matlab-基于matlab的二维FFT多普勒效应和恒虚警CFAR算法仿真-源码

clc; clear; close all; warning off; addpath(genpath(pwd)); max_range = 200; range_resolution = 1; max_velocity = 70; % speed of light = 3e8 c = 3e8; %% User Defined Range and Velocity of target % *%TODO* : % define the target's initial position and velocity. Note : Velocity % remains contant % initial range:max value of 200m and velocity: [-70 to + 70 m/s] target_range = 110; target_velocity = -20; % FMCW B = c /(2*range_resolution); Tchirp= (5.5*2*max_range)/c; slope = B/Tchirp; disp(slope); %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 %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)); for i=1:length(t) % *%TODO* : %For each time stamp update the Range of the Target for constant velocity. r_t(i) = target_range+ target_velocity*t(i); td(i) = 2*r_t(i)/c; Tx(i) = cos(2*pi*(fc*t(i) + (slope*t(i)^2)/2)); Rx(i) = cos(2*pi*(fc*(t(i)-td(i)) + (slope*(t(i)-td(i))^2)/2)); % *%TODO* : Mix(i) = Tx(i).*Rx(i); end % sig = reshape(Mix, [Nr, Nd]); % *%TODO* : %run the FFT on the beat signal along the range bins dimension (Nr) and sig_fft1 = fft(sig, Nr); %normalize. %sig_fft1 = sig_fft1 ./ max(sig_fft1); % Normalize sig_fft1 = sig_fft1 ./ Nr; % *%TODO* : % Take the absolute value of FFT output sig_fft1 = abs(sig_fft1); % *%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. sig_fft1 = sig_fft1(1:(Nr/2)); %plotting the range figure('Name','Range from First FFT') % *%TODO* : % plot FFT output plot(sig_fft1, "LineWidth",2); grid on; axis ([0 200 0 0.5]); xlabel('range'); ylabel('FFT output'); title('1D FFT'); %RANGE DOPPLER RESPONSE 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); 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 %plot(sig_fft2, "LineWidth",2); doppler_axis = linspace(-100,100,Nd); range_axis = linspace(-200,200,Nr/2)*((Nr/2)/400); figure,surf(doppler_axis,range_axis,RDM); xlabel('doppler'); ylabel('range'); zlabel('RDM'); title('2D FFT'); %CFAR implementation % *%TODO* : %Select the number of Training Cells in both the dimensions. Tr = 8; Td = 4; % *%TODO* : %Select the number of Guard Cells in both dimensions around the Cell under %test (CUT) for accurate estimation Gr = 4; Gd = 2; % *%TODO* : % offset the threshold by SNR value in dB offset = 1.4 % *%TODO* : %Create a vector to store noise_level for each iteration on training cells noise_level = zeros(1,1); RDM = RDM/max(max(RDM)); for i = Tr+Gr+1 : Nr/2-(Gr+Tr) % over range for j = Td+Gd+1 : Nd-(Gd+Td) % over doppler noise_level = zeros(1,1); for p = i-(Tr+Gr): i+ (Tr+Gr) for q = j-(Td+Gd): j+(Td+Gd) if (abs(i-p)> Gr ||abs(j-q)>Gd) % convert value from log to linear using db2pow noise_level = noise_level+ db2pow(RDM(p,q)); end end end %after averaging, convert it back to logarithmic using pow2db threshold = pow2db(noise_level/(2*(Td+Gd+1)*2*(Tr+Gr+1)-(Gr*Gd)-1)); % add offset to the noise determine the threshold. threshold = threshold + offset; CUT= RDM(i,j); if (CUT<threshold) RDM(i,j)=0; else RDM(i,j)= 1; % max_T disp(i); disp(j); end end end RDM(RDM~=0 & RDM~=1) = 0; % *%TODO* : figure('Name', 'CFAR') surf(doppler_axis,range_axis,RDM); colorbar; title('offset 1.4');