Signal Processing Tools for Radio Astronomy - Signal Processing Systems - page 453

simple (no multipath), in contrast to other array processing applications such as
seismology, synthetic aperture radar, or biomedical tomography.
However, this does not mean that radio astronomy is a “simple” application: data
volumes are massive, and the requirements on resolution and accuracy are mind-
boggling. Current telescopes, developed in the 1970s, start with signals sampled
at 1-2 bits accuracy (because anyway the signals are mostly noise), and after data
reduction and map making routinely end up with images with a dynamic range
of 10 5 .
So far, radio astronomy has done very well without explicit connection to
the array signal processing literature. However, we expect that, by making this
connection, a wealth of new insights and access to “new” algorithms can be
obtained. This will be beneficial, and possibly essential, for the development of new
instruments like LOFAR and SKA.
For further reading we suggest, first of all, the classical radio astronomy text-
books, e.g., Thompson [ 37 ] andPerley[ 33 ] . The August 2009 issue of the Proceed-
ings of the IEEE was devoted to the presentation of new instruments. The January
2010 issue of IEEE Signal Processing Magazine gave a signal processing perspec-
tive. For general insights into imaging and deconvolution, we suggest Blahut [ 2 ] .
Challenges for signal processing lie in (1) imaging, (2) calibration, (3) interfer-
ence suppression. These problems are really intertwined. It is interesting to note that,
especially for calibration and interference suppression, factor analysis is an essential
tool. Our contributions in these areas have appeared in [ 1 , 4 , 19 , 20 , 22 , 39 , 41 , 46 -
48 ] and are summarized in the Ph.D. theses [ 3 , 38 , 44 ] , which should provide ample
details for further reading.
References
1. Ben-David, C., Leshem, A.: Parametric high resolution techniques for radio astronomical
imaging. IEEE J. Sel. Topics in Signal Processing 2 (5), 670-684 (2008)
2. Blahut, R.E.: Theory of remote image formation. Cambridge University Press (2004). ISBN
0521553733
3. Boonstra, A.J.: Radio frequency interference mitigation in radio astronomy. Ph.D. thesis, TU
Delft, Dept. EEMCS (2005). ISBN 90-805434-3-8
4. Boonstra, A.J., van der Veen, A.J.: Gain calibration methods for radio telescope arrays. IEEE
Trans. Signal Processing 51 (1), 25-38 (2003)
5. Boonstra, A.J., Wijnholds, S.J., van der Tol, S., Jeffs, B.: Calibration, sensitivity and RFI
mitigation requirements for LOFAR. In: IEEE International Conference on Acoustics, Speech
and Signal Processing (ICASSP). Philadelphia (Penn.), USA (2005)
6. Borgiotti, G.B., Kaplan, L.J.: Superresolution of uncorrelated interference sources by using
adaptive array techniques. IEEE Trans. Antennas Propagat. 27 , 842845 (1979)
7. Briggs, D.S.: High fidelity deconvolution of moderately resolved sources. Ph.D. thesis, New
Mexico Inst. of Mining and Technology, Socorro (NM) (1995). URL http://www.aoc.nrao.edu/
dissertations/dbriggs/
8. Cornwell, T., Braun, R., Briggs, D.S.: Deconvolution. In: G.B. Taylor, C.L. Carilli, R.A.
Perley (eds.) Synthesis Imaging in Radio Astronomy II, Astronomical Society of the Pacific
Conference Series , vol. 180, pp. 151-170 (1999)