xinhaochuli.rar_阵列接收

close all; clear all; clc; Ne = 10; %no of elements Ni = 2; %no of interferences sig_ang = 100; %desired doa/real signal doa int_ang = [110 140]; %interference doas sig_array = steering_vector(sig_ang,Ne); L = 10; SNR = 10; %signal powers SIR = [20 20]; %interference powers noise_var = 1; %noise variance Ns = 10000; %no of snapshots signal_power = 10.^(SNR/10); %recevied signals of the sensors-----------x_matrix signal = sqrt(signal_power).*randn(1,Ns); %the souces int_matrix = zeros(Ne,Ns); %the interfers for i = 1 : 1 : Ni int_power = 10.^(SIR(i)/10); interfer = sqrt(int_power).*randn(1,Ns); int_array = steering_vector(int_ang(i),Ne); int_matrix = int_matrix + int_array*interfer; end noi_matrix = zeros(Ne,Ns); noi_matrix = sqrt(noise_var).*randn(Ne,Ns); x_matrix = zeros(Ne,Ns); x_matrix = sig_array*signal + noi_matrix + int_matrix; s_matrix = sig_array*signal; in_matrix = noi_matrix + int_matrix; R = zeros(Ne,Ne); Rin = (in_matrix*in_matrix')/Ns; Rs = (s_matrix*s_matrix')/Ns; %两种计算方法一样，存在误差 R = (x_matrix*x_matrix')/Ns; %SMI beamformer % cvx_begin quiet % variable w_smi(Ne) complex; %定义的变量都是列向量 % minimize(w_smi'*(R)*w_smi); % subject to % w_smi'*sig_array == 1; % cvx_end w_smi = inv(R)* steering_vector(sig_ang , Ne) / ( (steering_vector(sig_ang,Ne))'*inv(R)*steering_vector(sig_ang,Ne) ); theta_range = [0:1:180]; for theta_i = 1:1:length(theta_range) bp(theta_i)=10*log10(abs(w_smi'*(steering_vector(theta_range(theta_i),Ne)))); end plot(theta_range,bp,'k'); %steering_vector是testsmi的子程序