Number of snapshots

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clc clear all format long A=[30 45]/180pi; %Arrival of signal S=300; %Number of snapshots included f=[pi/6 pi/4]’; %Signal Frequency N=8; %Array elements count L=length(f); %Length(Number) of signal lambda=160; %Signal Wavelength t=lambda/2; %Spacing of elements snr=30; %Signal-to-Noise ratio T=zeros(L,N); %Matrix creation with L row and N column for p=1:L T(p,:)=exp(-j2pitsin(A(p))/lambda[0:N-1]); %Matrix Allocation end T=T’; yy=2exp(j(f[1:S])); %Simulate of signal y=Tyy; y=y+awgn(y,snr); %Inserting AWGN R=yy’; %Covariance matrix data [S,U]=eig(R); %Find the eigenvalues and eigenvectors HH=S(:,1:N-L); %Estimating noise subspace theta=-90:0.5:90; %Searching the peak for ii=1:length(theta) OO=zeros(1,length(N)); for jj=0:N-1 OO(1+jj)=exp(-j2jjpitsin(theta(ii)/180pi)/lambda); end RR=OOHHHH’OO’; Palgorithm(ii)=abs(1/ RR); end Palgorithm=10*log10(Palgorithm/max(Palgorithm)); %Signal function of Spatial spectrum plot(theta,Palgorithm,’-m’) grid on ylabel(‘ P(theta) spectrum function’) xlabel(‘ (theta) angle in degree’) title(‘DOA Estimation using MUSIC Algorithm ‘)

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