diff --git a/MLEstimators/COMET_2D.m b/MLEstimators/COMET_2D.m index 157b11daf2c8268d47c18eb4231a42d54ee92b7c..71c19775c61a75ef539a2d318085d1c2bfa06f9b 100644 --- a/MLEstimators/COMET_2D.m +++ b/MLEstimators/COMET_2D.m @@ -73,23 +73,4 @@ linInd = find(Spec_est==pos2DInd); DOA_est = [Grid(jOpt); Grid(iOpt)]; Spec_est(indGrid) = Spec_vec; Spec_est = Spec_est + Spec_est'; -% -% Spec_est = zeros(NGrid, NGrid); -% for (iGrid = 1:NGrid-1) -% for (jGrid = iGrid+1:NGrid-1) -% a1Ha2 = AHA(iGrid, jGrid); -% a1HRa1 = real(AHRA(iGrid, iGrid)); -% a2HRa2 = real(AHRA(jGrid, jGrid)); -% a2HRa1 = AHRA(jGrid, iGrid); -% Spec_est(iGrid, jGrid) = 1/(NAnt^2 - abs(a1Ha2)^2)*(NAnt*(a1HRa1 + a2HRa2)-2*real(a1Ha2*a2HRa1)); -% end -% end -% toc -% figure -% imagesc(Spec_est) -% Search for the global maximum and estimated DOAs -% [~, linInd] = min(1./Spec_est(:)); -% [iOpt, jOpt] = ind2sub(NGrid, linInd); -% DOA_est = [Grid(iOpt); Grid(jOpt)]; - end \ No newline at end of file diff --git a/MLEstimators/DML_2D_v2.m b/MLEstimators/DML_2D.m similarity index 91% rename from MLEstimators/DML_2D_v2.m rename to MLEstimators/DML_2D.m index a85d01bd8759abbb440de3c62a4d115f02aac5ba..6a33affee0f198774a432babec4a62503cb5cb19 100644 --- a/MLEstimators/DML_2D_v2.m +++ b/MLEstimators/DML_2D.m @@ -1,5 +1,5 @@ -function [ DOA_est, Spec_est] = DML_2D_v2( Y, NSrc, Grid, AGrid, varargin ) -%DML_2D_v2 returns the estimated DOAs and the corresponding 2D matrix +function [ DOA_est, Spec_est] = DML_2D( Y, NSrc, Grid, AGrid, varargin ) +%DML_2D returns the estimated DOAs and the corresponding 2D matrix %containing the value of the DML function in the case of two source %signals. In this function, simple nested for-loops are used to search for %the global minimum. The cost function of DML for two source signals are diff --git a/MLEstimators/SML_2D.m b/MLEstimators/SML_2D.m index 251304089ea96f6f73dd07511a83ff51484f3ac1..2eab3b030c41b1be63da8257b0f203fc75a49628 100644 --- a/MLEstimators/SML_2D.m +++ b/MLEstimators/SML_2D.m @@ -1,6 +1,6 @@ function [ DOA_est, Spec_est] = SML_2D( Y, NSrc, Grid, AGrid, varargin ) -%DML_2D returns the estimated DOAs and the corresponding 2D matrix -%containing the value of the DML function in the case of two source +%SML_2D returns the estimated DOAs and the corresponding 2D matrix +%containing the value of the SML function in the case of two source %signals. In this function, simple nested for-loops are used to search for %the global minimum % diff --git a/MLEstimators/WSF_2D_v2.m b/MLEstimators/WSF_2D.m similarity index 93% rename from MLEstimators/WSF_2D_v2.m rename to MLEstimators/WSF_2D.m index 5583e2340e5d1812418fa2f5bf446d36f6fa0c4e..234873aa85be2f02bf1169098bb79fc1ca8f5542 100644 --- a/MLEstimators/WSF_2D_v2.m +++ b/MLEstimators/WSF_2D.m @@ -1,5 +1,5 @@ -function [ DOA_est, Spec_est] = WSF_2D_v2( Y, NSrc, Grid, AGrid, varargin ) -%WSF_2D_v2 returns the estimated DOAs and the corresponding 2D matrix +function [ DOA_est, Spec_est] = WSF_2D( Y, NSrc, Grid, AGrid, varargin ) +%WSF_2D returns the estimated DOAs and the corresponding 2D matrix %containing the value of the WSF function in the case of two source %signals. In this function, simple nested for-loops are used to search for %the global minimum. The cost function of DML for two source signals are