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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.
Robust, Realtime Bandpass Removal for the Hi Parkes All
Sky Survey Project using AIPS++
D. G. Barnes
School of Physics, The University of Melbourne, Parkville, VIC 3052,
Australia; Email: dbarnes@physics.unimelb.edu.au
L. Staveley­Smith, T. Ye and T. Oosterloo
Australia Telescope National Facility, Marsfield, NSW 2122, Australia
Abstract. We present the algorithm and implementation details for
the robust, realtime bandpass removal and calibration routine developed
for the Hi Parkes All Sky Survey project. The software is based on the
AIPS++ toolkit.
1. Introduction
In Barnes (1998) we give an overview of the Parkes Multibeam Software, and the
motivation for its development, that is, the desire to have robust, realtime pro­
cessing software for the neutral hydrogen Hi Parkes All Sky Survey (HIPASS).
In this paper, we provide more details on the bandpass correction algorithm,
and its implementation, based on the AIPS++ toolkit.
2. Robust Bandpass Removal
Traditionally, the bandpass that is present in single­dish 21 cm spectra is re­
moved by observing in a ``signal­reference'' mode. In this mode, an extended
integration (typically 3 min) is acquired while the telescope is pointed at the tar­
get position, or signal. A second extended integration is then acquired while the
telescope is pointed towards a nearby position free of line or continuum sources---
the reference. The bandpass is removed by dividing the signal spectrum by the
reference spectrum. If longer on­source integration times are required, this pro­
cess can be repeated many times, and the quotient spectra averaged.
For the HIPASS Project, where the telescope is actively driven across the
sky at a rate of # 1 # min -1 , the traditional bandpass removal technique is not
suitable. Instead, a statistical estimate of the bandpass at the position and time
that a particular spectrum---the target spectrum---was acquired is made from
a set of earlier and later spectra observed by the same beam---these are the
reference spectra. The bandpass is then removed from the target spectrum by
dividing it by the statistical bandpass estimate.
This process can be formalised as follows: a particular integration will be
denoted as I b,p,c , where the subscripts b and p represent a beam­polarisation
89

90 Barnes, Staveley­Smith, Ye and Oosterloo
combination 1 , and c is the cycle number of the integration. I b,p,c is a 1024­
channel flux density spectrum.
For a given beam and polarization pair, the target spectrum is I b,p,ctarget ,
and the reference spectra, R, are a set of spectra which can be used to estimate
the bandpass for the target spectrum. The suitability of a particular spectrum
depends on a number of factors. Most importantly, a reference spectrum must be
measured on a part of the sky which is independent (with respect to the telescope
beam) of the part of the sky measured by the target spectrum. However, the
bandpass can be expected to vary with time, so spectra taken nearby in time
to the target spectrum are more useful reference spectra than those taken at
greater time separations. Furthermore, any movements of the receiver with
respect to the telescope dish, including rotations and axial movements, were
found to introduce large phase changes in the bandpass. This led to extreme
ripple in the baseline of spectra corrected with reference spectra having varying
parallactic angles or axial o#sets. Thus, valid reference spectra must be from
the same right ascension (or Galactic latitude) scan as the target spectrum.
Having selected the reference spectra R, the estimate of the bandpass
(B b,p,ctarget ) is given by
B b,p,ctarget = median (R) (1)
where the median statistic is taken channel by channel. Other, more sophisti­
cated estimators, such as robust linear interpolation, were tested, but proved
too slow for realtime reduction since in general they require minimization of
non­linear functions in multi­dimensional parameter spaces.
With B b,p,ctarget determined, calibration of the spectral data can be done
concurrently with bandpass removal. The system temperature for the target
spectrum, T target , is provided in the correlator file, whilst that for the bandpass
estimate, T bandpass , is obtained in a fashion analogous to the calculation of a sin­
gle channel in the bandpass estimate. Thus the bandpass­corrected, calibrated
target spectrum is
S b,p,c target
= I b,p,c target
B b,p,c target
â T bandpass - T target (2)
2.1. Implementation
The bandpass calculator, which is our AIPS++ implementation of Equa­
tion 2, stores incoming spectra in a four dimensional bu#er, of the form
Matrix>. The row and column in the parent matrix select
a beam­polarization pair, and the row and column in the sub­matrices select
cycle and channel numbers. The spectra are arranged this way to optimise ac­
cess speeds, yet still provide row() and column() methods to e#ciently extract
spectra or time series of individual channels. Both these operations are required
for bandpass correction. Since shu#ing the data through the matrices would be
ine#cient, an indexing system is utilised to keep track of the newest spectrum
added to the bu#er. Spectra are discarded (overwritten) when they are no longer
required.
1 Normally, b # {1, 2, . . . , 13} and p # {1, 2}.

Realtime Bandpass Removal for the Hi Parkes All Sky Survey 91
0 20 40 60 80 100
Cycle number
-0.2
-0.1
0.0
0.1
0.2
Flux
(cal,
Jy)
31.6
32.0
32.4
32.8
Flux
(raw,
Jy)
Figure 1. Raw (top) and calibrated flux densities for a selected chan­
nel of a HIPASS scan through the interacting galaxy ESO 269­IG 056
(cycles 34--41) and the continuum source PKS 1307­403 (cycles 66--
73)---see text.
2.2. Examples
Figure 1 shows the uncalibrated and calibrated flux densities for a selected chan­
nel of a HIPASS scan through a galaxy with the central beam of the Multibeam.
The galaxy appears as a rise and fall in flux density over cycles 35 to 42. This
feature is preserved in the calibrated flux densities; the uncalibrated and cali­
brated spectra corresponding to cycle 36 are shown in Figure 2.
The feature observed near cycle 69 in the raw bandpass (Figure 1) is the
continuum source PKS 1307­403 which generates an increased flux density in all
line channels. To first order, continuum sources are removed by the bandpass
removal algorithm, since the entire spectrum is rescaled according to Equation 2,
and then the median value of all channels is subtracted from each channel as a
simple means of baseline removal. For strong continuum sources though, there
are still serious baseline ripple and curvature e#ects which remain in the cali­
brated spectra.
3. Discussion and Conclusion
The robust bandpass removal algorithm implemented for the HIPASS Project
successfully produces calibrated Hi emission line spectra for most of the sur­
vey data. The technique is robust to the presence of contamination by radio
frequency interference and strong on­axis and o#­axis continuum sources in the
reference spectra. Unfortunately though, sources which emit in a particular
channel over more than # 2 # of declination, such as the Galaxy or associated

92 Barnes, Staveley­Smith, Ye and Oosterloo
0 500 1000
Channel Number
-0.2
0.0
0.2
0.4
Flux
(cal,
Jy)
0.0
10.0
20.0
30.0
40.0
Flux
(raw,
Jy)
Figure 2. Raw (top) and calibrated flux density spectrum for a single
integration (cycle 36) of the same HIPASS scan as shown in Figure 1---
see text.
high­velocity clouds, are not well calibrated. This is because a trade­o# between
a larger set of reference spectra (yielding a better estimate of the emission­
free bandpass in such cases) and a smaller set of reference spectra (yielding
robustness to time­variability of the bandpass) was necessary. Conversely, the
calibrated spectra of unresolved sources, which will form the bulk of the sources
detected by the HIPASS, are invariably flat and of excellent quality.
Acknowledgments. We were delighted with the frequent and high­quality
help provided by the many AIPS++ programmers during the planning and pro­
gramming of the Parkes Multibeam Software. We are grateful to the ATNF and
collaborating institutions for supporting the development of the Parkes Multi­
beam Receiver. We acknowledge the large investment of time and personnel
towards the design and construction of the receiver by the CSIRO Division of
Telecommunications and Industrial Physics. DGB acknowledges the support
of an APA, and is grateful for the financial assistance to attend ADASS '97
provided by the ADASS POC and a Melbourne Abroad Scholarship.
References
Barnes, D. G. 1998, this volume