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%/upf_demos/bshfun.m function [y] = bshfun(x,u,t); % PURPOSE : Measurement model function. % INPUTS : - x: The evaluation point in the domain. % OUTPUTS : - y: The value of the function at x.

%/upf_demos/hfun.m function [y] = hfun(x); % PURPOSE : Measurement model function. % INPUTS : - x: The evaluation point in the domain. % OUTPUTS : - y: The value of the function at x. % AUTHORS

function uo=units2tex(ui) % Function substitutes TeX-style units for input units that imply exponents or % greek letters (for axis annotation of plots) % e.g. kg/m3 ==> kg/m^3 % % Written by E. R., M

function S = dosim(T, cda, cdm, cm, sr_scale, sq_scale, stq_C, stq_F, stq_S) % % Run sim of level sensors % % Input: % T: truth struct with fields... % L: actual levels struct w/ fields % L.C (c

function q = useralg_pre(X) % This is a sparseness measurement algorithm defined by the user. % X: Observations % q: result

function f_calmenu (plotstr) %F_CALMENU: Set up caliper menu item % % Usage: f_calmenu (plotstr) % % Inputs: % plotstr = callback string to regenerate plot hm_2 = uimenu

function S = dosim(T, cda, cdm, cm, sr_scale, sq_scale, stq_C, stq_F, stq_S) % % Run sim of level sensors % % Input: % T: truth struct with fields... % L: actual levels struct w/ fields % L.C (c

function S = dosim(T, cda, cdm, cm, sr_scale, sq_scale, stq_C, stq_F, stq_S) % % Run sim of level sensors % % Input: % T: truth struct with fields... % L: actual levels struct w/ fields % L.C (c

% qrupa.m % Scope: This MATLAB macro implements the updating algorithm [1] for Q-R % factorization of the modified measurement matrix when a new %

%EKF_UPDATE2 2nd order Extended Kalman Filter update step % % Syntax: % [M,P,K,MU,S,LH] = EKF_UPDATE2(M,P,Y,H,H_xx,R,[h,V,param]) % % In: % M - Nx1 mean state estimate after prediction step %