代码搜索结果

function [x,P] = k_row(x,P,H,b,var) %K_ROW Kalman update, one measurement per call % Observation variance: var %Kai Borre and C.C. Goad 11-24-96 %Copyright (c) by Kai Borre %$Revision: 1

function [x,P,K,innovation_variance] = k_updatx(x,P,A,b,R,Q); % K_UPDATX Kalman update, one measurement per call % Allows for system covariance Q % Allows for observation cova

function [x,P] = b_row(x,P,A,b,R) %B_ROW Bayes update, one measurement per call % Observation covariance R %Kai Borre 3-28-97 %Copyright (c) 1997 by Kai Borre %$Revision: 1.1 $ $Date: 19

function [x,P] = k_ud(x,P,H,b,var) %K_UD Kalman update, one measurement per call % Observation variance: var %Kai Borre and C.C. Goad 11-24-96 %Copyright (c) by Kai Borre %$Revision: 1.0

function [x,P] = kud(x,P,H,b,var) %KUD Kalman update, one measurement per call % Observation variance: var %Kai Borre and C.C. Goad 11-24-96 %Copyright (c) by Kai Borre %$Revision: 1.0 $

function [x,P] = k_update(x,P,A,b,R) % K_UPDATE Kalman update, one measurement per call % Observation covariance R %Kai Borre 11-24-96 %Copyright (c) 1997 by Kai Borre %$Revision: 1.0

function [x,P] = k_update(x,P,A,b,R) % K_UPDATE Kalman update, one measurement per call % Observation covariance R %Kai Borre 11-24-96 %Copyright (c) 1997 by Kai Borre %$Revision: 1.0

// -*- c++ -*- // Copyright 2008 Isis Innovation Limited // // This header declares the data structures to do with keyframes: // structs KeyFrame, Level, Measurement, Candidate. // // A KeyFrame con

% mreast.m % Scope: This MATLAB macro executes measurement reasonableness test for a % given scalar measurement. % Usage: alpha = mreast(n,ud,h,r,dz,tes

% mudm.m % Scope: This MATLAB macro implements the discrete Kalman filter measurement % updating using Bierman's U-D measurement update algorithm. Onl