sa_ex7_15b.m

这个是英文版<<Smart Antennas for Wireless Communications>>配套的matlab源程序

sa% ESPRIT AOA estimation for a M = 4 element array with noise variance = .1



M = 4;    % number of array elements
D = 2;  % number of signals
sig2 = .1;    % noise variance
th1 = -10*pi/180;      % angle of arrival 1
th2 = 20*pi/180;       % angle of arrival 2

i = 1:M;
a1 = exp(1j*(i-1)*pi*sin(th1));
a2 = exp(1j*(i-1)*pi*sin(th2));
A=[a1.' a2.'];          % calculate matrix of steering vectors for the D signals

Rss = [1 0;0 1];  Rxx = A*Rss*A'+sig2*eye(M);

[V,Dia]=eig(Rxx);           % find eigenvalues and eigenvectors of Rrr
[Y,Index]=sort(diag(Dia));   % sorts the eigenvalues from least to greatest
ES=V(:,Index(M-D+1:M));      % calculate the signal subspace matrix of eigenvectors
                              % using the sorting done in the previous line
          
E1=ES(1:M/2+1,:);           % construct the signal subspace form the first K rows of ES (K = M/2+1)
E2=ES(M/2:M,:);             % construct the signal subspace from the last K rows of ES
C=[E1';E2']*[E1 E2];
[EC,tmp]=eig(C);            % Perform the eigendecomposition on the matrix C
E12=EC(1:2,3:4);            % construct the E12 submatrix
E22=EC(3:4,3:4);            % construct the E22 submatrix
PSI=-E12*inv(E22);          % estimate PSI, the rotation operator
[Vp,Ep]=eig(PSI);           % find the eigenvalues and eigenvectors of rotation operator PSI
e=diag(Ep);

angs=asin(angle(e)/pi)*180/pi     % find the angles associated with the roots