diff --git a/targets/PROJECTS/CORRIDOR/log_read.m b/targets/PROJECTS/CORRIDOR/log_read.m
index acc78059e5..437d8dbac4 100644
--- a/targets/PROJECTS/CORRIDOR/log_read.m
+++ b/targets/PROJECTS/CORRIDOR/log_read.m
@@ -1,7 +1,12 @@
-top_dir = 'E:\EMOS\corridor\trials2 train';
+clear all
+close all
+
+top_dir = 'P:\florian\CORRIDOR\trials2 train'; % needs to be updated according to your computer
 d1 = dir(fullfile(top_dir,'UHF','*.log'));
 d2 = dir(fullfile(top_dir,'2.6GHz','*.log'));
 
+
+
 start_time = [1.400489088000000e+09 1.400493112000000e+09 1.400499696000000e+09 1.400506864000000e+09];
 
 for idx=1:length(d1)
@@ -19,7 +24,7 @@ for idx=1:length(d1)
     
     rtime1 = data1{idx}(:,1) - data1{idx}(1,1);
     rtime2 = data2{idx}(:,1) - data2{idx}(1,1);
-        
+    
     %% plot gps coordinates
     figure(idx*10+1);
     hold off
@@ -29,19 +34,8 @@ for idx=1:length(d1)
     xlabel('lat [deg]');
     ylabel('lon [deg]')
     legend('UHF','2.6GHz')
+    title(sprintf('Run %d',idx));
     
-    %% compute distance
-    distances1=zeros(1,size(data1{idx},1));
-    distances2=zeros(1,size(data2{idx},1));
-    for i=1:size(data1{idx},1)
-        distances1(i)=Dist_Calc_from_GPS(data1{idx}(i,7),data1{idx}(i,8),48.25073056,1.55481944);
-    end
-
-    for i=1:size(data2{idx},1)
-        distances2(i)=Dist_Calc_from_GPS(data2{idx}(i,7),data2{idx}(i,8),48.25073056,1.55481944);
-    end
-
-   
     %% plot RSSI
     % TODO: convert time (in unix epoch) into something more meaninful
     figure(idx*10+2);
@@ -56,26 +50,232 @@ for idx=1:length(d1)
     ylabel('RSSI [dBm]')
     title(sprintf('Run %d',idx));
     
-    %%
-    figure(idx*10+3)
-    hold off
-    plot(rtime1,distances1,'r')
-    hold on
-    plot(rtime2,distances2,'b')
-    xlabel('time [seconds]')
-    ylabel('dist [km]')
-    legend('UHF','2.6GHz')
     
-    %%
-    figure(idx*10+4)
-    hold off
-    plot(distances1,data1{idx}(:,13),'rx')
-    hold on
-    plot(distances2,data2{idx}(:,13),'bx')
-    plot(distances2,data2{idx}(:,19),'cx')
-    plot(distances2,data2{idx}(:,25),'mx')
-    xlabel('dist [km]')
-    ylabel('RSSI [dBm]')
-    legend('UHF','2.6GHz card 1','2.6GHz card 2','2.6GHz card 3');
+    
+    %% measured distance (km)
+    % We can get the distance between the base station and the RX antenna from the GPS coordinates
+    distances1=zeros(size(data1{idx},1),1);
+    distances2=zeros(size(data2{idx},1),1);
+    for i=1:size(data1{idx},1)
+        distances1(i)=Dist_Calc_from_GPS(data1{idx}(i,7),data1{idx}(i,8),48.25073056,1.55481944);
+    end
+    
+    for i=1:size(data2{idx},1)
+        distances2(i)=Dist_Calc_from_GPS(data2{idx}(i,7),data2{idx}(i,8),48.25073056,1.55481944);
+    end
+    
+    
+    figure (100+idx)
+    subplot(1,2,1)
+    plot(rtime1,distances1,'r',rtime1,smooth(data1{idx}(:,13),100),'b')
+    title(sprintf('Run %d with the measured distance : UHF',idx));
+    xlabel('time [s]');
+    legend('distance [km]','RSSI [dBm]');
+    
+    subplot(1,2,2)
+    plot(rtime2,distances2,'r',rtime2,smooth(data2{idx}(:,13),100),'b')
+    title(sprintf('Run %d with the measured distance : 2.6GHz ',idx));
+    xlabel('time [s]');
+    legend('distance [km]','RSSI [dBm]');
+    %% estimated distance under the assumption of a constant speed
+    % We assume that the TGV speed is constant and then we find the distances to the base station with the time vector
+    
+    TGV_speed=82.5;%constant TGV speed in m/s
+    
+    
+    
+    [RSSI_max1,I_RSSI_max1]=max(data1{idx}(:,13));%we find the index corresponding to the maximum of RSSI
+    time01=rtime1(I_RSSI_max1)*ones(length(rtime1),1);%time corresponding to the maximim of RSSI
+    new_distances1=(TGV_speed*abs(rtime1-time01))/1000+min(distances1)*ones(length(rtime1),1);% new distance in km. is is minimum when the RSSI is maximum
+    
+    
+    [RSSI_max2,I_RSSI_max2]=max(data2{idx}(:,13));
+    time02=rtime2(I_RSSI_max2)*ones(length(rtime2),1);
+    new_distances2=(TGV_speed*abs(rtime2-time02))/1000+min(distances2)*ones(length(rtime2),1);% distance in km
+    
+    
+    if (idx==2)%For Run 2, there is an anomalous peak for the RSSI at the end. Here we ignore it 
+        [RSSI_max2,I_RSSI_max2]=max(data2{idx}(1:32900,13));
+        time02=rtime2(I_RSSI_max2)*ones(length(rtime2),1);
+        new_distances2=(TGV_speed*abs(rtime2-time02))/1000+min(distances2)*ones(length(rtime2),1);% distance in km
+    end
+    
+    figure (200+idx)
+    subplot(1,2,1)
+    plot(rtime1,new_distances1,'r',rtime1,smooth(data1{idx}(:,13),100),'b')
+    title(sprintf('Run %d with the estimated distance : UHF',idx));
+    xlabel('time [s]');
+    legend('distance [km]','RSSI [dBm]');
+    
+    subplot(1,2,2)
+    plot(rtime2,new_distances2,'r',rtime2,smooth(data2{idx}(:,13),100),'b')
+    title(sprintf('Run %d with the estimated distance : 2.6GHz ',idx));
+    xlabel('time [s]');
+    legend('distance [km]','RSSI [dBm]');
+    
+    
+    
+    
+    
+    
    
+    
+    
+    
+    
+    %% rssi(dBm) versus distance (log scale)
+    % We will plot the rssi versus the distance with the data before the passing of the train, and with the data after the passingof the train 
+   
+    % we heuristically determine a starting point and a ending point for the linear fitting   
+    if idx==1
+        
+        distance_before_break1_start=0.3913;%in km
+        distance_before_break1_end=27.71;
+        distance_before_break2_start=0.3282;
+        distance_before_break2_end=15.24;
+        
+        distance_after_break1_start=0.85;%in km
+        distance_after_break1_end=9;
+        distance_after_break2_start=0.2911;
+        distance_after_break2_end=9;
+    end
+    
+    if idx==2
+        distance_before_break1_start=0.8468;%in km
+        distance_before_break1_end=9;
+        distance_before_break2_start=0.4822;
+        distance_before_break2_end=7.099;
+        
+        distance_after_break1_start=0.5812;%in km
+        distance_after_break1_end=18.76;
+        distance_after_break2_start=0.4402;
+        distance_after_break2_end=10;
+    end
+    
+    if idx==3
+        distance_before_break1_start=4.258;%in km
+        distance_before_break1_end=29.46;
+        distance_before_break2_start=8.375;
+        distance_before_break2_end=29.66;
+        
+        distance_after_break1_start=2.274;%in km
+        distance_after_break1_end=5.376;
+        distance_after_break2_start=5.996;
+        distance_after_break2_end=7.613;
+    end
+    
+    if idx==4
+        distance_before_break1_start=0.1176;%in km
+        distance_before_break1_end=3.489;
+        distance_before_break2_start=0.1344;
+        distance_before_break2_end=3.78;
+        
+        distance_after_break1_start=0.3793;%in km
+        distance_after_break1_end=9;
+        distance_after_break2_start=0.5443;
+        distance_after_break2_end=9;
+    end
+    
+    % indexes of the starting and ending points with the data before the passing of the
+    % train
+    index_break1_before_start=1;
+    index_break2_before_start=1;
+    index_break1_before_end=1;
+    index_break2_before_end=1;
+    
+    % indexes of the starting and ending points with the data after the passing of the
+    % train
+    index_break1_after_start=I_RSSI_max1;
+    index_break2_after_start=I_RSSI_max2;
+    index_break1_after_end=I_RSSI_max1;
+    index_break2_after_end=I_RSSI_max2;
+    
+    %starting points
+    while (index_break1_before_start<length(new_distances1)) && (new_distances1(index_break1_before_start)>distance_before_break1_start)
+        index_break1_before_start=index_break1_before_start+1;
+    end
+    while (index_break2_before_start<length(new_distances2)) && (new_distances2(index_break2_before_start)>distance_before_break2_start)
+        index_break2_before_start=index_break2_before_start+1;
+    end
+    %ending points
+    while (index_break1_before_end<length(new_distances1)) && (new_distances1(index_break1_before_end)>distance_before_break1_end)
+        index_break1_before_end=index_break1_before_end+1;
+    end
+    while (index_break2_before_end<length(new_distances2)) && (new_distances2(index_break2_before_end)>distance_before_break2_end)
+        index_break2_before_end=index_break2_before_end+1;
+    end
+    
+    
+    %starting points
+    while (index_break1_after_start<length(new_distances1)) && (new_distances1(index_break1_after_start)<distance_after_break1_start)
+        index_break1_after_start=index_break1_after_start+1;
+    end
+    while (index_break2_after_start<length(new_distances2)) && (new_distances2(index_break2_after_start)<distance_after_break2_start)
+        index_break2_after_start=index_break2_after_start+1;
+    end
+    
+    %ending points
+    while (index_break1_after_end<length(new_distances1)) && (new_distances1(index_break1_after_end)<distance_after_break1_end)
+        index_break1_after_end=index_break1_after_end+1;
+    end
+    while (index_break2_after_end<length(new_distances2)) && (new_distances2(index_break2_after_end)<distance_after_break2_end)
+        index_break2_after_end=index_break2_after_end+1;
+    end
+    
+    
+    
+    
+    
+    figure(idx*10+3)
+    
+    
+    subplot(2,1,1)
+    
+    hold off
+    linearCoef1_before = polyfit(10*log10(new_distances1(index_break1_before_end:index_break1_before_start)),data1{idx}(index_break1_before_end:index_break1_before_start,13),1);
+    linearFit1_before = polyval(linearCoef1_before,10*log10(new_distances1(index_break1_before_end:index_break1_before_start)));
+    semilogx(new_distances1(1:I_RSSI_max1),data1{idx}(1:I_RSSI_max1,13),'rx',new_distances1(index_break1_before_end:index_break1_before_start),linearFit1_before,'r-')
+    display(sprintf('Run %d :slope UHF before: %f',idx,linearCoef1_before(1)))
+    
+    
+    hold on
+    linearCoef2_before = polyfit(10*log10(new_distances2(index_break2_before_end:index_break2_before_start)),data2{idx}(index_break2_before_end:index_break2_before_start,13),1);
+    linearFit2_before = polyval(linearCoef2_before,10*log10(new_distances2(index_break2_before_end:index_break2_before_start)));
+    semilogx(new_distances2(1:I_RSSI_max2),data2{idx}(1:I_RSSI_max2,13),'bx',new_distances2(index_break2_before_end:index_break2_before_start),linearFit2_before,'b-')
+    display(sprintf('Run %d :slope 2.6GHz before: %f',idx,linearCoef2_before(1)))
+    
+    title(sprintf('Run %d: With the data before the passing of the train',idx))
+    legend('UHF','UHF:linear fitting','2.6GHz card 1','2.6GHz card 1:linear fitting');
+    xlabel('distance [km]')
+    ylabel('RSSI [dBm]')
+    
+    subplot(2,1,2)
+    
+    hold off
+    linearCoef1_after = polyfit(10*log10(new_distances1(index_break1_after_start:index_break1_after_end)),data1{idx}(index_break1_after_start:index_break1_after_end,13),1);
+    linearFit1_after = polyval(linearCoef1_after,10*log10(new_distances1(index_break1_after_start:index_break1_after_end)));
+    semilogx(new_distances1(I_RSSI_max1:end),data1{idx}(I_RSSI_max1:end,13),'rx',new_distances1(index_break1_after_start:index_break1_after_end),linearFit1_after,'r-')
+    display(sprintf('Run %d :slope UHF after: %f',idx,linearCoef1_after(1)))
+    
+    
+    hold on
+    linearCoef2_after = polyfit(10*log10(new_distances2(index_break2_after_start:index_break2_after_end)),data2{idx}(index_break2_after_start:index_break2_after_end,13),1);
+    linearFit2_after = polyval(linearCoef2_after,10*log10(new_distances2(index_break2_after_start:index_break2_after_end)));
+    semilogx(new_distances2(I_RSSI_max2:end),data2{idx}(I_RSSI_max2:end,13),'bx',new_distances2(index_break2_after_start:index_break2_after_end),linearFit2_after,'b-')
+    display(sprintf('Run %d :slope 2.6GHz after: %f',idx,linearCoef2_after(1)))
+    
+    title(sprintf('Run %d: With the data after the passing of the train',idx))
+    legend('UHF','UHF:linear fitting','2.6GHz card 1','2.6GHz card 1:linear fitting');
+    xlabel('distance [km]')
+    ylabel('RSSI [dBm]')
+    
+    
+    
+    
+   
+    
+    
+    
+    
+    
 end
\ No newline at end of file