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MOD: matlab file kf_vtl parameter for state number

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miguekf 2022-12-19 18:56:45 +01:00
parent 9b9b195509
commit 33bd8d4937
1 changed files with 19 additions and 9 deletions
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28
src/utils/matlab/vtl/kf_prototype.m
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@ -2,17 +2,27 @@
%%
sat_number=5;
%% ################## Kalman filter initialization ######################################
st_nmbr=8;
% covariances (static)
kf_P_x = eye(8); %TODO: use a real value.
kf_x = zeros(8, 1);
kf_P_x = eye(st_nmbr); %TODO: use a real value.
kf_x = zeros(st_nmbr, 1);
kf_R = zeros(2*sat_number, 2*sat_number);
kf_dt=0.1;
% kf_F = eye(8, 8);
% kf_F = eye(st_nmbr, st_nmbr);
% kf_F(1, 4) = kf_dt;
% kf_F(2, 5) = kf_dt;
% kf_F(3, 6) = kf_dt;
% kf_F(7, 8) = kf_dt;
% kf_F=[ 1 0 0 kf_dt 0 0 0 0 0
% 0 1 0 0 kf_dt 0 0 0 0
% 0 0 1 0 0 kf_dt 0 0 0
% 0 0 0 1 0 0 0 0 0
% 0 0 0 0 1 0 0 0 0
% 0 0 0 0 0 1 0 0 0
% 0 0 0 0 0 0 1 kf_dt kf_dt^2/2
% 0 0 0 0 0 0 0 kf_dt 1];
kf_F=[ 1 0 0 kf_dt 0 0 0 0
0 1 0 0 kf_dt 0 0 0
0 0 1 0 0 kf_dt 0 0
@ -22,7 +32,7 @@ kf_F=[ 1 0 0 kf_dt 0 0 0 0
0 0 0 0 0 0 1 kf_dt
0 0 0 0 0 0 0 1];
kf_H = zeros(2*sat_number,8);
kf_H = zeros(2*sat_number,st_nmbr);
kf_y = zeros(2*sat_number, 1);
kf_yerr = zeros(2*sat_number, 1);
% kf_xerr = zeros(8, 1);
@ -48,7 +58,7 @@ for t=2:length(navSolution.RX_time)
%% State error Covariance Matrix Q (PVT) and R (MEASUREMENTS)
if (t<length(navSolution.RX_time)-point_of_closure)
%% State error Covariance Matrix Q (PVT)
kf_Q = eye(8);%new_data.rx_pvt_var(i); %careful, values for V and T could not be adecuate.
kf_Q = eye(st_nmbr);%new_data.rx_pvt_var(i); %careful, values for V and T could not be adecuate.
%%
% Measurement error Covariance Matrix R assembling
@ -80,7 +90,7 @@ for t=2:length(navSolution.RX_time)
cdeltatDot_u=kf_x(8,t);
% Kalman state prediction (time update)
kf_P_x = eye(8)*100; %TODO: use a real value.
kf_P_x = eye(st_nmbr)*100; %TODO: use a real value.
kf_xpri(:,t) = kf_F * (kf_x(:,t)-kf_x(:,t-1));% state prediction
kf_P_x= kf_F * kf_P_x * kf_F' + kf_Q;% state error covariance prediction
else
@ -116,7 +126,7 @@ for t=2:length(navSolution.RX_time)
end
for chan=1:5 % Measurement matrix H assembling
% It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
% It has st_nmbr columns (st_nmbr states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
kf_H(chan, 1) = a_x(chan,t); kf_H(chan, 2) = a_y(chan,t); kf_H(chan, 3) = a_z(chan,t); kf_H(chan, 7) = 1.0;
kf_H(chan+sat_number, 4) = a_x(chan,t); kf_H(chan+sat_number, 5) = a_y(chan,t); kf_H(chan+sat_number, 6) = a_z(chan,t); kf_H(chan+sat_number, 8) = 1.0;
end
@ -184,10 +194,10 @@ for t=2:length(navSolution.RX_time)
+(sat_velZ(chan,t)-zDot_u)*a_z(chan,t)+cdeltatDot_u_g;
end
kf_H = zeros(2*sat_number,8);
kf_H = zeros(2*sat_number,st_nmbr);
for chan=1:5 % Measurement matrix H assembling
% It has 8 columns (8 states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
% It has st_nmbr columns (st_nmbr states) and 2*NSat rows (NSat psudorange error;NSat pseudo range rate error)
kf_H(chan, 1) = a_x(chan,t); kf_H(chan, 2) = a_y(chan,t); kf_H(chan, 3) = a_z(chan,t); kf_H(chan, 7) = 1.0;
kf_H(chan+sat_number, 4) = a_x(chan,t); kf_H(chan+sat_number, 5) = a_y(chan,t); kf_H(chan+sat_number, 6) = a_z(chan,t); kf_H(chan+sat_number, 8) = 1.0;
end