📄 madsen.m
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%This function estimate the fdc with the Madsen method, based on the
%statistic of the signs of I and Q, hypotized independent gaussians with zero mean.
%The components I and Q selected are relative to an estimation window,
%which is a matrix 2*wx x wr (respectively byte in range and pulses in azimuth)
%The author suggests to select k=1, because R0_h(k) tends to zero very
%fast when abs(k) increases.
function [fdc]=Madsen(window,k,PRF)
PRT=1./PRF;
%[twowr,wx]=size(window);
[wr,wx]=size(window);
%wr=twowr/2;
for j=1:1:wx % wx azimuth complex samples
for i=1:1:wr % wr range complex sample
if real(window(i,j))>=0% window(2*i-1,j)>=0
I(i,j)=1;
else I(i,j)=-1;
end
end
end % I is a matrix wr x wx, containing the phase elements
for j=1:1:wx
for i=1:1:wr
if imag(window(i,j))>=0% window(2*i,j)>=0
Q(i,j)=1;
else Q(i,j)=-1;
end
end
end % Q is a matrix wr x wx, containing the quadrature elements
II=0;
QQ=0;
IQ=0;
QI=0;
%Estimation of the mean value of the correlation between azimuth lines (between the columns of I and Q), that
%are far from them of k pulses.
for j=1:1:(wx-k)
for i=1:1:wr
II=II+I(i,j+k).*I(i,j);
QQ=QQ+Q(i,j+k).*Q(i,j);
IQ=IQ+I(i,j+k).*Q(i,j);
QI=QI+Q(i,j+k).*I(i,j);
end
end
R_II=II/(wr*(wx-1)); % autocorrelation function of I
R_QQ=QQ/(wr*(wx-1)); % autocorrelation function of Q
R_IQ=IQ/(wr*(wx-1)); % correlation function of I and Q
R_QI=QI/(wr*(wx-1)); % correlation function of Q and I
RO_II=sin((pi/2)*R_II); % autocorrelation coefficient of I
RO_QQ=sin((pi/2)*R_QQ); % autocorrelation coefficient of Q
RO_IQ=sin((pi/2)*R_IQ); % autocorrelation coefficient of I and Q
RO_QI=sin((pi/2)*R_QI); % autocorrelation coefficient of Q and I
%complex correlation coefficient
RO_hre=0.5*(RO_II+RO_QQ);
RO_him=0.5*(RO_QI-RO_IQ);
RO_h=complex(RO_hre,RO_him);% RO_h=0.5.*(RO_hre+i*(RO_him))
fdc=angle(RO_h)/(2*pi*k*PRT);% The maximum value non-ambiguous of the correlation function R_xy is deltafdc_amb=1/k*PRT=PRF/k
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