LMS.rar_mean

clear all; close all;clc; J=sqrt(-1); source_number=3; source_doa=[20 15 -30 80]; sensor_number=9; snapshot_number=1000; A=exp(-J*(0:sensor_number-1)'*pi*sin(source_doa*pi/180)); W=zeros(sensor_number,1); M=100; for k=1:M length=2000; M1=2; M2=2; M3=2; M4=2; S1=randint(length,1,M1); S2=randint(length,1,M2);%干扰1 S3=randint(length,1,M3);%干扰2 S4=randint(length,1,M4); ps1=pskmod(S1,M1); ps2=pskmod(S2,M2); ps3=pskmod(S3,M3); ps4=pskmod(S4,M4); t=151:150+snapshot_number; s=[ps1(t), ps2(t),ps3(t),ps4(t)].'; SN1=0; %信噪比为0db SN2=0; SN3=20;%干噪比为10db SN4=30;%干噪比为10db sn=[SN1 SN2 SN3 SN4]'; noise1=randn(snapshot_number,1); noise2=randn(snapshot_number,1); noise3=randn(snapshot_number,1); noise4=randn(snapshot_number,1); ps1n=sigmerge(ps1(t),noise1,SN1); ps2n=sigmerge(ps2(t),noise2,SN2); ps3n=sigmerge(ps3(t),noise3,SN3); ps4n=sigmerge(ps4(t),noise4,SN4); S=[ps1n-noise1,ps2n-noise2,ps3n-noise3,ps4n-noise4]'; noisex=randn(sensor_number,snapshot_number)+j*randn(sensor_number,snapshot_number); X=A*S+noisex; S1=S(1,:); w1=zeros(sensor_number,1); y(1)=w1'*X(:,1); e(1)=S1(1,1)-y(1); % u(1)=0.0000002; for n=2:snapshot_number %u(n)=(e(n-1)*e(n-1))/(S1(1,n-1)*S1(1,n-1))*u(1); w1=w1+0.00000001*X(:,n-1)*conj(e(n-1));%计算1000次加权列向量，再求均值 y(n)=w1'*X(:,n); e(n)=S1(1,n)-y(n);%递推求LMS 权矢量 end W_lms(:,k)=w1; W_lms=sum(W_lms,2)/M; cc=0; for d=-pi/2:0.01:pi/2 cc=cc+1; A1(:,cc)=[exp(j*(0:sensor_number-1)*pi*sin(d))]'; f_lms(1,cc)=W_lms'*A1(:,cc); end end d=-pi/2:0.01:pi/2; d=d.*(180/pi); figure; f_lms=f_lms/abs(max(max(f_lms))); plot(d,10*log10(abs(f_lms).^2)); legend('lms'); %axis([-100 100 -70 0]); xlabel('到达角(deg)'); ylabel('阵列输出功率增益(dB)'); figure; n=2:snapshot_number; plot(n,e(n));