calman filter in matlab

main.m
% Define the state transition matrix A
A = [1 1; 0 1];

% Define the measurement matrix H
H = [1 0];

% Define the process noise covariance Q
Q = [1e-5 0; 0 1e-6];

% Define the measurement noise covariance R
R = 0.01;

% Define the initial state estimate x
x = [0; 0];

% Define the initial state covariance P
P = [1 0; 0 1];

% Generate some example data to be filtered
data = randn(100,1);

% Preallocate arrays to store results
filteredStates = zeros(2,100);
filteredCovariances = zeros(2,2,100);

% Kalman filter loop
for i = 1:100
    % Predict step
    x = A*x;
    P = A*P*A' + Q;
    
    % Update step
    K = P*H'/(H*P*H' + R);
    x = x + K*(data(i) - H*x);
    P = (eye(2) - K*H)*P;
    
    % Store results
    filteredStates(:,i) = x;
    filteredCovariances(:,:,i) = P;
end
790 chars
41 lines