SFND_Radar_Target_Generation_and_Detection

Writeup for submission

Radar Specifications

Frequency of operation = 77GHz
Max Range = 200m
Range Resolution = 1 m
Max Velocity = 100 m/s
Speed of light = 3e8

Target initial status:
Initial Range = 100 m
Initial Velocity = 10 m/s;

FMCW Waveform Design

sweepBandwidth = c/(2*rangeResolution);
Tchirp = 5.5*2*maxRange/c;
sweepSlope = sweepBandwidth/Tchirp;

Simulation Loop

Set the vectors for looping :

Nd = 128;                   % #of doppler cells OR #of sent periods % number of chirps

% The number of samples on each chirp. 
Nr = 1024;                  %for length of time OR # of range cells

% Timestamp for running the displacement scenario for every sample on each
% chirp
t = linspace(0, Nd*Tchirp, Nr*Nd); %total time for samples


% Creating the vectors for Tx, Rx and Mix based on the total samples input.
Tx = zeros(1,length(t)); %transmitted signal
Rx = zeros(1,length(t)); %received signal
Mix = zeros(1,length(t)); %beat signal

% Similar vectors for range_covered and time delay.
rangeTarget = zeros(1,length(t));
timeDelay = zeros(1,length(t));

Then run the loop:

for i = 1 : length(t)      

    rangeTarget(i) = initTargetRange + initTargetVelocity*t(i);
    timeDelay(i) = 2*rangeTarget(i)/c;
    Tx(i) = cos(2*pi*(carrierFreq*t(i)+sweepSlope*t(i)^2/2));
    Rx(i) = cos(2*pi*(carrierFreq*(t(i)-timeDelay(i)) + (sweepSlope*(t(i)-timeDelay(i))^2)/2));
    Mix(i) = times(Tx(i), Rx(i));
    
end

Range FFT

Implement Fast Fourier Transform and do some post-processing:

MixFFT = fft(Mix,Nr)./Nr;
MixFFT = abs(MixFFT);
MixFFT  = MixFFT(1:Nr/2);

In the image above, a range of 100m is detected.

2D CFAR

The output from 2D-FFT(Range Doppler Map, RDM) as follows:

First set numbers of training and guard cells for both directions, and set offset for threshold:

% Select the number of Training Cells in both the dimensions.
Tr = 2;
Td = 1;

% Select the number of Guard Cells in both dimensions around the Cell under 
% test (CUT) for accurate estimation
Gr = 2;
Gd = 1;

% offset the threshold by SNR value in dB
offset = 1.5;

Then calculate the number of training cells in a window based on parameters above:

windowSize = (2*Tr+2*Gr+1)*(2*Td+2*Gd+1);
numTrainingCells = windowSize-(2*Gr+1)*(2*Gd+1);

Then slide the window over the Range Doppler Map :

for i = 1 : RDMd-2*(Td+Gd)
    for j = 1 : RDMr-2*(Tr+Gr)
        
        % Crop the RDM with patch size
        trainingCellsPatch = db2pow( RDM(j : j+2*(Tr+Gr), i : i+2*(Td+Gd)) );
        % set guard cells and CUT to 0
        trainingCellsPatch(Tr+1 : end-Tr, Td+1 : end-Td) = 0;
        
        noiseLevel = pow2db(sum(sum(trainingCellsPatch))/numTrainingCells);
        noiseLevel = noiseLevel*offset; % scale noise level with offset
        
        if RDM(j+(Td+Gr),i+(Td+Gd)) > noiseLevel
            mapCFAR(j+(Td+Gr), i+(Td+Gd)) = 1;
        else
            mapCFAR(j+(Td+Gr), i+(Td+Gd)) = 0;
        end
           
    end
end

The output of 2D CA-CFAR :

As shown in the image, a range of 100m and a doppler velocity of 10m/s are detected.