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ukf_update2.m
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ukf_update2.m
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%UKF_UPDATE2 - Augmented form Unscented Kalman Filter update step
%
% Syntax:
% [M,P,K,MU,IS,LH] = UKF_UPDATE2(M,P,Y,h,R,h_param,alpha,beta,kappa,mat)
%
% In:
% M - Mean state estimate after prediction step
% P - State covariance after prediction step
% Y - Measurement vector.
% h - Measurement model function as a matrix H defining
% linear function h(x) = H*x+r, inline function,
% function handle or name of function in
% form h([x;r],param)
% R - Measurement covariance.
% param - Parameters of h (optional, default empty)
% alpha - Transformation parameter (optional)
% beta - Transformation parameter (optional)
% kappa - Transformation parameter (optional)
% mat - If 1 uses matrix form (optional, default 0)
%
% Out:
% M - Updated state mean
% P - Updated state covariance
% K - Computed Kalman gain
% MU - Predictive mean of Y
% S - Predictive covariance Y
% LH - Predictive probability (likelihood) of measurement.
%
% Description:
% Perform augmented form Discrete Unscented Kalman Filter (UKF)
% measurement update step. Assumes additive measurement
% noise.
%
% Function h should be such that it can be given
% DxN matrix of N sigma Dx1 points and it returns
% the corresponding measurements for each sigma
% point. This function should also make sure that
% the returned sigma points are compatible such that
% there are no 2pi jumps in angles etc.
%
% Example:
% h = inline('atan2(x(2,:)-s(2),x(1,:)-s(1))','x','s');
% [M2,P2] = ukf_update2(M1,P1,Y,h,R,S);
%
% See also:
% UKF_PREDICT1, UKF_UPDATE1, UKF_PREDICT2, UKF_PREDICT3, UKF_UPDATE3
% UT_TRANSFORM, UT_WEIGHTS, UT_MWEIGHTS, UT_SIGMAS
% History:
% 08.02.2008 JH Fixed a typo in the syntax description.
% 04.05.2007 JH Initial version. Modified from ukf_update1.m
% originally created by SS.
%
%
% References:
% [1] Wan, Merwe: The Unscented Kalman Filter
%
% Copyright (C) 2007 Jouni Hartikainen, Simo S�rkk�
%
% $Id$
%
% This software is distributed under the GNU General Public
% Licence (version 2 or later); please refer to the file
% Licence.txt, included with the software, for details.
function [M,P,K,MU,S,LH] = ukf_update2(M,P,Y,h,R,h_param,alpha,beta,kappa,mat)
%
% Check that all arguments are there
%
if nargin < 5
error('Too few arguments');
end
if nargin < 6
h_param = [];
end
if nargin < 7
alpha = [];
end
if nargin < 8
beta = [];
end
if nargin < 9
kappa = [];
end
if nargin < 10
mat = [];
end
%
% Apply defaults
%
if isempty(mat)
mat = 0;
end
%
% Do transform and make the update
%
m = size(M,1);
n = size(R,1);
MA = [M;zeros(size(R,1),1)];
PA = zeros(size(P,1)+size(R,1));
PA(1:size(P,1),1:size(P,1)) = P;
PA(1+size(P,1):end,1+size(P,1):end) = R;
tr_param = {alpha beta kappa mat};
[MU,S,C] = ut_transform(MA,PA,h,h_param,tr_param);
K = C / S;
MA = MA + K * (Y - MU);
PA = PA - K * S * K';
M = MA(1:m,:);
P = PA(1:m,1:m);
if nargout > 5
LH = gauss_pdf(Y,MU,S);
end