📄 sa_ex7_9b.m
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% Min-Norm AOA estimation for a M = 6 element array with noise variance = .1
M=6;
D = 2; % number of signals
sig2=.1;
th1=-5*pi/180;
th2=5*pi/180;
a1=[1];
a2=[1];
a=[1];
temp=zeros(1,M-1);
II=eye(M);
u1=II(:,1);
%u1=[1 temp];
for i=2:M
a1=[a1 exp(-1j*i*pi*sin(th1))];
a2=[a2 exp(-1j*i*pi*sin(th2))];
end
A=[a1.' a2.'];
Rss=[1 0;0 1];
Rrr=A*Rss*ctranspose(A)+sig2*eye(M);
[V,D]=eig(Rrr);
N=V(:,1:4); % calculate the noise subspace matrix of eigenvectors
for k=1:180;
th(k)=-pi/6+pi*k/(3*180);
clear a
a=[1];
for jj=2:M
a = [a exp(-1j*jj*pi*sin(th(k)))];
end
P(k)=1./abs(conj(a)*N*N'*u1).^2;
end
figure;
plot(th*180/pi,10*log10(P/max(P)),'k')
grid on
xlabel('Angle')
ylabel('|P(\theta)|')
axis([-30 30 -30 10])
%num2str(A,2)
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