mirror of
https://github.com/saitohirga/WSJT-X.git
synced 2024-11-22 20:28:42 -05:00
34f8924cfc
This merge brings the WSPR feature development into the main line ready for release in a future v1.6 release. git-svn-id: svn+ssh://svn.code.sf.net/p/wsjt/wsjt/branches/wsjtx@5424 ab8295b8-cf94-4d9e-aec4-7959e3be5d79
143 lines
3.6 KiB
Fortran
143 lines
3.6 KiB
Fortran
subroutine timf2(x0,k,nfft,nwindow,nb,peaklimit,x1, &
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slimit,lstrong,px,nzap)
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! Sequential processing of time-domain I/Q data, using Linrad-like
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! "first FFT" and "first backward FFT", treating frequencies with
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! strong signals differently. Noise blanking is applied to weak
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! signals only.
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! x0 - real input data
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! nfft - length of FFTs
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! nwindow - 0 for no window, 2 for sin^2 window
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! x1 - real output data
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! Non-windowed processing means no overlap, so kstep=nfft.
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! Sin^2 window has 50% overlap, kstep=nfft/2.
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! Frequencies with strong signals are identified and separated. Back
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! transforms are done separately for weak and strong signals, so that
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! noise blanking can be applied to the weak-signal portion. Strong and
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! weak are finally re-combined, in the time domain.
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parameter (MAXFFT=1024,MAXNH=MAXFFT/2)
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parameter (MAXSIGS=100)
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real x0(0:nfft-1),x1(0:nfft-1)
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real x(0:MAXFFT-1),xw(0:MAXFFT-1),xs(0:MAXFFT-1)
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real xwov(0:MAXNH-1),xsov(0:MAXNH-1)
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complex cx(0:MAXFFT-1),cxt(0:MAXFFT-1)
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complex cxs(0:MAXFFT-1) !Strong signals
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complex cxw(0:MAXFFT-1) !Weak signals
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real*4 w(0:MAXFFT-1)
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real*4 s(0:MAXNH)
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logical*1 lstrong(0:MAXNH),lprev
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integer ia(MAXSIGS),ib(MAXSIGS)
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logical first
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equivalence (x,cx),(xw,cxw),(xs,cxs)
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data first/.true./
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data k0/99999999/
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save
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if(first) then
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pi=4.0*atan(1.0)
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do i=0,nfft-1
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w(i)=(sin(i*pi/nfft))**2
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enddo
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s=0.
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nh=nfft/2
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kstep=nfft
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if(nwindow.eq.2) kstep=nh
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fac=1.0/nfft
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slimit=1.e30
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first=.false.
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endif
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if(k.lt.k0) then
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xsov=0.
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xwov=0.
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endif
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k0=k
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x(0:nfft-1)=x0
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if(nwindow.eq.2) x(0:nfft-1)=w(0:nfft-1)*x(0:nfft-1)
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call four2a(x,nfft,1,-1,0) !First forward FFT, r2c
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cxt(0:nh)=cx(0:nh)
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! Identify frequencies with strong signals.
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do i=0,nh
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p=real(cxt(i))**2 + aimag(cxt(i))**2
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s(i)=p
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enddo
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ave=sum(s(0:nh))/nh
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lstrong(0:nh)=s(0:nh).gt.10.0*ave
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nsigs=0
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lprev=.false.
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iwid=1
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ib=-99
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do i=0,nh
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if(lstrong(i) .and. (.not.lprev)) then
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if(nsigs.lt.MAXSIGS) nsigs=nsigs+1
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ia(nsigs)=i-iwid
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if(ia(nsigs).lt.0) ia(nsigs)=0
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endif
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if(.not.lstrong(i) .and. lprev) then
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ib(nsigs)=i-1+iwid
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if(ib(nsigs).gt.nh) ib(nsigs)=nh
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endif
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lprev=lstrong(i)
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enddo
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if(nsigs.gt.0) then
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do i=1,nsigs
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ja=ia(i)
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jb=ib(i)
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if(ja.lt.0 .or. ja.gt.nh .or. jb.lt.0 .or. jb.gt.nh) then
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cycle
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endif
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if(jb.eq.-99) jb=ja + min(2*iwid,nh)
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lstrong(ja:jb)=.true.
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enddo
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endif
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! Copy frequency-domain data into array cs (strong) or cw (weak).
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do i=0,nh
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if(lstrong(i)) then
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cxs(i)=fac*cxt(i)
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cxw(i)=0.
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else
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cxw(i)=fac*cxt(i)
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cxs(i)=0.
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endif
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enddo
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call four2a(cxw,nfft,1,1,-1) !Transform weak and strong back
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call four2a(cxs,nfft,1,1,-1) !to time domain, separately (c2r)
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if(nwindow.eq.2) then
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xw(0:nh-1)=xw(0:nh-1)+xwov(0:nh-1) !Add previous segment's 2nd half
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xwov(0:nh-1)=xw(nh:nfft-1) !Save 2nd half
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xs(0:nh-1)=xs(0:nh-1)+xsov(0:nh-1) !Ditto for strong signals
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xsov(0:nh-1)=xs(nh:nfft-1)
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endif
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! Apply noise blanking to weak data
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if(nb.ne.0) then
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do i=0,kstep-1
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peak=abs(xw(i))
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if(peak.gt.peaklimit) then
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xw(i)=0.
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nzap=nzap+1
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endif
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enddo
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endif
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! Compute power levels from weak data only
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do i=0,kstep-1
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px=px + xw(i)**2
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enddo
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x1(0:kstep-1)=xw(0:kstep-1) + xs(0:kstep-1) !Recombine weak + strong
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return
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end subroutine timf2
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