This repository contains the submission for the Radar project which is part of Udacity's Sensor Fusion Nanodegree program.

• Loop over elements of RDM array each iteration selecting one cell to be the CUT (Cell Under Test)
  for i = Tr+Gr+1 : (Nr/2)-(Gr+Tr)
for j = Td+Gd+1 : Nd-(Gd+Td)
• For each iteration loop over the training cells "excluding the guarding cells" to sum their values
  for p = i-(Tr+Gr) : i+(Tr+Gr)
for q = j-(Td+Gd) : j+(Td+Gd)
• Calculate the average of the noise value
  noise_level = noise_level + db2pow(RDM(p,q));
• Convert using pow2db
  th = pow2db(noise_level/(2*(Td+Gd+1)*2*(Tr+Gr+1)-(Gr*Gd)-1));
• Add the offset value
  th = th + offset;
• If the CUT is greater then the threshold replace it by 1, else 0
  

• Tr = 10, Td = 8 For both Range and Doppler Training Cells.
• Gr = 4, Gd = 4 For both Range and Doppler Guard Cells.
• offset = 1.3 the offset value.

This was done throught sclicing the output such that we have the surrounding rows and columns sepending on the Training cells for both range and doppler.
RDM(union(1:(Tr+Gr),end-(Tr+Gr-1):end),:) = 0; % Rows
RDM(:,union(1:(Td+Gd),end-(Td+Gd-1):end)) = 0; % Columns

This is the output for a target at 120m moving at -20 m/s relative speed.