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A.2.2.5 PSF Modeling

The estimate of the contamination of IOR and halation-ramp region fluxes by illumination from the spectral orders proceeds in two steps. Information from the PSF model and from the echelle order fluxes is not used in the first step, nor is a halation overlap region defined. The solution in this ``Step 1" of Pass 1 is determined entirely from a Chebyshev interpolation from points in the end (non-IOR) regions of the swath. In the presence of certain image pathologies (Section A.2.4), as well as the first and last few Pass 1 swaths, this Step 1 is the only step; it becomes the final solution for the Pass 1 phase.

For the great majority of Pass 1 swaths, i.e. those passing through the middle of the camera image and not encountering poor statistical solutions, BCKGRD continues with a Step 2. This step uses the solution from Step 1 as a starting point to compute a PSF-compensated solution in which we attempt to subtract from the measured interorder fluxes the contamination from adjacent orders. As can be inferred from Figure A.3, the correction for this overlap can be determined by the simple relation:

\begin{displaymath}
Flux_{corr} = Order Height ~\times~ 2PSF_{1}/[1 - 2(PSF_{1} - PSF_{2})], \end{displaymath}

where Fluxcorr and Order Height are given in FN flux units per pixel and PSF1 and PSF2 are given as a fraction of the true local order height. Step 2 concludes by subtracting Fluxcorr from the local measured background at each interorder location and refitting a new Chebyshev solution through the adjusted Pass 1 swath values. Note particularly that in NEWSIPS an explicit effort is made to compensate for the contamination of the it interorder fluxes (i.e., the background fluxes) in the manner described above, there is no adjustment made to correct the on-order fluxes (gross fluxes) for the effects of overlapping orders.

BCKGRD uses the same trial spatial PSF model for all types of continuum source types in a given camera. The algorithm also assumes that the PSF is global over the image. The model was determined by replicating the accumulation of flux overlap toward short wavelength orders from a large number of actual images.

Because the PSF may actually change from image to image, the algorithm attempts to accommodate such changes by using on-the-fly order information to refine the PSF model - specifically the slope of the $\overline{nf~nd}$ leg of the IOR triangle. This is accomplished by comparing the fractional flux overlap with the model result for a reference order within the IOR, that is by comparing the increase in overlap for this order to the overlap found at the start of the IOR (pixel nd). If the measured and model slopes agree within a tolerance factor (1.5 ×), the program adopts the measured slope and scales the model PSF accordingly. Otherwise, the model PSF is used. Tests show that various Pass 1 swaths for a given image can either pass or fail this tolerance test independently.


next up previous contents
Next: A.2.2.6 Post-Solution Pathology Tests Up: A.2.2 Pass 1: Cross-Dispersion Previous: A.2.2.4 On-the-Fly Pathology Screening
Karen Levay
12/4/1997