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Measurement 的代码
kf_update.m
%KF_UPDATE Kalman Filter update step
%
% Syntax:
% [X,P,K,IM,IS,LH] = KF_UPDATE(X,P,Y,H,R)
%
% In:
% X - Nx1 mean state estimate after prediction step
% P - NxN state covariance after predictio
bot_d2h_dx2.m
% Hessian of the measurement function in BOT-demo.
% Copyright (C) 2007 Jouni Hartikainen
%
% This software is distributed under the GNU General Public
% Licence (version 2 or later); please refer t
kf_update.m
%KF_UPDATE Kalman Filter update step
%
% Syntax:
% [X,P,K,IM,IS,LH] = KF_UPDATE(X,P,Y,H,R)
%
% In:
% X - Nx1 mean state estimate after prediction step
% P - NxN state covariance after predictio
kf_update.m.bak
%KF_UPDATE Kalman Filter update step
%
% Syntax:
% [X,P,K,IM,IS,LH] = KF_UPDATE(X,P,Y,H,R)
%
% In:
% X - Nx1 mean state estimate after prediction step
% P - NxN state covariance after predictio
fl45.sub
FPAttributeValueFile
n SubType="IVI"
n SubVersion="1"
v Current_Med_Fast_RangeTable DataType="d"
FL45_VAL_AUTO_RANGE_ON (-1.00000000000000E+0)
"Configures the DMM to calculate the r
stdkalman.m
% STDKALMAN.M standard discrete-time Kalman filter for the following system:
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% plant equation: x(k)
pdakalman.m
% PDAKALMAN.M discrete-time Kalman filter with probabilistic data association
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% plant equation: x(k
xmudm.m
% xmudm.m
% Scope: This MATLAB program tests the macros: mudm, mudm1 and mreast .
% Implementation of the discrete Kalman filter measurement updating
%
xqrupa.m
% xqrupa.m
% Scope: This MATLAB program tests the updating algorithm [1] for Q-R
% factorization of the modified measurement matrix when a new
%
kf_update.m
%KF_UPDATE Kalman Filter update step
%
% Syntax:
% [X,P,K,IM,IS,LH] = KF_UPDATE(X,P,Y,H,R)
%
% In:
% X - Nx1 mean state estimate after prediction step
% P - NxN state covariance after predictio