*-- Author : S.Burke / J.V. Morris
SUBROUTINE FKLFLT(JPL,IERR)
**********************************************************************
* *
* Kalman Filter at plane JPL using the weighted mean formalism. *
* *
* ERROR CONDITIONS; *
* IERR = 0 ; normal termination *
* -> IERR = 101 ; no projection at JPL - filter terminated *
* IERR = 5 ; filtering at JPL already done - but continue *
* -> IERR = 107 ; failure to invert measurement covariance *
* -> IERR = 111 ; failure to invert filtered covariance *
* IERR = 12 ; covariance of filtered residuals n.p.d. *
* -> IERR = 116 ; theta > pi/2: reset to pi/4 *
* IERR = 17 ; theta > 1 (warning) *
* *
* -> Fatal errors *
* *
* NB Error 12 is not considered fatal, but the chi-sq will be zero *
* *
**********************************************************************
*KEEP,FKECODE.
*KEND.
*
* Common block definitions
*
*KEEP,FKNPL.
*
* Per-track values can go in H1WORK; note that LTRUE and LFIRST must
* be set at least per event.
*
* This is about 36k words long; the remaining common blocks are
* about 3.6k in total. Some of this could be in /H1WORK/, but the
* blocks would have to be reorganised.
*
* /FKPROJ/
* /FKFILT/
* /FKSMTH/
* /FKINT/
* /FKRSID/
* /FKTRUE/
* /FKDBG/
*KEEP,FKMEAS.
*KEEP,FKFLAG.
*KEEP,FKPROJ.
*KEEP,FKFILT.
*KEEP,FKRSID.
*KEND.
**********************************************************************
*
* Local arrays ...
*
**********************************************************************
*
* Initialisation and checks ...
*
* has projection to JPL been done ...... if not, terminate!
CALL FKERR(IUTIL,IROUT,IFATAL,IINF1,IERR)
* Has filtering already been done at this plane? Continue anyway .... !?
IF (LFIL(JPL)) CALL FKERR(IUTIL,IROUT,IWARN,IDONE,IERR)
**********************************************************************
*
* If no measurement has been made at JPL, then the filtered vector and
* its covariance are the same as the projected vector and covariance.
* The residuals, covariances and chi-squared are set to zero. This is
* not strictly necessary, but it makes things neater.
*
CALL UCOPY(SPRO(1,JPL),SFIL(1,JPL),10)
CALL FKCOPY(CPRO(1,1,JPL),CFIL(1,1,JPL))
CALL VZERO(RPRO(1,JPL),4)
CALL VZERO(CRPRO(1,1,JPL),8)
CALL VZERO(RFIL(1,JPL),4)
CALL VZERO(CRFIL(1,1,JPL),8)
**********************************************************************
* Invert CMES
CALL FKINV(MES(JPL),CMES(1,1,JPL),GMES,IFAIL)
CALL FKERR(IUTIL,IROUT,IFATAL,IMCV,IERR)
* Compute the filtered (weighted average) covariance
CALL FKCOVP(CPRO(1,1,JPL),HMES(1,1,JPL),GMES,
CALL FKCOVR(CPRO(1,1,JPL),HMES(1,1,JPL),GMES,
CALL FKERR(IUTIL,IROUT,IFATAL,IOCV,IERR)
* Compute the filtered state vector
CALL FKWMES(MES(JPL),HMES(1,1,JPL),GMES,WMES(1,JPL),HGW)
CALL FKWVEC(SPRO(1,JPL),WT,CFIL(1,1,JPL),HGW,SFIL(1,JPL))
CALL FKNORM(SFIL(1,JPL),IFAIL)
IF (IFAIL.NE.0) CALL FKERR(IUTIL,IROUT,IFAIL/100,IFAIL,IERR)
* Calculate the residuals of the prediction
IF (LRPRO) CALL FKLRSD(JPL,SPRO(1,JPL),CPRO(1,1,JPL),2,
* Calculate the filtered residuals
CALL FKLRSD(JPL,SFIL(1,JPL),CFIL(1,1,JPL),-3,
IF (IFAIL.NE.0) CALL FKERR(IUTIL,IROUT,IWARN,IFAIL,IERR)
* Set the flag to show filter has been done
*