Kalman filter design for impedance measurement data

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.