A Position Mode observing program uses the FGS to derive the relative angular
separations of several objects distributed across an astrometric field. In traditional astrometry, images of objects are recorded simultaneously onto a photographic plate, and the plate is later analyzed to determine the relative separations of the objects. Astrometry with the FGS, by contrast, proceeds in the reverse order; the positions of the individual objects are found first, and then a virtual plate is constructed with the help of data from the guide stars and check stars.
Both approaches must deal with optical field angle distortions, lateral color shifts,
and plate scales. However, FGS measurements are far more vulnerable to temporal variations that might occur during the observing sequence. The challenge is to assemble an astrometric plate by defining a common but arbitrary coordinate system onto which the individual observations are mapped. Observers must assume that the telescope’s yaw, pitch, and roll might be slightly different for each observation, causing the sky to wobble about in FGS1r’s detector space. Such motions can be detected and eliminated using guide star data and check star measurements. Corrections based on guide star data are referred to as Position Mode dejittering
, and those based on check star data are called drift corrections
. Here we discuss the errors associated with each procedure.
During a nominal FGS visit, two FGSs guide the telescope, tracking their guide
stars in FineLock, while the third sequentially measures the positions of the astrometry targets in detector space. The pointing control system uses one of the guide stars, called the dominant guide star, to minimize unintended translation of HST’s optical axis across sky. It uses the other, called the roll star, to control the rotation of the focal plane. The section “Preparing the Output Products of CALFGSB for Gaussfit”
in Chapter 4
, decribes how the Position Mode pipeline accounts for spacecraft jitter during a visit by mapping all observations into the frame defined by the guide star centroids during the first observation.
The adjustments to the astrometry centroids from this Position Mode dejittering
correction are typically about 1 mas. However, the corrections occasionally can be as large as 5 mas for one or two observations of a visit. These large corrections arise most frequently when orbital day-to-night or night-to-day transitions excite HST’s vibrational modes. During such events the residuals depend upon the amplitudes of these excited modes but are estimated to be typically about 1 mas. During quiet times, the residual of this correction is about +/– 0.3 mas.
Astrometry targets observed multiple times per visit typically drift across the FGS
by about 2 to 7 mas when two FGSs guide the telescope and by up to 70 mas with only one FGS guiding. Because astrometry observations execute sequentially, the resulting errors in the measured angular separations between objects increase as the time between the measurements lengthens. The pipeline must then remove an effect that is typically 4 and not infrequently up to 25 times the overall astrometry error budget (2.7 mas).
To remove this drift, the calibration pipeline applies a model derived from the
check star data to all the observations in the visit. The residuals from this correction are difficult to quantify in the usual way because the standard deviation of the data from a fit means little if only three to five points determine the fit. On the other hand, the success of the drift correction is clearly demonstrated by comparing the residuals of two plate overlays, one where the individual visits are drift corrected, the other where they are not. Provided adequate check star data are available to generate a reliable model, plates with the drift correction applied correlate well, typically with 2 mas rms residuals. At minimum, two check stars should be observed three times each. Residuals between those same visits without drift correction range up to 15 mas rms.
The first two models are translational only. The third model requires more than one
check star and is unreliable if there are not enough visits to any given check star. The pipeline applies all three algorithms, where applicable, and computes chi squares and degrees of freedom for each result. The observer should review these data to determine which result is best suited for further data processing. Experience has shown that often one cannot determine which drift model is best until data from several visits are compared and the plate overlay residuals are evaluated.