1
0
mirror of https://github.com/gnss-sdr/gnss-sdr synced 2024-11-15 06:14:58 +00:00
gnss-sdr/utils/reproducibility/ieee-access18/plot_dump.m

220 lines
7.5 KiB
Matlab

% -------------------------------------------------------------------------
%
% GNSS-SDR is a Global Navigation Satellite System software-defined receiver.
% This file is part of GNSS-SDR.
%
% SPDX-License-Identifier: GPL-3.0-or-later
% SPDX-FileCopyrightText: Antonio Ramos, 2018. antonio.ramos(at)cttc.es
%
% -------------------------------------------------------------------------
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/access18.dat', 'r');
dinfo = dir('data/access18.dat');
filesize = dinfo.bytes;
aux = 1;
while ne(ftell(fileID), filesize)
navsol.TOW_at_current_symbol_ms(aux) = fread(fileID, 1, 'uint32');
navsol.week(aux) = fread(fileID, 1, 'uint32');
navsol.RX_time(aux) = fread(fileID, 1, 'double');
navsol.user_clock_offset(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.VX(aux) = fread(fileID, 1, 'double');
navsol.VY(aux) = fread(fileID, 1, 'double');
navsol.VZ(aux) = fread(fileID, 1, 'double');
navsol.varXX(aux) = fread(fileID, 1, 'double');
navsol.varYY(aux) = fread(fileID, 1, 'double');
navsol.varZZ(aux) = fread(fileID, 1, 'double');
navsol.varXY(aux) = fread(fileID, 1, 'double');
navsol.varYZ(aux) = fread(fileID, 1, 'double');
navsol.varZX(aux) = fread(fileID, 1, 'double');
navsol.latitude(aux) = fread(fileID, 1, 'double');
navsol.longitude(aux) = fread(fileID, 1, 'double');
navsol.height(aux) = fread(fileID, 1, 'double');
navsol.number_sats(aux) = fread(fileID, 1, 'uint8');
navsol.solution_status(aux) = fread(fileID, 1, 'uint8');
navsol.solution_type(aux) = fread(fileID, 1, 'uint8');
navsol.AR_ratio_factor(aux) = fread(fileID, 1, 'float');
navsol.AR_ratio_threshold(aux) = fread(fileID, 1, 'float');
navsol.GDOP(aux) = fread(fileID, 1, 'double');
navsol.PDOP(aux) = fread(fileID, 1, 'double');
navsol.HDOP(aux) = fread(fileID, 1, 'double');
navsol.VDOP(aux) = fread(fileID, 1, 'double');
aux = aux + 1;
end
fclose(fileID);
mean_Latitude = mean(navsol.latitude);
mean_Longitude = mean(navsol.longitude);
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 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)
% 3D 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
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_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))
% 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 2D
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,:), '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)
%% SCATTER PLOT 3D
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);
xlabel('North [m]', 'fontname', 'Times', 'fontsize', fontsize-2)
ylabel('East [m]', 'fontname', 'Times', 'fontsize', fontsize-2)
zlabel('Up [m]', 'fontname', 'Times', 'fontsize', fontsize-2)
str = strcat('MRSE=', num2str(MRSE), ' m')
text(cosd(45)*MRSE, sind(45)*MRSE, 20, str, 'Color', [0 0.6 0]);
a = gca;
set(a, 'fontsize', fontsize-6)
hh = findall(hf, '-property', 'FontName');
set(hh, 'FontName', 'Times');
print(hf, 'Figure2.eps', '-depsc')
close(hf);