Abstract
Radio-astronomical observations are increasingly contaminated by interference, and suppression techniques become essential. A powerful candidate for interference mitigation is adaptive spatial filtering. We study the effect of spatial filtering techniques on radio-astronomical imaging. Current deconvolution procedures, such as CLEAN, are shown to be unsuitable for spatially filtered data, and the necessary corrections are derived. To that end, we reformulate the imaging (deconvolution/calibration) process as a sequential estimation of the locations of astronomical sources. This is not only leads to an extended CLEAN algorithm, but also the formulation allows the insertion of other array signal processing techniques for direction finding and gives estimates of the expected image quality and the amount of interference suppression that can be achieved. Finally, a maximum-likelihood (ML) procedure for the imaging is derived, and an approximate ML image formation technique is proposed to overcome the computational burden involved. Some of the effects of the new algorithms are shown in simulated images.
| Original language | English |
|---|---|
| Pages (from-to) | 1730-1747 |
| Number of pages | 18 |
| Journal | IEEE Transactions on Information Theory |
| Volume | 46 |
| Issue number | 5 |
| DOIs | |
| State | Published - Aug 2000 |
| Externally published | Yes |
Bibliographical note
Funding Information:Manuscript received September 2, 1999; revised March 21, 2000. The work of A. Leshem was supported by the NOEMI project of the STW under Contract DEL77-4476. The material in this paper was presented in part at the workshop “Perspectives in Radio-Astronomy: Technologies for Large Arrays,” Dwingeloo, The Netherlands 1999.