autopic2.asv

calculation of the autocorrelation peak sidelobe levels and corsscorrelation. CE sequence, frank aut

clear, close all;
sqL=10;
p=1;
L=sqL^2;
% t=0:(L-1);
S=frank_seq(sqL,L,p);

% plot(t,angle(S));

% autocorrelation_pic2(L,S,0);
% m=power_integer_2(L);
% nfft=2^(m);
nfft=2*L+1;


% sfft=fft(S,nfft);
% Ac=fftshift(abs(ifft(sfft.* conj(sfft)))/L);
% figure(1);
% time=(-(nfft/2)):1:(nfft/2-1);
% plot(time,Ac);

S=[S, zeros(1,(nfft-L))];
winid=0;
if (winid==0.)
    win(1:nfft)=1.;
    win=win';
else 
    if (winid==1.)
        win=hamming(nfft);
    else
        if(winid==2.)
            win=kaiser(nfft,pi);
        else
            if(winid==3.)
                win=hann(nfft);
            end
        end
    end
end
       
x=zeros(41,nfft);
col=0;
for fdT=0:.01:2
   col=col+1;
   for row=1:nfft
      Sr(row)=S(row)*exp(i*2.*pi*(row-1)*fdT/L);
   end
   x(col,:) = 20*log( fftshift(abs(ifft(fft(Sr).* conj(fft(S)).*win'))/L) );
end

% % test if the autocorrelation figure in the fdT=0 right matched the former Ac computered   
% figure(1);
% time=(-(nfft/2)):1:(nfft/2-1);
% plot(time,Ac);
% hold all
% plot(time,x(:,21),'--r');

time=(-(nfft/2)):1:(nfft/2-1);
fdT=0:.01:2;
% box off;
figure(1);

image(time,fdT,x,'CDataMapping','scaled');


xlabel('sample shift');
ylabel('Doppler shift fd*T');
zlabel('Autocorrelation function');
colorbar;