minimize.m

rang doppler imaging and motion compensation中的源代码

     function [beq, spol] = minimize(x0,data,smat,emat,tt,tint,sizemat,bc,bt);
     %
     % Find the polynomial estimates where the focal quality
     % indicator is minimum. In this algorithm, the weighted
     % least squares combined with complex analysis method
     % is used as focal quality indicator.
     %
     
     matcomp=motioncomp(data,x0,tt,bc);
     [mm,nn]=size(matcomp);
     
     cenerc=[];
     dds=[];
     
     for bcount=1:mm 
     daburst=matcomp(bcount,:);
     cfind=max(find(emat(bcount,:)));
     cenerb=[];
     dslope=[];
     for cnum=1:cfind
     cstartend=smat(bcount,cnum):emat(bcount,cnum);
     cslope=daburst(cstartend);
     ccslope=abs(cslope);
     sumcsl=sum(ccslope);
     cenerb=[cenerb;sumcsl];
     dslmean=gradient5(cslope);
     dslope=[dslope;dslmean];
     end
     cenerc=[cenerc;cenerb];
     dds=[dds;dslope];
     end
     ddss=dds*22.00158;
     cenercc=cenerc.^2;
   
    midtime=tint*((smat+emat)/2-1);
    findtime = midtime > 0;
    btmat=(bt*ones(1,sizemat)+midtime).*double(findtime);
    btmatt=btmat.';
    nonzvec=nonzeros(btmatt);    
    polyestim=wls(nonzvec,ddss,cenercc,2);
    spol1=2*polyestim(1);
    spol2=polyestim(2);
    enpoly=sqrt(spol2^2+spol1^2);
    spol=[spol2;spol1];   
    beq=enpoly;