Matlab实现MVDR算法与认知的MVDR算法

clc; clear; close all num=10; %% 阵元数 k=1000; %%采样点数 as=0; %期望方向 ai=[-5 15]; %%干扰方向 e_position=[0:num-1]'; aa=90*[-1:0.001:1]; %%角度扫描范围 vs=exp(j*pi*e_position*sin(as/180*pi)); %信号导向矢量 vi=exp(j*pi*e_position*sin(ai/180*pi)); %干扰导向矢量 v=exp(j*pi*e_position*sin(aa/180*pi)); %全空间的导向矢量 f=15000; %信号频率 fi=[14000 21000 ]'; t=[0:1:k-1]/1000; snr=5; inr=20; B=zeros( size( aa ) ) ; Bop2=zeros( size( aa ) ) ; RPT=100; %脉冲重复时间 for r_ = 1 : RPT xs=diag(sqrt(2)*10.^(snr/20))*vs*exp(j*2*pi*f*t); %信号 xi=diag(sqrt(2)*10.^(inr/20))*vi*exp(j*2*pi*fi*t); %干扰 xw=[randn(num,k)+j*randn(num,k)]; %噪声 % w=1/num*vs; % figure(1),plot(aa,20*log10(abs(w'*v))); % axis([-90 90 -50 0]); % xlabel('degree'); % ylabel('dB'); % grid on % hold on xn=xs+xi+xw; %接收信号 sn=xn*xn'/k; %协方差矩阵 w=sn\vs/(vs'/sn*vs); for i=1:2 wop2=(vi(:,i)'*inv(sn)*vi(:,i)*inv(sn)*vs-vi(:,i)'*inv(sn)*vs*inv(sn)*vi(:,i))/(vs'*inv(sn)*vs*vi(:,i)'*inv(sn)*vi(:,i)-vs'*inv(sn)*vi(:,i)*vi(:,i)'*inv(sn)*vs); end B=(w'*v)+B; Bop2=(wop2'*v)+Bop2; end B=20 * log10(abs(B)/RPT) ; Bop2=20 * log10(abs(Bop2)/RPT ); % B=w'*v; % Bop2=wop2'*v; % B=20 * log10(abs(B)) ; % Bop2=20 * log10(abs(Bop2)); figure(1) plot(aa,B) hold on plot(aa,Bop2,'r:','linewidth' ,2); grid on % for i_ = 1 : length(as ) % plot( as( i_ ) * [ 1 , 1 ] , [ 0 , - 50 ] , 'b-.' ) % plot( as( i_ ) , - snr( i_ ) , 'rp' , 'linewidth' , 2 ) % end for i_ = 1 : length(ai) plot( ai( i_ ) * [ 1 , 1 ] , [ 0 , - 50 ] , 'm--' ) end % axis([-100 100 -70 10]); xlabel( '\theta ( ^o ) ' ) ylabel( 'Power Response ( dB )' ) legend( 'MVDR' , 'Cognitive MVDR' ) title('MVDR Beampattern,snr=25,inr=35')