[Bayes++] Bayes++ EKF Example Request

[Nithya N. V. <nvi...@cs...>]

Hi,

I am working on a prediction system implemented using Extended Kalman 
filters. Ideally, my system would take a set of time series data points 
and fill in any missing values. I have installed Bayes++ and tried out the 
examples. I am looking for more examples on extended kalman filters 
implemented using Bayes++. As a novice to Kalman filters, I greatly 
appreciate any help.

To begin with, I am working on extending the position velocity example to 
take in a set of observations made at 10 time points, update the kalman 
filter and then predict the observations for the 11th through 15th time 
points. I would like to use EKF. I wrote a simple example using the kalman 
filter toolbox in matlab. I appreciate any help in coding this up in 
Bayes++. The partial code in matlab is as follows.

------position_velocity.m----------

%Take as observation vector and velocity vector values

%set F, H, Q, R values
ss = 2; % state size
os = 1; % observation size
F = [1 dt; ...
         0 1];
H = [1 0];
Q = 0.1*eye(ss);
R = 1*eye(os);

initx = [obsVec(1); velVec(1)]
initV = 10*eye(ss)

%first 10 observations. perform kalman update
T = 10;
xfilt(:,1) = initx;
Vfilt(:,:,1) = initV;
for i = 2:T
     [xfilt(:,i), Vfilt(:,:,i)] = kalman_update(F, H, Q, R, obsVec(i), ...
     xfilt(:,i-1), Vfilt(:,:,i-1), 'initial', 0);
end

%predict next 5 values
x = [obsVec; velVec];
temp = zeros(2,2);
for i=T:T+5
     %calculate next position
     temp = F*xfilt(:,i-1);
     %update filter
     [xfilt(:,i), Vfilt(:,:,i)] = kalman_update(F, H, Q, R, temp(1), ...
     xfilt(:,i-1),Vfilt(:,:,i-1), 'initial', 0);
end


thanks,
Nithya