rts_smooth.m

用EKF/UKF的Matlab仿真程序包

%RTS_SMOOTH  Rauch-Tung-Striebel smoother
%
% Syntax:
%   [M,P,S] = RTS_SMOOTH(M,P,A,Q)
%
% In:
%   M - NxK matrix of K mean estimates from Kalman filter
%   P - NxNxK matrix of K state covariances from Kalman Filter
%   A - NxN state transition matrix or NxNxK matrix of K state
%       transition matrices for each step.
%   Q - NxN process noise covariance matrix or NxNxK matrix
%       of K state process noise covariance matrices for each step.
%
% Out:
%   M - Smoothed state mean sequence
%   P - Smoothed state covariance sequence
%   D - Smoother gain sequence
%   
% Description:
%   Rauch-Tung-Striebel smoother algorithm. Calculate "smoothed"
%   sequence from given Kalman filter output sequence
%   by conditioning all steps to all measurements.
%
% Example:
%   m = m0;
%   P = P0;
%   MM = zeros(size(m,1),size(Y,2));
%   PP = zeros(size(m,1),size(m,1),size(Y,2));
%   for k=1:size(Y,2)
%     [m,P] = kf_predict(m,P,A,Q);
%     [m,P] = kf_update(m,P,Y(:,k),H,R);
%     MM(:,k) = m;
%     PP(:,:,k) = P;
%   end
%   [SM,SP] = rts_smooth(MM,PP,A,Q);
%
% See also:
%   KF_PREDICT, KF_UPDATE

% Copyright (C) 2003-2006 Simo S鋜kk