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			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(cx,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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