+ Post New Thread
Results 1 to 1 of 1
  1. #1
    Newbie level 1
    Points: 16, Level: 1

    Join Date
    May 2019
    Posts
    1
    Helped
    0 / 0
    Points
    16
    Level
    1

    How to simulate FMCW and process Radar 2D matrix in Matlab. Problem explained.

    Hi. I am a Masters Student who requires this as a first step to start my Thesis, and I am new to matlab signal processing. I have theoretical knowledge but I just started Matlab implementation of the same. Also I am completely new to the FMCW tool chain. I have to create an FMCW signal, transmit, receive and mix them to get the IF signal, and inturn get the radar 2D matrix for post processing. But I my 2nd FFT doesnt give the correct value of velocity. I set the chirp parameters and thus obtain the Vmax and Rmax values.
    There are 2 IF signals created : one the theoretical, obtained from equation, and the other is obtained from mixing the received and transmitted signals and applying a Lowpass Filter. The goal is to create a radar 2D matrix (No. of samples x No. of chirps) so that I can try post processing to get the Range and velocity. I am able to get the correct range value, but the velocity is always wrong. I am unable to figure out what's wrong. I have posted the code below. Any help would be greatly appreciated.
    Thanks in advance.


    Code Matlab M - [expand]
    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    49
    50
    51
    52
    53
    54
    55
    56
    57
    58
    59
    60
    61
    62
    63
    64
    65
    66
    67
    68
    69
    70
    71
    72
    73
    74
    75
    76
    77
    78
    79
    80
    81
    82
    83
    84
    85
    86
    87
    88
    89
    90
    91
    92
    93
    94
    95
    96
    97
    98
    99
    100
    101
    102
    103
    104
    105
    106
    107
    108
    109
    110
    111
    112
    113
    114
    115
    116
    117
    118
    119
    120
    121
    122
    123
    124
    125
    126
    127
    128
    129
    130
    131
    132
    133
    134
    135
    136
    137
    138
    139
    140
    141
    142
    143
    144
    145
    146
    147
    148
    149
    150
    151
    152
    153
    154
    155
    156
    157
    158
    159
    160
    161
    162
    163
    164
    165
    166
    167
    168
    169
    170
    171
    172
    173
    174
    175
    176
    177
    178
    179
    180
    181
    182
    183
    184
    185
    
    close all;
    clear all;
    clc;
     
    %% Params
    c=3e8;
     
    %%% Transmit side params
    f0 = 10e9;
    % dR = 15e-2;
    % Rmax = 7.5e3;
    % dV = 0.94;
    % Vmax = 7.5;
     
    B = 1e9;
    T = 1e-5;
    Ns = 2048;
    L = 64;
     
    % fdmax=1/(1*T);
     
    %%% Receive side params
    R1 = 70;
    v1 = 50; % m/s
     
    %% Derived Params
    %----------------
    % If Vmax, Rmax, dR, dV specified
    % T = c/(4*Vmax*f0);
    % B=c/(2*dR);
    % Ns = (4*B*Rmax)/c;
    % L = ceil(c/(2*f0*dV*T)) ; % No.of Chirps
    %-------------------------------
    %If B, T, Ns, L are specified
    Vmax = c/(4*T*f0);
    dR=c/(2*B);
    m = B/T;
    Rmax = Ns*c/(4*B);
    dV = c/(2*f0*L*T);
     
    %-------------------------------
    % n=ceil(log10(Vmax));
    % factor = roundn(Vmax,n)
    % v1 = factor-v1;
    %-------------------------------
     
    t0 = 2*R1/c;
    phi0 = 2*pi*f0*t0 - pi*m*(t0^2);
    fb = 2*R1*m/c;
    fd = -2*v1*f0/c;
     
    % fif_val1 = fb + fd;           % For comparison purpose
    % fif_val2 = m*t0 +f0*2*v/c;
    % v1=v1-T*1e8/2;
     
    fif_val= fb + fd;
    Ts = T/Ns;
    Fs = 1/Ts;
     
    %Therefore
    t=0:Ts:T-Ts;
    % 
     
    %% Big time scale
    time_scale = zeros(1,L*Ns);
    time_scale(1:length(t)) = t(1:end);
     
    %% For No.of chirps = L
     for i=1:L-1
        time_scale((i*length(t))+1:(i+1)*length(t)) = t + (T*i);
     end
    %  time_scale=0:Ts:T*L-Ts;
     
    % td=1e-6;
    td=2*(R1+v1.*t)/c;
     
    % R= c*td/2
    f_t = f0 + m*t;
    % f_r = f0 + m*(t-td)/2;
     
    %% For L chirps 
    t=time_scale;
    td=2*(R1+v1.*t)/c;
    f_t = repmat(f_t,1,L);
     
    % New -----------
    f_r = zeros(size(f_t));
    n = ceil(t0/Ts);
    f_r(n+1:end) = f_t(1:end-n);
    f_r = f_r + fd;
    %----------
     
    % f_r = repmat(f_r,1,L);
    f_if = f_t-f_r;
    % f_if(1:n) = 0;
    st = cos(2*pi.*f_t.*t);
    rt = cos(2*pi.*f_r.*t);
    % rt = cos(2*pi.*f_r.*(t+td));  %%%%%%%%
    % rt = cos(2*pi*(f0(t-td) + m*((t-td)^2)/2));
                                                                                % t = time_scale;
                                                                                % st = repmat(st,1,L);
                                                                                % rt = repmat(rt,1,L);
                                                                                % f_t = repmat(f_t,1,L);
                                                                                % f_r = repmat(f_r,1,L);
    fif = rt.*st;
    fif_lpf = lowpass(fif,max(f_if),2*B,'Steepness',0.8);
    %% Final IF signal
    fif_the = 0.5*cos(phi0 + 2*pi*fif_val.*t);
    % fif_the = 0.5*cos(phi0 + 2*pi.*f_if.*t);
     
    %% Plots
    % xlimit = 2*T;
    xlimit = T/2;
     
    %-------Fig 3 For Big time scale----------%
    figure(3)
    subplot(511)
    plot(t,st);
    xlim([0 xlimit])
    title("Received signal as st = cos(2*pi.*f_t.*t);")
    subplot(512)
    plot(t,rt);
    xlim([0 xlimit])
    title("Received signal as rt = cos(2*pi.*f_r.*t);")
    subplot(513)
    plot(t,fif);
    xlim([0 xlimit])
    title("IF after Mixing")
    subplot(514)
    plot(t,fif_lpf);
    xlim([0 xlimit])
    title("IF after LPF")
    subplot(515)
    plot(t,fif_the);
    xlim([0 xlimit])
    title("IF from fif_the = 0.5*cos(phi0 + 2*pi*fif_val.*t);")
     
    figure(5)
    subplot(211)
    plot(t,f_t);
    % xlim([0 T/10])
    hold on;
    grid on;
    plot(t,f_r);
    ylim([f0-B f0+(2*B)]);
    xlim([0 T*5])
    legend('f_t','f_r')
    subplot(212)
    plot(t,f_if);
    grid on;
    xlim([0 T*5])
     
    %% Post processing
    % radar_mat = reshape(fif_the,Ns,L); %% Using the Theoretical IF Signal
    radar_mat = reshape(fif_lpf,Ns,L); %% Using the Mixed and LPF IF Signal
     
    %% Window function
    window_1D = hann(size(radar_mat,1));
    window_2D = hann(size(radar_mat,2));
     
    %% FFT
    rfft = (fft(radar_mat.*window_1D,[],1));
    rfft = rfft./max(max(rfft)); %Normalization
    rfft = rfft(1:size(rfft)/2,:);
     
    % zeroPadding = zeros(size(rfft));
    % rfft = vertcat(rfft,zeroPadding);
     
    vfft = fft(rfft.*window_2D',[],2);
     
    %% Normalization
    % normalize = vfft./max(max(vfft));
    %vfft = fftshift(vfft,2)
    vfft = vfft./max(max(vfft));
     
    %% Range and Velocity vectors
    R = 0:dR:Rmax-dR;
    V = linspace(-Vmax, Vmax, L);
     
    figure(4);
    h=imagesc(V,R,20*log10(abs(fftshift(vfft,2))),[-60 0]);
    cb = colorbar;
    set(gca,'YDir','normal')
    xlabel('Velocity (m/s)');
    ylabel('Range (m)');
    Last edited by bassa; 28th May 2019 at 16:32. Reason: add code tag

    •   AltAdvertisement

        
       

--[[ ]]--