ee.rar_CDMA DOA_DoA beamforming_ee_智能天线 doa_波束赋形

% This is a simulation to model the Elam SDMA technique % Developed by Frank B. Gross, November 11, 2004 % define the sample baseband modulation initially as a 1kHz phase modulation tone % WALSH FUNCTIONS WORK BETTER THAN PN SEQUENCES % Can also use Gold codes f=1E3; T=1/(4*f); Nchips=64; tend=20*Nchips; t=[0:(tend-1)]*T/(tend-1); m=sin(2*pi*f*t); % modulation m m=zeros(1,length(m)); % plot array factor for linear array N=11; % number of receive elements to give 10 degree beamwidth d=.5; % spacing in wavelengths between adjacent array elements theta=0:.01:pi; % generate pseudo-random 50 chip codes T long to modulate the % received signals from each antenna binary % generate the N pseudo-noise binary codes test=-30*pi/180; test=0; test2=45*pi/180; Vr=zeros(181,length(t)); Vr2=zeros(181,length(t)); er=zeros(181,length(t)); for k=1:181; an(k)=(k-1)-90; th(k)=an(k)*pi/180; % calculate the actual received signal for each angle using the N=11 element % receiver and sum all N signals. for i=1:N Vr(k,:)=Vr(k,:)+exp(1j*(m+2*pi*(i-1)*d*sin(test)+codes(i,:))); % create combined signal at angle j Vr2(k,:)=Vr2(k,:)+exp(1j*(m+2*pi*(i-1)*d*sin(test2)+codes(i,:))); er(k,:)=er(k,:)+exp(1j*(2*pi*(i-1)*d*sin(th(k))+codes(i,:))); end %Vr(k,:)=Vr(k,:)+Vr2(k,:); R1(k)=sum(Vr(k,:).*er(k,:)); R2(k)=sum(Vr(k,:).*conj(er(k,:))); %phase1(k,:)=unwrap(angle(Vr(k,:).*conj(er(k,:)))); %phase2(k,:)=unwrap(angle(Vr(k,:).*(er(k,:)))); phase1(k,:)=unwrap(angle(R1(k))); phase2(k,:)=unwrap(angle(R2(k))); end AF=sin(N*pi*d*(sin(th)-sin(test)))./(N*sin(pi*d*(sin(th)-sin(test)))); maxAF=max(abs(AF)); maxR2=max(abs(R2)); maxR1=max(abs(R1)); figure; plot(an,abs(R2)/maxR2,'k',an,abs(AF),'k:') xlabel('\theta') ylabel('Correlation Magnitude') title('N=20 elements, d=\lambda/2, Nchips=64') axis([-90 90 0 1]) grid on %title('correlation comparison \theta_k =45^0') %legend('correlation') %figure; %plot(t,m,'k',t,phase1(46,:),'k:',t,phase2(46,:),'k-.') %xlabel('t') %ylabel('phase') %title('comparison of instantaneous and averaged phases') %legend('phase m(t)','avg w/o conjugate','avg with conjugate')