[Sample B: Approval/Signature Sheet] - George Mason University

data = results.error(b+1,:)
stars = [nstars_1 nstars_2]
fprintf(savefile, '%12.6e\t', data);
fprintf(savefile, '\r Number of stars: Sensor 1: %6.0f\t, Sensor 2: %6.0f\n', stars);
fprintf(savefile, 'MSE: \t');
fprintf(savefile, '%12.6e\t', MSE(kk,:));
fprintf(savefile, 'RMS: \t');
fprintf(savefile, '%12.6e\t', RMS(kk,:));
fprintf(savefile, 'Mean Error: \t');
fprintf(savefile, '%12.6e\t', Mean_error(kk,:));
if b == 3
figure(6);
hold on;
p64 = plot(kstart:10:kend, error(kk, b).state_est_timeave(1:10:kend-kstart+1), lk);
title('Mean Error of target with EKF bias correction');
xlabel('Time (seconds)');
ylabel('Mean Error Km');
axis([0 1800 0 1]);
end
end
end
% end bias
% end kk
% ------------------------------ Calculate and plot PCRLB -----------------------
tcrb = 600;
Qn = [1/3 1/2 0 0 0 0;
1/2 1 0 0 0 0;
0 0 1/3 1/2 0 0;
0 0 1/2 1 0 0;
0 0 0 0 1/3 1/2;
0 0 0 0 1/2 1];
Qcrb = process_error*Qn/1000;
for t = 1:tcrb
Jz_1 = PCRLB(target.posit(:,t), Sat(1).posit(:,t), oNoise);
Jz_2 = PCRLB(target.posit(:,t), Sat(2).posit(:,t), oNoise);
if t == 1
J(:,:,t) = eye(6);
else
J(:,:,t) = inv(Qcrb+ A*inv(J(:,:,t-1))*A') + .5*Jz_1 + .5*Jz_2;
end % if t==0
CRLB(:,:,t) = inv(J(:,:,t));
CRLBave(t) = CRLB(1,1,t)^2 + CRLB(3,3,t)^2 + CRLB(5,5,t)^2;
end % end t 1-50
figure(8)
170