music.m.zip_DOA estimation_doa algorithm_music_music doa_radar

%music.m %high resolution DOA Estimation clear all clc tic %parameters M=8; %size of antenna array doa=[-2 1 10]/180*pi;%doa targets P=length(doa);%num of targets f=7.7e10;%frequency of wave c=3e8;%speed of light lambda=f/c;%lambda of wave d=lambda/2;%array spacing snr=10;%signal/noise rate(dB) N=1024;%samples of received signal(snapshots) peak_thres = -20;%peak searching threshold(dB) %FMCW % for i=-fix(N/2):fix(N/2)-1 % Chirp(i+fix(N/2)+1)=exp(1j*(pi*FMR*(i/Fs)^2)); % end % coeff=conj(fliplr(Chirp)); %antenna model for i=1:P A(:,i)=exp(-j*2*pi*d*[0:M-1]'/lambda*sin(doa(i))); end %signal source model for k=1:P S(k,:)=sqrt(10.^(snr/10))*(randn(1,N)+j*randn(1,N)); end %load from file %X_raw = csvread('RadarData/20171121_a5_b2_a8_b3.csv'); %X = zeros(size(X_raw,1), M); %for i=1:4 % X(:,i) = (X_raw(:, 2*i-1) + 1j*X_raw(:, 2*i)) / 32767.0; %end %received signal X=A*S+1/sqrt(2)*(randn(M,N)+j*randn(M,N)); %svd decomposition of the covarience matrix R=X*X'/N; [V,D,U]=svd(R); US=V(:,1:P);%noise space %music spectrum computing theta=-30:0.1:30; I=eye(M); for ii=1:length(theta) a=exp(-j*2*pi*d*(0:M-1)'*sin(theta(ii)/180*pi)/lambda); Pmusic(ii)=abs(1/(a'*(I-US*US')*a)); end Pmusic=10*log10(Pmusic/max(Pmusic)); %unify & convert to dB %peak searching for ii=1:length(theta) if ii > 2 && (Pmusic(ii-1)>Pmusic(ii) && Pmusic(ii-1)>Pmusic(ii-2) && Pmusic(ii-1)>peak_thres) disp(['peak at angle ', num2str(theta(ii))]) end end %graph figure(1) plot(theta,Pmusic) legend('classic music') xlabel('theta/deg') ylabel('unified Pmusic/dB') title('classic music spectrum') grid on toc