cleaning3.m

rang doppler imaging and motion compensation中的源代码

   function [cleaned, indexc] = cleaning3(data,origin,mm,nn,Pfa);
 	%	
   % Cleanes the data in the spatial domain to raise
   % SNR. The noise level is estimated using Weibull
   % distribution and thrshold level is determined.
   % Linear filtering is used to clean the data.
   %


   [m n] = size(data);
   leng=length(data);
   if m ~= leng
      temp=m;
      m = n;
      n = temp ;
      data = data.';
   end

   Pfa=Pfa*10;
   nmul=16;
   numnn=nmul*m;
   d7mat=fftshift2(fft(data,numnn));
   d727c=abs(d7mat);
   vecindr=noisesect(d727c,8,4);
   [norm,fact]=normalize(vecindr);
   [weibb,weiba]=weibmen(norm);

   TQ=(abs(log(Pfa))./weiba).^(1./weibb);
   T=TQ.*fact;

   absvecd=[];
   for it = 1:n
   absve = d727c(:,it) > T(it);
   absvecd = [absvecd,absve];
   end
   mask1=medfilt2(absvecd);
   mask2=morph(mask1,0,0,3,5);
   mask=morpharea(mask2).';

   [centro,maximo]=filtindex(mask,nmul);
   indexb=(centro-(m/2+1))*2*pi/m;
   [modorig,inxc]=shiftzero(origin,indexb);
   indexd=indexb-inxc;
   if maximo <= 9
   maximo = 9;
   end

   indexc=maximo/m;  
   centm=centerm(indexd,m);
   pnum=tranfreqm(n,m);
   dtemlow=centm.*pnum;

   dlowt=(exp(-j*dtemlow).*modorig).';
   f=[0 indexc-0.03 indexc+0.03 1];
   fm=[1 1 0 0];
  
   lowcoef=remez(83,f,fm);
   dlowmat=filtfilt(lowcoef,1,dlowt);

   dlowmatt=dlowmat.';
   doriginal=dlowmatt.*exp(j*dtemlow);
   cleaned=repnan(doriginal);
%   imagesc(abs(fft(cleaned.')));
%   pause