44 lines
1.2 KiB
Matlab
44 lines
1.2 KiB
Matlab
function [esti_ang_deg, P_MUSIC, test_ang_deg] = df_1D_MUSIC(snapshot, Ntarget, array_struct, fov_deg, unit_ang_deg , plot_flag)
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% Number of Snapshots
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Nsnap = size(snapshot, 2);
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% Estimated Correlation matrix of X
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Rx = (1/Nsnap) * (snapshot * snapshot');
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% MUSIC algorithm
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% Eigen decomposition
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[Q, ~, ~] = svd(Rx);
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% Noise subspace
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Q_n = Q(:, Ntarget+1:end);
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% MUSIC algorithm
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test_ang_deg = -fov_deg : unit_ang_deg : fov_deg - unit_ang_deg;
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P_MUSIC = zeros(1, length(test_ang_deg));
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if size(array_struct.eff_ch_loc, 1) == 1
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array_struct.eff_ch_loc = array_struct.eff_ch_loc.';
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end
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Q_n_square = Q_n * Q_n';
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for ang_idx = 1 : length(test_ang_deg)
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z = exp(1i * 2 * pi / array_struct.lambda_c * array_struct.unit * -sind(test_ang_deg(ang_idx)));
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test_sv = z.^array_struct.eff_ch_loc;
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P_MUSIC(ang_idx) = 1 / (test_sv' * Q_n_square * test_sv);
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end
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if plot_flag == 1
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figure()
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plot(test_ang_deg, pow2db(abs(P_MUSIC)));
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grid on
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xlabel('Test angle [deg]');
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ylabel('Magnitude [dB]');
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end
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[pks, pks_ang, ~, ~] = findpeaks(pow2db(abs(P_MUSIC)), test_ang_deg);
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[~, order] = sort(pks, 'descend');
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esti_ang_deg = pks_ang(order(1:Ntarget));
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end |