Hi Dion,
According to the description given by you, the below modeified code to your original code would give you elevation in your plot.
format long %The data show that as long shaping scientific
doa = [30]/180*pi; %Direction of arrival
phi_1 = [30]/180*pi; %Azimuth Degree
theta_1 = [90]/180*pi; %Elevation Degree
N = 200; %Snapshots
w = [pi/4]'; %Frequency
M = 3; %Number of array elements
P = length(w); %The number of signal
snr = 20; %SNA
D = [1; cos(phi_1+pi/4)/sin(theta_1); sin(phi_1+pi/4)/sin(theta_1)]; %Steering vector of Single Crossed-Loop/Monopole
xx = 10*rand(1,N) + 1i*rand(1,N); %Simulate signal
x = D*xx;
x = x + awgn(x, snr); %Insert Gaussian white noise
R = x*x'; %Data covariance matrix
[N,V] = eig(R); %Find the eigenvalues and eigenvectors of R
NN = N(:,1:2); %Estimate noise subspace
theta = -180:0.5:180; %Azimuth angles
phi = -180:0.5:180; %Elevation angles
Pmusic = zeros(length(phi), length(theta)); %Initialize Pmusic matrix
for ll = 1:length(phi)
for ii = 1:length(theta)
SS = zeros(1,3);
for jj = 0:M-1
if jj == 0
SS(1+jj) = 1; % Rumus untuk elemen pertama SS
elseif jj == 1
SS(1+jj) = cos((phi(ll)/180*pi)+pi/4)/sin(theta(ii)/180*pi); % Rumus untuk elemen kedua SS
elseif jj == 2
SS(1+jj) = sin((phi(ll)/180*pi)+pi/4)/sin(theta(ii)/180*pi); % Rumus untuk elemen ketiga SS
end
end
PP = SS*NN*NN'*SS';
Pmusic(ll, ii) = abs(1/PP);
end
end
Pmusic = 10*log10(Pmusic/max(Pmusic(:))); %Spatial spectrum function
figure;
surf(phi, theta, Pmusic', 'EdgeColor', 'none');
xlabel('angle \phi/degree');
ylabel('angle \theta/degree');
zlabel('spectrum function P(\theta) /dB');
title('DOA estimation based on MUSIC algorithm');
In the modified code, I have added the elevation angles (phi) and modified the loop to iterate over both azimuth (ll) and elevation (ii) angles. The Pmusic matrix is now a 2D matrix to store the spatial spectrum function for each combination of azimuth and elevation angles.
Thanks.
