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https://github.com/saitohirga/WSJT-X.git
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146 lines
3.8 KiB
Fortran
146 lines
3.8 KiB
Fortran
subroutine syncft4(iwave,nfa,nfb,syncmin,nfqso,maxcand,s,candidate, &
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ncand,sbase)
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include 'ft4_params.f90'
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! Search over +/- 2.5s relative to 0.5s TX start time.
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parameter (JZ=20)
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complex cx(0:NH1)
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real s(NH1,NHSYM)
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real savg(NH1)
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real sbase(NH1)
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real x(NFFT1)
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real sync2d(NH1,-JZ:JZ)
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real red(NH1)
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real candidate0(3,maxcand)
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real candidate(3,maxcand)
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real dd(NMAX)
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integer jpeak(NH1)
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integer indx(NH1)
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integer ii(1)
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integer*2 iwave(NMAX)
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integer icos4(0:3)
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data icos4/0,1,3,2/ !Costas 4x4 tone pattern
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equivalence (x,cx)
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dd=iwave/1e3
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! Compute symbol spectra, stepping by NSTEP steps.
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savg=0.
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tstep=NSTEP/12000.0
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df=12000.0/NFFT1 !3.125 Hz
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fac=1.0/300.0
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do j=1,NHSYM
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ia=(j-1)*NSTEP + 1
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ib=ia+NSPS-1
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x(1:NSPS)=fac*dd(ia:ib)
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x(NSPS+1:)=0.
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call four2a(x,NFFT1,1,-1,0) !r2c FFT
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do i=1,NH1
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s(i,j)=real(cx(i))**2 + aimag(cx(i))**2
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enddo
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savg=savg + s(1:NH1,j) !Average spectrum
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enddo
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call baseline(savg,nfa,nfb,sbase)
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ia=max(1,nint(nfa/df))
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ib=nint(nfb/df)
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nssy=NSPS/NSTEP ! # steps per symbol
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nfos=NFFT1/NSPS ! # frequency bin oversampling factor
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jstrt=0.25/tstep
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candidate0=0.
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k=0
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do i=ia,ib
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do j=-JZ,+JZ
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ta=0.
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tb=0.
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tc=0.
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t0a=0.
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t0b=0.
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t0c=0.
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do n=0,3
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m=j+jstrt+nssy*n
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if(m.ge.1.and.m.le.NHSYM) then
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ta=ta + s(i+nfos*icos4(n),m)
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t0a=t0a + sum(s(i:i+nfos*3:nfos,m))
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endif
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tb=tb + s(i+nfos*icos4(n),m+nssy*36)
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t0b=t0b + sum(s(i:i+nfos*3:nfos,m+nssy*36))
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if(m+nssy*72.le.NHSYM) then
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tc=tc + s(i+nfos*icos4(n),m+nssy*72)
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t0c=t0c + sum(s(i:i+nfos*3:nfos,m+nssy*72))
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endif
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enddo
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t=ta+tb+tc
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t0=t0a+t0b+t0c
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t0=(t0-t)/3.0
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sync_abc=t/t0
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t=tb+tc
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t0=t0b+t0c
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t0=(t0-t)/3.0
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sync_bc=t/t0
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sync2d(i,j)=max(sync_abc,sync_bc)
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enddo
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enddo
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red=0.
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do i=ia,ib
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ii=maxloc(sync2d(i,-JZ:JZ)) - 1 - JZ
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j0=ii(1)
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jpeak(i)=j0
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red(i)=sync2d(i,j0)
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enddo
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iz=ib-ia+1
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call indexx(red(ia:ib),iz,indx)
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ibase=indx(nint(0.40*iz)) - 1 + ia
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if(ibase.lt.1) ibase=1
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if(ibase.gt.nh1) ibase=nh1
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base=red(ibase)
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red=red/base
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do i=1,min(maxcand,iz)
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n=ia + indx(iz+1-i) - 1
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if(red(n).lt.syncmin.or.isnan(red(n)).or.k.eq.maxcand) exit
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k=k+1
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! candidate0(1,k)=n*df+37.5*1.5
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candidate0(1,k)=n*df
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candidate0(2,k)=(jpeak(n)-1)*tstep
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candidate0(3,k)=red(n)
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enddo
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ncand=k
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! Put nfqso at top of list, and save only the best of near-dupe freqs.
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do i=1,ncand
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if(abs(candidate0(1,i)-nfqso).lt.10.0) candidate0(1,i)=-candidate0(1,i)
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if(i.ge.2) then
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do j=1,i-1
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fdiff=abs(candidate0(1,i))-abs(candidate0(1,j))
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if(abs(fdiff).lt.4.0) then
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if(candidate0(3,i).ge.candidate0(3,j)) candidate0(3,j)=0.
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if(candidate0(3,i).lt.candidate0(3,j)) candidate0(3,i)=0.
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endif
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enddo
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endif
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enddo
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fac=20.0/maxval(s)
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s=fac*s
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! Sort by sync
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! call indexx(candidate0(3,1:ncand),ncand,indx)
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! Sort by frequency
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call indexx(candidate0(1,1:ncand),ncand,indx)
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k=1
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! do i=ncand,1,-1
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do i=1,ncand
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j=indx(i)
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! if( candidate0(3,j) .ge. syncmin .and. candidate0(2,j).ge.-1.5 ) then
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if( candidate0(3,j) .ge. syncmin ) then
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candidate(2:3,k)=candidate0(2:3,j)
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candidate(1,k)=abs(candidate0(1,j))
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k=k+1
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endif
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enddo
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ncand=k-1
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return
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end subroutine syncft4
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