signal_noise_gauss.m

三种DOA方法：经典的MUSIC,前后向空间平滑和改进的空间平滑算法

   %产生复高斯信号源signal与复高斯噪声noise的函数
   function   [signal_gauss,noise_gauss_complex]=signal_noise_gauss(antenna_number,signal_number,samplepoint_number,SNR,signal_frequency,sample_frequency)
               %生成高斯噪声
               sigma_noise=1;
               noise_gauss=normrnd(0,sigma_noise,antenna_number,samplepoint_number);
               %生成复高斯型信号源
               sigma_signal=sigma_noise*10.^(SNR/20);
               for  row_signal=1:signal_number
                    for column_signal=1:samplepoint_number;
                         p1=rand(1,1);
                         p2=rand(1,1);
                         signal_gauss(row_signal,column_signal)=(sqrt(-2*sigma_signal(row_signal)^2*log(p1))*exp(j*(2*pi*p2)))/sqrt(2);
                    end 
               end
   %生成复高斯型噪声noise
               for  row_noise=1:antenna_number
                    for column_noise=1:samplepoint_number;
                         p3=rand(1,1);
                         p4=rand(1,1);
                         noise_gauss_real(row_noise,column_noise)=sqrt(-2*sigma_noise^2*log(p3))*cos(2*pi*p4);
                         noise_gauss_imag(row_noise,column_noise)=sqrt(-2*sigma_noise^2*log(p3))*sin(2*pi*p4);
                         noise_gauss_complex(row_noise,column_noise)=(noise_gauss_real(row_noise,column_noise)+j*noise_gauss_imag(row_noise,column_noise))/sqrt(2);
                    end 
               end