described with
Z = Re*(1+1i*w*Ri*Cm)./(1+1i*w*(Re+Ri)*Cm);
w = 2*pi*f;
f = linspace(10e3, 100e3, 100);
Then I would like to add some noise:
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.
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