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Kalman filtering demo in MATLAB with automatic MATLAB-to-C code generation
by Houman Zarrinkoub
Kalman filtering algorithm to track an object and generating C source code for implementation
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| kalman01(z) %#eml
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% Copyright 2009 - 2010 The MathWorks, Inc.
function y = kalman01(z) %#eml
% Initialize state transition matrix
dt=1;
A=[ 1 0 dt 0 0 0;...
0 1 0 dt 0 0;...
0 0 1 0 dt 0;...
0 0 0 1 0 dt;...
0 0 0 0 1 0 ;...
0 0 0 0 0 1 ];
% Measurement matrix
H = [ 1 0 0 0 0 0; 0 1 0 0 0 0 ];
Q = eye(6);
R = 1000 * eye(2);
% Initial conditions
persistent x_est p_est
if isempty(x_est)
x_est = zeros(6, 1);
p_est = zeros(6, 6);
end
% Predicted state and covariance
x_prd = A * x_est;
p_prd = A * p_est * A' + Q;
% Estimation
S = H * p_prd' * H' + R;
B = H * p_prd';
klm_gain = (S \ B)';
% Estimated state and covariance
x_est = x_prd + klm_gain * (z - H * x_prd);
p_est = p_prd - klm_gain * H * p_prd;
% Compute the estimated measurements
y = H * x_est;
end
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