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Add reproducibility files for IEEE Access publication

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Carles Fernandez 2018-02-28 13:15:46 +01:00
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src/utils/reproducibility/ieee-access/L2-access18.conf Normal file
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[GNSS-SDR]
;######### GLOBAL OPTIONS ##################
;internal_fs_sps: Internal signal sampling frequency after the signal conditioning stage [samples per second].
GNSS-SDR.internal_fs_sps=3000000
;######### SIGNAL_SOURCE CONFIG ############
;#implementation: Use [File_Signal_Source] or [UHD_Signal_Source] or [GN3S_Signal_Source] (experimental)
SignalSource.implementation=File_Signal_Source
;#filename: path to file with the captured GNSS signal samples to be processed
SignalSource.filename=./data/L125_III1b_210s_L2_3Msps.bin ; <- Available at https://zenodo.org/record/1184601
;#item_type: Type and resolution for each of the signal samples. Use only gr_complex in this version.
SignalSource.item_type=ibyte
;#sampling_frequency: Original Signal sampling frequency in [Hz]
SignalSource.sampling_frequency=3000000
;#samples: Number of samples to be processed. Notice that 0 indicates the entire file.
SignalSource.samples=0
;#repeat: Repeat the processing file. Disable this option in this version
SignalSource.repeat=false
;#dump: Dump the Signal source data to a file. Disable this option in this version
SignalSource.dump=false
;#enable_throttle_control: Enabling this option tells the signal source to keep the delay between samples in post processing.
; it helps to not overload the CPU, but the processing time will be longer.
SignalSource.enable_throttle_control=false
;######### SIGNAL_CONDITIONER CONFIG ############
SignalConditioner.implementation=Signal_Conditioner
;######### DATA_TYPE_ADAPTER CONFIG ############
DataTypeAdapter.implementation=Ibyte_To_Complex
;######### INPUT_FILTER CONFIG ############
InputFilter.implementation=Pass_Through
;######### RESAMPLER CONFIG ############
Resampler.implementation=Pass_Through
Resampler.item_type=gr_complex
;######### CHANNELS GLOBAL CONFIG ############
Channels_2S.count=10
Channels.in_acquisition=1
Channel0.signal=2S
Channel1.signal=2S
Channel2.signal=2S
Channel3.signal=2S
Channel4.signal=2S
Channel5.signal=2S
Channel6.signal=2S
Channel7.signal=2S
Channel8.signal=2S
Channel9.signal=2S
;######### ACQUISITION GLOBAL CONFIG ############
Acquisition_2S.implementation=GPS_L2_M_PCPS_Acquisition
Acquisition_2S.item_type=gr_complex
Acquisition_2S.doppler_max=4500
Acquisition_2S.doppler_step=125
Acquisition_2S.use_CFAR_algorithm=false
Acquisition_2S.threshold=19.5
Acquisition_2S.blocking=true
;######### TRACKING GLOBAL CONFIG ############
Tracking_2S.implementation=GPS_L2_M_DLL_PLL_Tracking
Tracking_2S.item_type=gr_complex
Tracking_2S.pll_bw_hz=4.0;
Tracking_2S.dll_bw_hz=0.75;
Tracking_2S.early_late_space_chips=0.5;
Tracking_2S.dump=true
Tracking_2S.dump_filename=./data/track_ch_
;######### TELEMETRY DECODER CONFIG ############
TelemetryDecoder_2S.implementation=GPS_L2C_Telemetry_Decoder
;######### OBSERVABLES CONFIG ############
Observables.implementation=Hybrid_Observables
;######### PVT CONFIG ############
PVT.implementation=RTKLIB_PVT
PVT.positioning_mode=Single; options: Single, Static, Kinematic, PPP_Static, PPP_Kinematic
PVT.iono_model=OFF; options: OFF, Broadcast, SBAS, Iono-Free-LC, Estimate_STEC, IONEX
PVT.trop_model=OFF; options: OFF, Saastamoinen, SBAS, Estimate_ZTD, Estimate_ZTD_Grad
;#output_rate_ms: Period between two PVT outputs. Notice that the minimum period is equal to the tracking integration time [ms]
PVT.output_rate_ms=100
;#display_rate_ms: Position console print (std::out) interval [ms]. Notice that output_rate_ms<=display_rate_ms.
PVT.display_rate_ms=500
;# KML, GeoJSON, NMEA and RTCM output configuration
;#dump_filename: Log path and filename without extension. Notice that PVT will add ".dat" to the binary dump and ".kml" to GoogleEarth dump.
PVT.dump_filename=./data/PVT
;#nmea_dump_filename: NMEA log path and filename
PVT.nmea_dump_filename=./gnss_sdr_pvt.nmea
;#flag_nmea_tty_port: Enable or disable the NMEA log to a serial TTY port (Can be used with real hardware or virtual one)
PVT.flag_nmea_tty_port=false
;#nmea_dump_devname: serial device descriptor for NMEA logging
PVT.nmea_dump_devname=/dev/pts/4
PVT.flag_rtcm_server=false
PVT.rtcm_tcp_port=2101
PVT.rtcm_station_id=1234
PVT.flag_rtcm_tty_port=false
PVT.rtcm_dump_devname=/dev/pts/1
PVT.dump=true
PVT.elevation_mask=5

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src/utils/reproducibility/ieee-access/README.md Normal file
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Continuous Reproducibility in GNSS Signal Processing
----------------------------------------------------
This folder contains files required for the reproduction of the experiment proposed in:
C. Fern&aacute;ndez-Prades, J. Vil&agrave;-Valls, J. Arribas and A. Ramos, *Continuous Reproducibility in GNSS Signal Processing*, submitted to IEEE Access, Feb. 2018.
The dataset used in this paper is available at
The sample format is `ibyte`: Interleaved (I&Q) stream of samples of type signed integer, 8-bit two’s complement number ranging from -128 to 127. 
The figure appearing in that paper can be automatically generated with the pipeline available at https://gitlab.com/gnss-sdr/gnss-sdr/pipelines
After the **Build** stage, which compiles the source code in several versions of the most popular GNU/Linux distributions, and the **Test** stage, which executes GNSS-SDR’s QA code, the **Deploy** stage creates and publishes an image of a software container ready to execute the experiment. This container is available by doing:
```
$ docker pull carlesfernandez/docker-gnsssdr:access18
```
Then, in the **Experiment** stage, a job installs the image created in the previous step, grabs the data file, executes the experiment and produces a figure with the obtained results.
The steps to reproduce the experiment in your own machine (with [Docker](https://www.docker.com) already installed and running) are:
```
$ docker pull carlesfernandez/docker-gnsssdr:access18
$ git clone https://github.com/gnss-sdr/gnss-sdr
$ cd gnss-sdr
$ git checkout next
$ mkdir -p exp-access18/data
$ cd ex-access18/data
$ curl https://zenodo.org/record/1184601/files/L2_signal_samples.tar.xz --output L2_signal_samples.tar.xz
$ tar xvfJ L2_signal_samples.tar.xz
$ echo "3a04c1eeb970776bb77f5e3b7eaff2df L2_signal_samples.tar.xz" > data.md5
$ md5sum -c data.md5
$ cd ..
$ cp ../src/utils/reproducibility/ieee-access18/L2-access18.conf .
$ cp ../src/utils/reproducibility/ieee-access18/plot_dump.m .
$ cp -r ../src/utils/matlab/libs/geoFunctions .
$ octave --no-gui plot_dump.m
$ epspdf Figure2.eps Figure2.pdf
```

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src/utils/reproducibility/ieee-access/plot_dump.m Normal file
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% /*!
% * \file plot_dump.m
% * \brief Read GNSS-SDR Tracking dump binary file and plot some internal
% variables
% * \author Antonio Ramos, 2018. antonio.ramos(at)cttc.es
% * -------------------------------------------------------------------------
% *
% * Copyright (C) 2010-2018 (see AUTHORS file for a list of contributors)
% *
% * GNSS-SDR is a software defined Global Navigation
% * Satellite Systems receiver
% *
% * This file is part of GNSS-SDR.
% *
% * GNSS-SDR is free software: you can redistribute it and/or modify
% * it under the terms of the GNU General Public License as published by
% * the Free Software Foundation, either version 3 of the License, or
% * at your option) any later version.
% *
% * GNSS-SDR is distributed in the hope that it will be useful,
% * but WITHOUT ANY WARRANTY; without even the implied warranty of
% * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% * GNU General Public License for more details.
% *
% * You should have received a copy of the GNU General Public License
% * along with GNSS-SDR. If not, see <http://www.gnu.org/licenses/>.
% *
% * -------------------------------------------------------------------------
% */
clear all;
clc;
n_channel = 0;
symbol_period = 20e-3;
filename = 'track_ch_';
fontsize = 12;
addpath('./data') % Path to gnss-sdr dump files (Tracking and PVT)
addpath('./geoFunctions')
load([filename int2str(n_channel) '.mat']);
t = (0 : length(abs_P) - 1) * symbol_period;
hf = figure('visible', 'off');
set(hf, 'paperorientation', 'landscape');
subplot(3, 3, [1,3])
plot(t, abs_E, t, abs_P, t, abs_L)
xlabel('Time [s]','fontname','Times','fontsize', fontsize)
ylabel('Correlation result','fontname','Times','fontsize', fontsize)
legend('Early', 'Prompt', 'Late')
grid on
subplot(3, 3, 7)
plot(Prompt_I./1000, Prompt_Q./1000, 'linestyle', 'none', 'marker', '.')
xlabel('I','fontname','Times','fontsize', fontsize)
ylabel('Q','fontname','Times','fontsize', fontsize)
axis equal
grid on
subplot(3, 3, [4,6])
plot(t, Prompt_I)
xlabel('Time [s]','fontname','Times','fontsize', fontsize)
ylabel('Navigation data bits','fontname','Times','fontsize', fontsize)
grid on
fileID = fopen('data/PVT_ls_pvt.dat', 'r');
dinfo = dir('data/PVT_ls_pvt.dat');
filesize = dinfo.bytes;
aux = 1;
while ne(ftell(fileID), filesize)
navsol.RX_time(aux) = fread(fileID, 1, 'double');
navsol.X(aux) = fread(fileID, 1, 'double');
navsol.Y(aux) = fread(fileID, 1, 'double');
navsol.Z(aux) = fread(fileID, 1, 'double');
navsol.user_clock(aux) = fread(fileID, 1, 'double');
navsol.lat(aux) = fread(fileID, 1, 'double');
navsol.long(aux) = fread(fileID, 1, 'double');
navsol.height(aux) = fread(fileID, 1, 'double');
aux = aux + 1;
end
fclose(fileID);
mean_Latitude=mean(navsol.lat);
mean_Longitude=mean(navsol.long);
mean_h=mean(navsol.height);
utmZone = findUtmZone(mean_Latitude,mean_Longitude);
[ref_X_cart,ref_Y_cart,ref_Z_cart]=geo2cart(dms2mat(deg2dms(mean_Latitude)), dms2mat(deg2dms(mean_Longitude)), mean_h, 5);
[mean_utm_X,mean_utm_Y,mean_utm_Z]=cart2utm(ref_X_cart,ref_Y_cart,ref_Z_cart,utmZone);
numPoints=length(navsol.X);
aux=0;
for n=1:numPoints
aux=aux+1;
[E(aux),N(aux),U(aux)]=cart2utm(navsol.X(n), navsol.Y(n), navsol.Z(n), utmZone);
end
v_2d=[E;N].'; %2D East Nort position vectors
v_3d=[E;N;U].'; %2D East Nort position vectors
%% ACCURACY
% 2D -------------------
sigma_E_accuracy=sqrt((1/(numPoints-1))*sum((v_2d(:,1)-mean_utm_X).^2));
sigma_N_accuracy=sqrt((1/(numPoints-1))*sum((v_2d(:,2)-mean_utm_Y).^2));
sigma_ratio_2d_accuracy=sigma_N_accuracy/sigma_E_accuracy
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 65%
DRMS_accuracy=sqrt(sigma_E_accuracy^2+sigma_N_accuracy^2)
% if sigma_ratio=1 -> Prob in circle with r=2DRMS -> 95%
TWO_DRMS_accuracy=2*DRMS_accuracy
% if sigma_ratio>0.3 -> Prob in circle with r=CEP -> 50%
CEP_accuracy=0.62*sigma_E_accuracy+0.56*sigma_N_accuracy
% 3D -------------------
sigma_U_accuracy=sqrt((1/(numPoints-1))*sum((v_3d(:,3)-mean_utm_Z).^2));
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 50%
SEP_accuracy=0.51*sqrt(sigma_E_accuracy^2+sigma_N_accuracy^2+sigma_U_accuracy^2)
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 61%
MRSE_accuracy=sqrt(sigma_E_accuracy^2+sigma_N_accuracy^2+sigma_U_accuracy^2)
% if sigma_ratio=1 -> Prob in circle with r=2DRMS -> 95%
TWO_MRSE_accuracy=2*MRSE_accuracy
%% PRECISION
% 2D analysis
% Simulated X,Y measurements
%v1=randn(1000,2);
% 2D Mean and Variance
mean_2d = [mean(v_2d(:,1)) ; mean(v_2d(:,2))];
sigma_2d = [sqrt(var(v_2d(:,1))) ; sqrt(var(v_2d(:,2)))];
sigma_ratio_2d=sigma_2d(2)/sigma_2d(1)
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 65%
DRMS=sqrt(sigma_2d(1)^2+sigma_2d(2)^2)
% if sigma_ratio=1 -> Prob in circle with r=2DRMS -> 95%
TWO_DRMS=2*DRMS
% if sigma_ratio>0.3 -> Prob in circle with r=CEP -> 50%
CEP=0.62*sigma_2d(1)+0.56*sigma_2d(2)
% Mean and Variance
mean_3d=[mean(v_3d(:,1)) ; mean(v_3d(:,2)) ; mean(v_3d(:,3))];
sigma_3d=[sqrt(var(v_3d(:,1))) ; sqrt(var(v_3d(:,2))) ; sqrt(var(v_3d(:,3)))];
% absolute mean error
% 2D
error_2D_vec=[mean_utm_X-mean_2d(1) mean_utm_Y-mean_2d(2)];
error_2D_m=norm(error_2D_vec)
error_3D_vec=[mean_utm_X-mean_3d(1) mean_utm_Y-mean_3d(2) mean_utm_Z-mean_3d(3)];
error_3D_m=norm(error_3D_vec)
% RMSE 2D
RMSE_X=sqrt(mean((v_3d(:,1)-mean_utm_X).^2))
RMSE_Y=sqrt(mean((v_3d(:,2)-mean_utm_Y).^2))
RMSE_Z=sqrt(mean((v_3d(:,3)-mean_utm_Z).^2))
RMSE_2D=sqrt(mean((v_2d(:,1)-mean_utm_X).^2+(v_2d(:,2)-mean_utm_Y).^2))
RMSE_3D=sqrt(mean((v_3d(:,1)-mean_utm_X).^2+(v_3d(:,2)-mean_utm_Y).^2+(v_3d(:,3)-mean_utm_Z).^2))
% SCATTER PLOT
subplot(3,3,8)
scatter(v_2d(:,1)-mean_2d(1),v_2d(:,2)-mean_2d(2));
hold on;
plot(0,0,'k*');
[x,y,z] = cylinder([TWO_DRMS TWO_DRMS],200);
plot(x(1,:),y(1,:),[0 0.6 0],'Color',[0 0.6 0]);
str = strcat('2DRMS=',num2str(TWO_DRMS), ' m');
text(cosd(65)*TWO_DRMS,sind(65)*TWO_DRMS,str,'Color',[0 0.6 0]);
[x,y,z] = cylinder([CEP CEP],200);
plot(x(1,:),y(1,:),'r--');
str = strcat('CEP=',num2str(CEP), ' m');
text(cosd(80)*CEP,sind(80)*CEP,str,'Color','r');
grid on
axis equal;
xlabel('North [m]','fontname','Times','fontsize', fontsize)
ylabel('East [m]','fontname','Times','fontsize', fontsize)
% 3D analysis
% Simulated X,Y,Z measurements
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 50%
SEP=0.51*sqrt(sigma_3d(1)^2+sigma_3d(2)^2+sigma_3d(3)^2)
% if sigma_ratio=1 -> Prob in circle with r=DRMS -> 61%
MRSE=sqrt(sigma_3d(1)^2+sigma_3d(2)^2+sigma_3d(3)^2)
% if sigma_ratio=1 -> Prob in circle with r=2DRMS -> 95%
TWO_MRSE=2*MRSE
% SCATTER PLOT
subplot(3,3,9)
scatter3(v_3d(:,1)-mean_3d(1),v_3d(:,2)-mean_3d(2), v_3d(:,3)-mean_3d(3));
hold on;
[x,y,z] = sphere();
hSurface=surf(MRSE*x,MRSE*y,MRSE*z); % sphere centered at origin
set(hSurface,'facecolor','none','edgecolor',[0 0.6 0],'edgealpha',1,'facealpha',1);
%axis equal;
xlabel('North [m]','fontname','Times','fontsize', fontsize)
ylabel('East [m]','fontname','Times','fontsize', fontsize)
zlabel('Up [m]','fontname','Times','fontsize', fontsize)
str = strcat('MRSE=',num2str(MRSE), ' m');
text(cosd(45)*MRSE,sind(45)*MRSE,20,str,'Color',[0 0.6 0]);
hh=findall(hf,'-property','FontName');
set(hh,'FontName','Times');
print(hf, 'Figure2.eps', '-depsc')
close(hf);