removed paper folders

matlab/GPSaidedINS_car.m

@@ -20,7 +20,7 @@
 % out_data.delta_u_h        Estimated IMU biases [accelerometers; gyroscopes]
 % out_data.diag_P           Diagonal elements of the Kalman filter state
 %                           covariance matrix.
-% out_data.energy            overall estimated power consumption
+% out_data.energy           overall estimated power consumption
 % out_data.error            average RMS
 %
 %

matlab/GPSaidedINS_cycling.m

@@ -20,7 +20,7 @@
 % out_data.delta_u_h        Estimated IMU biases [accelerometers; gyroscopes]
 % out_data.diag_P           Diagonal elements of the Kalman filter state
 %                           covariance matrix.
-% out_data.energy            overall estimated power consumption
+% out_data.energy           overall estimated power consumption
 % out_data.error            average RMS
 %
 %

matlab/main_car.m

@@ -4,16 +4,16 @@
 
 
 %% Load data
-disp('Loads data')
+disp('Load data')
 load('car_input_data.mat');
 
 %% Load filter settings
-disp('Loads settings')
+disp('Load settings')
 settings=get_settings_car();
 settings.P_treshold=4.1;
 
 %% Run the GNSS-aided INS
-disp('Runs the GNSS-aided INS')
+disp('Run the GNSS-aided INS')
 out_data=GPSaidedINS_car(in_data,settings);
 
 %% Plot the data 

matlab/main_cycling.m

@@ -4,16 +4,16 @@
 
 
 %% Load data
-disp('Loads data')
+disp('Load data')
 load('cycling_input_data');
 
 %% Load filter settings
-disp('Loads settings')
+disp('Load settings')
 settings=get_settings_cycling();
 settings.P_treshold=2.5;
 
 %% Run the GNSS-aided INS
-disp('Runs the GNSS-aided INS')
+disp('Run the GNSS-aided INS')
 out_data=GPSaidedINS_cycling(in_data,settings);
 
 %% Plot the data 

matlab/plot_single_trace.m

 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 % Script for data plot:
-% plots the trajecotry and the stimation accuracy with the GPS turn on
+% plots the trajecotry and the estimation accuracy with the GPS turn on
 % signal
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 % display the overall error (root mean square)
-out_data.error    
+disp(['Root mean square error:',num2str(out_data.error)])
 
 % Display trajectory estimated with sensor fusion against trajectory for the
 % GPS alone always on

original_submission/Makefile

-all:
-	xelatex main.tex
-	bibtex main
-	xelatex main.tex
-	xelatex main.tex
-	rm -f main.aux main.bbl main.blg main.log	main.out

original_submission/data/exp_biketrace.csv

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original_submission/data/exp_cartrace.csv

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-0.39823,-0.1114
-0.39823,2.0955e-08
-0.28445,0.1114
-2.3283e-10,4.6566e-10
--0.22756,0.2228
--1.5929,1.671
--4.2099,3.8991
--7.8509,7.3526
--11.833,12.031
--15.474,17.602
--19.684,24.063
--24.747,31.638
--30.266,39.659
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--1.9912,-25.065
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--26.398,-98.368
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--26.057,-97.923

original_submission/data/exp_sb1.csv

-14928,55.93
-14624,52.981
-14584,63.653
-14472,61.59
-14772,173.21
-14268,56.248
-15360,63.679
-14516,59.844
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-15236,64.541
-14916,63.82
-14336,54.763
-14476,61.361
-14344,57.605
-14728,60.507
-14836,55.08
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-13936,53.726
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-14136,56.288
-15236,64.541
-15284,57.775
-14568,59.359
-14372,104.04
-15256,56.337
-15064,59.353
-15260,58.433
-15236,56.677

original_submission/data/exp_sb2.csv

-11572,64.093
-11380,78.234