radar_target_generation_and_detection.m

clear all
clc;

%% Radar Specifications 
%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Frequency of operation = 77GHz
% Max Range = 200m
% Range Resolution = 1 m
% Max Velocity = 100 m/s
%%%%%%%%%%%%%%%%%%%%%%%%%%%

%speed of light = 3e8
%% User Defined Range and Velocity of target
% *%TODO* :
% define the target's initial position and velocity. Note : Velocity
% remains contant
max_range = 200; 
Range_res = 1;
c = 3 * 10^8; 
Vmax = 70;
Vel_res = 3;

Ptar = 110;
Vtar = -20;




%% FMCW Waveform Generation

% *%TODO* :
%Design the FMCW waveform by giving the specs of each of its parameters.
% Calculate the Bandwidth (B), Chirp Time (Tchirp) and Slope (slope) of the FMCW
% chirp using the requirements above.

B = c/(2*Range_res);
Tchirp = (5.5* 2* max_range)/c;
slope = B/Tchirp;

%Operating carrier frequency of Radar 
fc= 77e9;             %carrier freq

                                                          
%The number of chirps in one sequence. Its ideal to have 2^ value for the ease of running the FFT
%for Doppler Estimation. 
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
t_delta = t(2)- t(1);

%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.
r_t=zeros(1,length(t));
td=zeros(1,length(t));


%% Signal generation and Moving Target simulation
% Running the radar scenario over the time. 

for i=1:length(t)         
    
    
    % *%TODO* :
    %For each time stamp update the Range of the Target for constant velocity.
    if i == 1
       r_t(i) = Ptar ;
    else
        r_t(i) = r_t(i-1) + Vtar*t_delta;
    end
    td(i) = 2*r_t(i)/c; 
    % *%TODO* :
    %For each time sample we need update the transmitted and
    %received signal. 
    Tx(i) = cos(2* pi*(fc*t(i) + 0.5*slope*t(i)*t(i)));
    Rx(i) = cos(2* pi*(fc*(t(i)- td(i))+ 0.5*slope*(t(i)- td(i))*(t(i)- td(i))));
    % *%TODO* :
    %Now by mixing the Transmit and Receive generate the beat signal
    %This is done by element wise matrix multiplication of Transmit and
    %Receiver Signal
    Mix(i) = Tx(i).*Rx(i);
    
end

%% RANGE MEASUREMENT

 % *%TODO* :
%reshape the vector into Nr*Nd array. Nr and Nd here would also define the size of
%Range and Doppler FFT respectively.
Mix = reshape(Mix,Nr,Nd);
 % *%TODO* 
%run the FFT on the beat signal along the range bins dimension (Nr) and
%normalize.
signal_fft = fft(Mix);
signal_fft = abs(signal_fft/Nr);
one_dim_fft = signal_fft(1:Nr/2+1,:);
 % *%TODO* :
% Take the absolute value of FFT output

 % *%TODO* :
% Output of FFT is double sided signal, but we are interested in only one side of the spectrum.
% Hence we throw out half of the samples.


%plotting the range
figure ('Name','Range from First FFT')
subplot(2,1,1)

 % *%TODO* :
 % plot FFT output
plot(one_dim_fft(:,50));
axis ([0 200 0 1]);



%% RANGE DOPPLER RESPONSE
% The 2D FFT implementation is already provided here. This will run a 2DFFT
% on the mixed signal (beat signal) output and generate a range doppler
% map.You will implement CFAR on the generated RDM


% Range Doppler Map Generation.

% The output of the 2D FFT is an image that has reponse in the range and
% doppler FFT bins. So, it is important to convert the axis from bin sizes
% to range and doppler based on their Max values.

Mix=reshape(Mix,[Nr,Nd]);

% 2D FFT using the FFT size for both dimensions.
sig_fft2 = fft2(Mix,Nr,Nd);

% Taking just one side of signal from Range dimension.
sig_fft2 = sig_fft2(1:Nr/2,1:Nd);
sig_fft2 = fftshift (sig_fft2);
imagesc(signal_fft);
RDM = abs(sig_fft2);
RDM = 10*log10(RDM) ;

%use the surf function to plot the output of 2DFFT and to show axis in both
%dimensions
doppler_axis = linspace(-100,100,Nd);
range_axis = linspace(-200,200,Nr/2)*((Nr/2)/400);
figure,surf(doppler_axis,range_axis,RDM);

%% CFAR implementation

%Slide Window through the complete Range Doppler Map

% *%TODO* :
%Select the number of Training Cells in both the dimensions.
Tr = 12;
Td = 6; 
Gr = 4;
Gd = 2;
% *%TODO* :
%Select the number of Guard Cells in both dimensions around the Cell under 
%test (CUT) for accurate estimation

% *%TODO* :
% offset the threshold by SNR value in dB
offset =15;
% *%TODO* :
%Create a vector to store noise_level for each iteration on training cells
noise_level = zeros(1,1);


% *%TODO* :
%design a loop such that it slides the CUT across range doppler map by
%giving margins at the edges for Training and Guard Cells.
%For every iteration sum the signal level within all the training
%cells. To sum convert the value from logarithmic to linear using db2pow
%function. Average the summed values for all of the training
%cells used. After averaging convert it back to logarithimic using pow2db.
%Further add the offset to it to determine the threshold. Next, compare the
%signal under CUT with this threshold. If the CUT level > threshold assign
%it a value of 1, else equate it to 0.
[M,N] = size(RDM);
CFAR_output = zeros(M,N);
   % Use RDM[x,y] as the matrix from the output of 2D FFT for implementing
   % CFAR
   disp('Hehe');
for i = 1:(M-(Tr+Gr+1))
   for j = 1:(N-(Td+Gd+1))
       noise_level = 0;
       for p = i:i+Tr
            for q = j:j+Td 
                if(p < i+Tr-(Gr+1) || q < j+Td-(Gd+1))
                   noise_level = noise_level + db2pow(RDM(p,q));
                end
            end
       end
       noise_level = noise_level/((Td*Tr)-(Gd*Gr));
       threshold = pow2db(noise_level) + offset;
       %disp(threshold);
        if(RDM(i+Tr+Gr,j+Td+Gd) > threshold)
            CFAR_output(i+Tr+Gr, j+Td+Gd) = 1;
        end
   end
end




% *%TODO* :
% The process above will generate a thresholded block, which is smaller 
%than the Range Doppler Map as the CUT cannot be located at the edges of
%matrix. Hence,few cells will not be thresholded. To keep the map size same
% set those values to 0. 
 








% *%TODO* :
%display the CFAR output using the Surf function like we did for Range
%Doppler Response output.
figure,surf(doppler_axis,range_axis,CFAR_output);
colorbar;