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Astronomical Data Analysis Software and Systems VII
ASP Conference Series, Vol. 145, 1998
R. Albrecht, R. N. Hook and H. A. Bushouse, e
Ö Copyright 1998 Astronomical Society of the Pacific. All rights reserved.
ds.
A Software Package for Automatic Reduction of
ISOPHOT Calibration Data
S. Huth 1,2 and B. Schulz 2
(1) Max­Planck­Institut f˜ur Astronomie, K˜onigstuhl 17, 69117
Heidelberg, Germany
(2) ISO Science Operations Center, Astrophysics Division of ESA,
Villafranca, Spain
Abstract. ISOPHOT is one of the four focal plane instruments of
the European Space Agency's (ESA) Infrared Space Observatory (ISO)
(Kessler et al. 1996), which was launched on 17 November 1995. The
impurity IR­detectors do not behave ideally but show varying responsivity
with time. Also the measured signals are a#ected by detector transients,
altering the final results considerably. We present the design and the main
features of a software package, developed in order to support the absolute
calibration of the instrument. It enables a homogeneous processing and
reprocessing of a large amount of calibration observations and provides
automatic transient correction and quality flagging. Updates to the data
processing method can be immediately applied to the full dataset.
1. Introduction
The Si or Ge based infrared (IR) detectors of ISOPHOT (Lemke, Klaas at
al. 1996) show varying relations between incident flux and measured signal
(responsivity) over the orbit of the satellite, triggered by influences like high
energy radiation impacts or changing IR­flux. Internal fine calibration sources
(FCS) provide a reproducible reference flux, that is absolutely calibrated during
the mission by comparison with known celestial standards (stars, planets, as­
teroids). The FCS signal is then used to determine the detector­responsivity at
the time of an observation. The software package presented here was developed
in order to support the absolute calibration of the FCSs, which is one of the
tasks of the Instrument Dedicated Team (IDT) in the ISO­ground­station in
Villafranca near Madrid (Spain).
2. Concept
The program was designed to allow for evaluation of a large number of ISOPHOT
calibration observations automatically and in a consistent way. Thus new devel­
opments in data processing and calibration can be accommodated easily. Imme­
diate reprocessing of the calibration database is performed without user interac­
tion. The intentional omission of a GUI helps to keep a maximum of flexibility,
212

Automatic Reduction of ISOPHOT Calibration Data 213
which is essential for this kind of work, where changes are frequent, the users
are experts and research and development go hand in hand.
The software is based on the Interactive Data Language (IDL) (Research
Systems Inc., 1992) and the PHT­Interactive Analysis (PIA) (Gabriel et al.
1997), using a simple command line driven interface. The data is processed in
units of a single measurement, e.g., data that were taken at a fixed instrument
configuration. In this context pointings within a raster are also considered to
be single measurements. Detector pixels are taken as independent units and are
processed individually. While the standard­way of PIA­processing is followed in
general, some improvements were introduced, such as non­interactive empirical
drift fitting and quality flagging. Under certain conditions, e.g., when long­term
transients are likely to influence a sequence of measurements, the full sequence
is corrected together (baseline fit).
The derived signals are then combined, guided by formatted ASCII­files,
that indicate the sequence of the di#erent targets, such as source, background or
FCS. The resulting FCS­fluxes are stored in formatted ASCII­tables, allowing
for easy examination in editors and step­by­step checking of the intermediate
values and are used as database for further research. In addition a PostScript
record of signal­diagrams is saved during processing and used in the subsequent
analysis and quality checks.
3. Automatic­drift­fit
Figure 1 shows a typical detector response after a flux­change, with a constant
flux over the following 128 seconds. The measured signal is asymptotically
drifting towards an upper limit. This non­ideal detector behaviour is observed
in intrinsic photoconductors operated at low illumination levels.
measured photocurrent
0 50 100 150
measurement time [s]
3
4
5
6
7
8
Volt/second
measured signal
fitted
curve
derived final signal
first 10%
removed
subdivision for
stability check
signal processing (staring observation)
6
5
4
3
8
7
50
0 100 150
Volts/second
measurement time [s]
Figure 1. A typical detector response after a flux change.
In order to derive the final signal the first 10% of the data is discarded, thereby
avoiding the so called hook­response, which is not described properly by tran­

214 Huth and Schulz
sient models so far (Fouks & Schubert 1995). A statistical trend­check is per­
formed on the remaining portion of the data. In case the dataset is not stable
within a confidence limit of 95%, the data is split into two parts and the test is
repeated on the latter one, until either the remaining part of the measurement
is considered to be stable or one of the following three conditions is met in the
next iteration: a) the dataset comprises less than 8 datapoints b) the dataset
comprises less than 8 seconds c) the number of iterations exceeds 5. If any of
these three conditions is met, the stability test is considered to have failed and
an empirical drift fit is tried on the full dataset with the first 10% removed. The
measurement is divided into three parts and weighted with the values 0.2, 0.8
and 1 respectively, to improve the fit convergence. Again a quality check using
criteria on the curvature is performed on the result. The limits were found em­
pirically and tuned with real data on a trial and error basis. A further check
is performed on the final signal deduced from the successful fit. The result is
rejected if the average of the last 30% of the measurement is more than a factor
of 2 di#erent from the final signal. A final signal is always rejected if negative.
In case the fit is not successful, the average of the last 30% of the data is taken
as the final signal. The outcome of the various tests, is coded in a two digit
quality flag attached to the result.
4. Baseline Fit
In the case of small signals on a large background, whole measurement sequences
can be strongly disturbed by long lasting transients. Figure 2 left shows a
sequence of measurements of a faint source on a high background. The sequence
is bounded by two measurements of the FCS, to fix the responsivity for the
baseline correction
0 200 400 600 800 1000
measurement time [s]
0.00
0.02
0.04
0.06
0.08
0.10
Volt/second bg
source
fitted baseline
2.FCS
1.FCS
source
initial drifting signal
corrected signal
bg
FCS
source
background signal
internal calibration signal
source signal
corrected baseline
bg
bg
0.10
0.08
0.06
0.04
0.02
0.00
Volts/second
0 200 400 600 800 1000
measurement time [s]
500 520 540 560 580 600 620
18
20
22
24
26
28
30
32
Backgr
flux
[MJy/sr] 1
2
average flux
500 520 540 560 580 600 620
18
20
22
24
26
28
30
32
Backgr
flux
[MJy/sr] 1
2
average flux
uncorrected
baseline corrected
day of mission
background
flux
[MJ/sr]
Figure 2. (left) Measurement sequence which is a#ected by a
longterm transient and the applied correction method (baseline cor­
rection). (right) Stability monitoring: the upper and lower plots show
fluxes derived without and with baseline correction respectively.
time of the observation. The downward drift superposed over all signals causes
strong deviations in the two FCS signals and therefore in the two calculated

Automatic Reduction of ISOPHOT Calibration Data 215
responsivities. In order to eliminate the longterm drift, an empirical drift curve
is fitted to the signals of all four background measurements. All signals are
divided by this baseline. This correction leads to a much better agreement of
individual signals measured at equal flux levels and the consistency of the finally
derived fluxes is restored. Figure 2 right shows an example of the improvements
achieved by this method. The diagrams show evaluated fluxes from a long­term
monitoring program, repeating measurements of the type described above (see
Figure 2 left) on the same source every two weeks. The two di#erent symbols
represent individual calibrations of the final background signals, using the first or
the second FCS­signal. The triangle corresponds to the first FCS measurement.
The calibrated fluxes are clearly much more consistent in the lower diagram,
where the baseline correction was applied.
5. Discussion and Future developments
The development of this software has considerably improved the data quality in
the area of ISOPHOT flux calibration, which forms a cornerstone of the overall
calibration of the instrument. As long as theoretical transient­models are only
available under certain conditions, empirical models provide a useful means to
achieve better results. The ASCII­output tables including the quality flags have
proved to be a good basis for further analysis of the data, reducing the necessity
for checking other datasets from earlier processing levels, in case questions arise.
Further improvements, except the ones coming from improved transient­models,
are corrections taking into account the actual pointing of the satellite and the
beam­profiles.
Acknowledgments. We thank our colleagues in the PIDT in VILSPA for
their valuable suggestions and support.
References
Kessler, M.F., Steinz, J.A., Anderegg, M.E., et al. 1996, A&A, 315, L27
Lemke, D., Klaas, U., et al. 1996, A&A, 315, L64
Gabriel, C., at al. 1997, in ASP Conf. Ser., Vol. 125, Astronomical Data Analysis
Software and Systems VI, ed. Gareth Hunt & H. E. Payne (San Francisco:
ASP), 108
Fouks, B., & Schubert, J. 1995, Proc. SPIE 2475, 487
IDL 1992, IDL is a registered Trademark of Research Systems, Inc. c
#1992