Initial Commit.

Functions/01. Direction finding/df_OMP.m

@@ -0,0 +1,61 @@
+function [esti_ang_deg, P_OMP, test_ang_deg] = df_OMP(snapshot, fov_deg, unit_ang_deg, array_struct, sparsity_val, plot_flag)
+
+test_ang_deg = -fov_deg : unit_ang_deg : fov_deg - unit_ang_deg;
+
+Nant = length(array_struct.eff_ch_loc);
+
+% Spectrum
+dic_mat = zeros(Nant, length(test_ang_deg));
+for ang_idx = 1 : length(test_ang_deg)
+    sv = exp(-1i * 2 * pi / array_struct.lambda_c * array_struct.eff_ch_loc.' * array_struct.unit * sind(test_ang_deg(ang_idx)));    
+    dic_mat(:, ang_idx) = sv;
+end
+
+mc_val = cal_mutual_coherence(dic_mat, 0)
+
+[N, K] = size(dic_mat); % N:dim of signal, K: # atoms in dictionary
+if (N ~= size(snapshot))
+    error('Dimension not matched');
+end
+
+%% Initializing
+x = zeros(K,1);      % coefficient (output)
+r = snapshot;        % residual of b
+omega = zeros(sparsity_val,1);  % selected support
+A_omega = [];        % corresponding columns of A
+cnt = 0;
+
+%% Iteration
+while (cnt < sparsity_val)  % choose sparsity_val atoms
+    cnt = cnt+1;
+    x_tmp = zeros(K,1);
+    inds = setdiff([1:K],omega); % iterate all columns except for the chosen ones
+    for idx = inds
+        x_tmp(idx) = dic_mat(:,idx)' * r / norm(dic_mat(:,idx)); % sol of min ||a'x-b||
+    end
+    [~, ichosen] = max(abs(x_tmp)); % choose the maximum
+    omega(cnt) = ichosen;
+    A_omega = [A_omega dic_mat(:,ichosen)];
+    x_ls = A_omega \ snapshot;  % Aomega * x_ls = b
+    r = snapshot - A_omega * x_ls; % update r
+end
+
+for idx = 1 : sparsity_val
+    x(omega(idx)) = x_ls(idx); %x_sparse(i).value;
+end
+
+P_OMP = zeros(1, K);
+P_OMP(omega) = abs(x_ls).^2;
+
+% Plot
+if plot_flag == 1
+    figure()
+    plot(test_ang_deg, (P_OMP/max(P_OMP)));
+    grid on
+    xlabel('Angle [deg]')
+    ylabel('Normalized Magnitude [linear]')
+end
+
+esti_ang_deg = test_ang_deg(omega);
+
+end