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ukf_one_dim_v2.m 

% Code to test the Unscented Kalman filter for a linear state-space model.
% Though the UKF block is very powerful in it's ability to track signals
% generated by a nonlinear model, this test is intended to be a sanity
% check.
% 
% Author: Saurabh Prasad
% Last modified: November 2, 2005.
%
% Dependent files - 
%                 |- sigmapt.m - compute sigma points
%                 |- sigmawt.m - compute 'predicted' observation, y from
%                                the sigma point theory.
%                 |- sigmawt_process.m - compute 'predicted' state vectors
%                                from the sigma point theory

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function [mu, sigma] = sigmawt_process(sigma,L)

% Function to use sigma point theory to generate predicted state
% values by a weighted sum of sigma points passed through the process
% model. It produces the mean and covar. matrix of the predicted
% states
% Author - Saurabh Prasad
% Last Modified - November 02, 2005
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function [mu, sigma] = sigmawt(sigma,L)

% Function to use sigma point theory to generate predicted observation
% values by a weighted sum of sigma points passed through the measurement
% model. It produces the mean and covar. matrix of the predicted
% observations.
% Author : Saurabh Prasad
% Last Modified : November 2, 2005
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function [sigma] = sigmapt(x,mu_x,P_x,L)

% Function to generate sigma points about the mean, using the sigma-point
% theory
% Author: Saurabh Prasad
% Last Modified: November 2, 2005
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