Automatic data processing and quality control: experiences from ISO-LWS
M. J. Burgdorfa, A. S. Harwoodb, N. R. Tramsa,
T. L. Lima, c,
S. D. Sidherb, B. M. Swinyardb and P. E. Cleggc
a. ISO Science Operations Centre, ESA Science Department,
Villafranca del Castillo, P.O. Box Apdo 50727, 28080 Madrid, Spain
b. Space Science Department, Rutherford Appleton Laboratory, Chilton,
Didcot, OX11 0QX, UK
c. Queen Mary and Westfield College, University of London, Mile End
Road, London E1 4NS, UK
(gzip-ped postscript file)
Abstract:
The high level of automation in the operation of the ESA Infrared Space
Observatory, together with high observing efficiency, leads to a requirement
for a commensurate level of automation in the subsequent processing of the
astronomical data. This inevitably means that all data for a given instrument
mode have the same calibration applied, regardless of the exact details of the
object being observed. Questions then arise about these "pipeline processed"
data in terms of the calibration accuracy achieved; how to control the quality
of data received by the observer and how much further processing is required -
or desirable - by the observer. In this paper we outline the experience of two
years of operation of the Long Wavelength Spectrometer on board ISO,
detailing the improvements made in the pipeline processing during this time
and the difficulties encountered in the automated processing of some
instrument modes.
Data processing, observatories
INTRODUCTION
The Long Wavelength Spectrometer [1] is one of two
complementary spectrometers
aboard the European Space Agency's
Infrared Space Observatory [2].
It covers the wavelength range 43 - 197 m at either medium or high
spectral resolving power. There are ten doped-Germanium photoconductors, all
of them being used simultaneously in different wavelength ranges such that a
full grating spectrum is divided into ten subspectra.
Like the other instruments on ISO, the LWS is operated in a pre-scheduled way
in order to maximize the efficiency of this observatory. This means that the
details of the observations have to be defined well in advance.
Four different Astronomical Observation Templates (AOT's) are available to
users of the LWS for entering their observations; they correspond to the basic
instrument modes: scans over a line or an extended wavelength range with the
grating or the Fabry-Perot subsystem. By means of the Proposal Generation Aids
software an astronomer assigns concrete values to the variables in these
templates (coordinates,
integration times etc.) and gets his observation into the
"Mission Database". From the pool of observations of all instruments a
timeline is built for each revolution of the satellite. The observations are
then executed by translating them into instrument command sequences which are
sent to the spacecraft. These sequences are always of the same structure for a
given AOT.
The standardization of the astronomical observations makes an automatic
processing of the generated data possible. One branch of this is the real-time
monitoring of the instruments which guarantees that none of the housekeeping
values goes out of limits unnoticed [3],
the other is the off-line processing which
generates the data products that are sent to observers on CD-ROM. In
section 2 we describe in detail the various steps of generating
these "pipeline" products and in section 3 we discuss the
modifications that became necessary from experience in flight. Subsequently
section 4 gives an overview of the possibilities to examine the
data products with LWS Interactive Analysis (LIA) and ISO Spectroscopy Analysis
Package (ISAP) routines, and we finish this
paper with a description of some instrument peculiarities which can currently
not be handled, yet, by the automatic processing.
PIPELINE PROCESSING
The automated ISO data processing for each instrument consists of three stages
(see figure 1) which are explained with the example of the LWS
in the following subchapters. The products
from each stage are sent to the observer so that he can choose at which level
to start the analysis of his data.
Figure 1:
Overview of the ISO data processing
|
Derivation of Edited Raw Data
The first step in the ISO processing is in principle the same for all
instruments: the telemetry data from the
satellite are related
to the different observations executed. For this the start and the end
of an observation and important events within like beginning and end of an
illuminator flash are identified and written to a "Compact Status History"
file. This information is then used to extract a set of Flexible Image
Transport System (FITS) binary tables with Edited Raw Data. The part of
the ERD that is common to all instruments includes housekeeping and satellite
information and has the same format for each observation whereas the
instrument specific ERD contain mainly the science data for a given
observation. The ERD are a complete set of data in a primitive form, therefore
they are not a useful starting point for
further analysis by the observer.
Derivation of Standard Processed Data
The second stage of pipeline processing converts the raw data from the
detectors into photocurrents. This is carried out via the following steps:
- Construction of ramps and discarding unusable readouts: The
detector signals are grouped into the useful time intervals between resets
of the integrating amplifiers. The periods where the instrument was changing
between modes and therefore was not in a well-defined state are discarded.
- Conversion of read-outs to voltages: A linear relationship is used to
convert the digital units of each elementary integration ramp into Volts; the
coefficients needed for that operation are read from calibration files.
- Discard saturated readouts: All voltages above a certain threshold that
is defined in a calibration file are discarded. The number of saturated
readouts is recorded in the SPD.
- First level deglitching: The recognition of glitches, i. e. sudden jumps
in output signal caused by hits of highly energetic particles, is done in
several steps. First the differences between adjacent points are calculated and
the mean and standard deviation of this set of data are determined. Those
values in the set that are further away from the mean than 3.5 standard
deviations are
checked for the typical glitch pattern in the respective readouts. Once a
candidate for a glitch event is identified, its height is calculated and
compared to the overall signal in order to recognize insignificant outliers.
The rest of an integration ramp after a (positive) glitch is discarded and
also the two following ramps.
- Extraction of ramp slopes and uncertainties: A second order polynomial is
fitted to each ramp and its slope is determined from the first and the last
point on that fit. With a linear function the slopes are then
converted into photocurrents; if a ramp has been discarded, e. g. because of a
glitch, its value is set to zero.
- Illuminator processing: Every scientific observation contains
measurements of the dark background and the signal from the internal illuminator
flashes for reference. The calculation of the photocurrents is done for them in
the same way as for the observation on the target except for a slight
difference in the deglitching algorithm.
This processing is independent of the AOT used; its product contains scientific
data, but not in astronomical units. Nevertheless it will be used by
expert users as starting point for an interactive analysis of the data, if they
want to use e. g. their own flux calibration.
Auto Analysis
Auto Analysis applies the flux and wavelength calibration to the SPD and
creates a data product in scientifically meaningful units. It performs the
following steps:
- Dark current / background straylight subtraction: The average "dark
signal" as measured before and after each astronomical observation is
subtracted from the signal of the source.
- Grating scan wavelength calibration: The positions of the grating
mechanism are converted into wavelengths by using a table in a calibration
file.
- Grating spectral responsivity calibration: As the instrumental
responsivity varies as a function of wavelength, each flux value obtained in
grating mode is corrected with the relative spectral response function of the
instrument. This correction is done by dividing the fluxes by the responsivity
values in a calibration table.
- Spectral bandwidth correction: For grating scans the flux of each
detector is divided by the FWHM spectral resolution.
- Fabry-Perot (FP) scan wavelength calibration: In order to determine the
wavelength for a Fabry-Perot scan, the mechanism position is converted into
distance between the two FP etalons. The pipeline calculates then with this
value and with the order in which the FP was operated the wavelength.
- Fabry-Perot spectral responsivity calibration: The fluxes in an FP
spectrum are divided by the responsivity values for the respective FP and
grating positions.
- Velocity correction to wavelength: The velocity of the spacecraft towards
the target is included in the header of the SPD file; this information is used
for a correction of the measured wavelength by the Doppler effect.
At this stage an intermediate Auto Analysis product is generated, because it is
possible, especially for weak sources, that the following steps cause
systematic errors. In these cases the observer should perform the remaining
processing with interactive analysis (see section 4).
- Absolute responsivity correction: At the beginning and at the end of each
scientific observation a sequence of standard illuminator flashes is performed.
The ratio between the signal from a reference illuminator flash and the one
from these sequences gives a correction factor with which the absolute
responsivity for each detector is multiplied. As the measurement of the
standard illuminator flash takes only 100 sec, it is prone to corruption e. g.
by strong glitches and this can lead to an incorrect absolute responsivity
correction.
- Responsivity drift correction: The wavelength range AOT's consist of
several identical scans with the grating or the FP, and their average signal
is used to correct for drifts within an observation.
Sometimes the drift
slope cannot be calculated because of a lack of valid data.
The AOT-specific Auto Analysis produces for the bulk of observations
reliable spectra
that give the flux
in W/cmm (W/cm2 for FP spectra) as a function of wavelength in
m. It can serve
as a good starting point for further work, e. g. removing remaining instrument
peculiarities like fringes or extracting scientific results. If problems
occur during the processing Auto Analysis will generate one out of 52 standard
error messages. Typical examples are the notification of the last point in a
scan having a different direction or of observations where the
measurement of the dark current is doubtful, because too
many elementary integration ramps had to be rejected due to glitches.
These messages are brought to
the attention of an instrument specialist and are checked interactively - mostly
with the result that the data products are valid nevertheless.
IMPROVEMENTS OF THE PIPELINE DURING THE MISSION
The experience gained from analyzing pipeline products during the mission leads
to constant improvements of calibration files and of the routines for the
derivation of both SPD and AAR. At certain intervals new versions of the
pipeline are generated which include these updates, and all observations
obtained until then are reprocessed.
Modifications to Calibration Files
Improvements in the calibration of the instrument result usually only in more
accurate numbers and do not require modifications of the processing routines.
These values are embodied in updates of calibration files that are used in the
pipeline processing. For the derivation of Standard Processed Data there are
eleven such files which contain, in the form of FITS headers, the parameters
needed to perform deglitching and voltage conversion. The Auto Analysis stage
makes use of FITS binary tables or primary arrays that contain e. g. the
relationship between mechanism position and wavelength or the relative
response of the instrument.
The dramatic improvements in the quality of the data that were achieved
by updates of calibration files
are best illustrated with the example of the responsivity calibration.
The version of the pipeline that
was used immediately after launch still relied on measurements in the
laboratory,
where extended emission from a blackbody was used for flux calibration.
The resulting spectra of observations in flight had discontinuities
because of the changed
detector sensitivities and they showed fringes which had not been
recognized in the relative spectral response function (RSRF, see
figure 2).
New values for the absolute and relative responsivity that were
based on observations of Ceres and later of Uranus solved both problems
largely (see figure 3).
Figure 2:
The LWS end-to-end spectrum of the bright HII-region S106 as
observed in the performance verification phase of the satellite and processed
to Auto Analysis level
with a pipeline version developed before launch. Because the responsivity of
the detectors was very different in flight from the tests in the laboratory
the ten subspectra do not match. (Another unit for intensity was used in
later versions of the pipeline.)
|
Figure 3:
The same observation as in figure 2
, but processed with a
pipeline version from routine phase. The different subspectra fit here much
better together.
|
Modifications to the Derivation of Standard Processed Data
Apart from several minor bug fixes and modifications to the layout and content
of the SPD files the changes here applied mainly to the determination of the
slope of an elementary integration ramp (see figures 4 and 5). One requirement
for this is the
correct identification of useless points, and it became necessary to increase
the amount of time discarded at the beginning of a ramp at low signal levels,
because it took the detectors longer than expected to recover from a reset
pulse. The slope itself was at first determined by fitting a first or second
order polynomial to the data, but this led at times to discontinuities in the
spectra. Hence finally all ramps were fitted by a second order
polynomial and the slope was determined from a straight line through the first
and the last point of that fit [4].
This means that the result lies between
the higher slope at the beginning and the lower one at the end of the ramp, if
the photocurrent decreases because of saturation.
Figure 4:
Spectrum in one detector (LW4) of the reflection nebula
NGC7023 as
observed in revolution 448 and processed
to Auto Analysis level
with a pipeline version used during routine phase (v. 6). The [OI] line at 146
micron and the [CII] line at 158 micron
are easily recognizable in the spectrum.
|
Figure 5:
The same observation as in figure 4, but processed with a
prototype of the
next pipeline version (v. 7).
The spread of the measured
values has been significantly reduced, mainly because of an improved
ramp fitting.
Modifications to the Derivation of Auto Analysis Results
Major changes to the Auto Analysis were the implementation of a time dependent
grating wavelength calibration, the change in calculating the dark signal and
the number of files to be produced. Most work was concentrated, however, on
optimizing the drift correction. At first the use of illuminator flashes to
correct for changes in responsivity within a revolution [5]
produced unreliable
results, therefore it was switched off. But a new illuminator flash sequence
made this correction within the pipeline possible. Besides, an
algorithm was implemented which removed drifts within an observation by
calculating the average signal from each scan. The usually positive slope of
these average detector signals as a function of time is used to correct for
the responsivity drifts within wavelength range AOT's [6].
For weak sources it
can make a
big difference whether the dark signal is subtracted before or after this
drift correction, since in the first case the algorithm can produce significant
distortions of the signal.
PROCESSING BEYOND AUTO ANALYSIS
The LWS Interactive Analysis Software [7]
allows the observer to examine and
to modify the products of the pipeline.
It contains the following inspection routines:
- Display of the signal from the illuminator flash sequences and the
measured dark current in astronomical observations: This enables the observer to
identify possible corruption in the data (see section 2.3)
- Display of the absolute responsivity correction factors
- Display of pointing directions (this is particularly useful for raster
observations)
- Comparison of the SPD results before and after pipeline deglitching
- Comparison of the SPD results with and without responsivity drift
correction
- Comparison of SPD, Relative Spectral Response Function and AAR:
This comparison is useful for the identification of spurious
features in a grating spectrum.
With them it is possible for the observer to check that the crucial steps of
the pipeline processing have been executed successfully.
If he is not content with the execution of a particular processing
step in the pipeline, he can use LIA also for repeating this step in an
improved way, e. g. by using nominal values for
the dark currents instead of the measured ones. It is possible, too, to
create
a product without the responsivity drift correction.
In order to facilitate the scientific analysis of the data another set of
interactive routines was written: the ISO Spectroscopy Analysis Package
[8].
This software uses AAR as starting point and performs the following tasks in
Interactive Data Language (IDL):
- Display of spectra in various units with the possibility to remove
outliers
- Mathematical operations on the data like averaging of scans or
subtracting of background observations
- Removal of fringes in the spectra that are caused by emission off the
center of the field of view
- Removal of discrepancies between adjacent detectors by comparing their
signals in the overlap region
LIMITS OF PIPELINE PROCESSING
Although the pipeline produces reliable results for the great majority of
observations, there are some conditions which require special attention. The
most important case is the AOT for Fabry Perot range scans (L03), where the
data products should only be used for identification of lines. An insufficient
accuracy in setting the grating to the correct position results in an uncertain
contribution of the underlying grating profile to the FP spectrum.
Therefore the flux calibration in the pipeline can produce here
significant errors, and special interactive processing is required to obtain
the correct shape and flux in the spectrum.
Other peculiarities of the instrument, for which there are currently no
corrections
in the pipeline, are:
- Memory effects in LWS data: The transient response of the doped-Germanium
photoconductors produces a shift of the line center and in certain cases also
variations of the continuum shape depending on the scan direction [9].
The pipeline
uses at present the average relative spectral response function of forward and
backward scans, but separate RSRF's for each scan direction will be
available in the future.
- Special flux calibration for strong sources: Pipeline processing assumes
a linear relationship between photocurrents and flux, but this is not true for
sources with fluxes of several thousand Jy or more. A strong source correction
is being
tested at the time of writing and may be available in a future version of the
pipeline. [6]
- Fringes in the spectra: Reasonable defringing routines are available for
post-pipeline processing.
- Flux calibration for extended sources: Since the beam size of the LWS
differs from the model value and changes as a function of wavelength and
direction in the focal plane, the accuracy of the flux calibration is reduced
for extended sources. In order to quantify this problem, the signal from a
point source at different positions in the field of view has been measured.
But even when the beam geometry is exactly known, highest accuracy in
the flux of an extended source can only be achieved interactively with
certain assumptions on the size and the shape of the source.
- Spurious features in spectra due to filter leaks: This is, like the
previous point, an instrumental effect that as a matter of principle cannot
be resolved automatically. The observer has to
remove the spurious features by fitting a
Gaussian profile to them.
CONCLUSIONS
The experience gained with the LWS during flight made some changes to the
pipeline processing of the data necessary. These modifications reflected the
growing accuracy in the wavelength and flux calibration of the instrument and
the improvements of its observing strategy. Each increase of calibration
accuracy can be implemented by a simple update of a table; changes to the
processing itself are done by modifications of subroutines. This structure has
proven to be flexible enough to adapt quickly to the altered behaviour of
this complex instrument in space, and it was possible to obtain with automatic
processing already during the mission scientifically valid data for the great
majority of observations. Refinements of the calibration in the post mission
phase will result in further updates of the pipeline during the next few years.
ISO is an ESA project with instruments funded by ESA Member States (especially
the PI countries: France, Germany the Netherlands and the United Kingdom) and
with the participation of ISAS and NASA. The LWS was designed and built by a
consortium of scientists and engineers from Canada, France, Italy, the UK and
the USA. For the software systems discussed here the majority of work was
performed at ESTEC SAI and the Rutherford Appleton Laboratory (RAL).
- 1
-
P. E. Clegg, et al., ``The ISO Long-Wavelength Spectrometer,''
A&A 315, pp. L38-L42, 1996.
- 2
-
M. F. Kessler, et al., ``The Infrared Space Observatory (ISO) mission,''
A&A 315, pp. L27-L31, 1996.
- 3
-
K. J. King, et al., ``The life enhancement possibilities of trend
analysis,''
these proceedings,
1998.
- 4
-
B. M. Swinyard, et al., ``In orbit performance of the ISO long wavelength
spectrometer,''
these proceedings,
1998.
- 5
-
M. J. Burgdorf, et al.
, ``In-Orbit Performance of the LWS Detectors,''
in The Far InfraRed and Submillimetre Universe ,
ESA SP-401, ed. A. Wilson, pp. 353-356, 1997.
- 6
-
B. M. Swinyard, et al.
, ``Calibration of the ISO Long Wavelength Spectrometer:
Correction of Detector Responsivity Drift and Non-Linearity,''
in The Far InfraRed and Submillimetre Universe ,
ESA SP-401, ed. A. Wilson, pp. 441-444, 1997.
- 7
-
S. D. Sidher, B. M. Swinyard, A. S. Harwood, S. D. Lord, and S. J. Unger
, ``The LWS Interactive Analysis Software,''
in Proceedings of the First ISO Workshop on Analytical
Spectroscopy ,
ESA SP-419, ed. A. M. Heras, K. Leech, N. R. Trams, and
M. Perry, pp. 297-298, 1998.
- 8
-
E. Sturm, et al., ``The ISO Spectral Analysis Package ISAP,''
ASP Conf. Ser., 1997.
- 9
-
T. Lim, B. M. Swinyard, X.-W. Liu, M. Burgdorf, C. Gry, S. Pezzuto,
and E. Tommasi, ``Memory Effects and the LWS RSRF,''
in Proceedings of the First ISO Workshop on Analytical
Spectroscopy ,
ESA SP-419, ed. A. M. Heras, K. Leech, N. R. Trams, and
M. Perry, pp. 281-282, 1998.
M. J. Burgdorf et al.