  The Square Kilometre Array (SKA) will form the largest radio telescope ever
built and such a huge instrument in the desert poses enormous engineering and
logistic challenges. Algorithmic and architectural breakthroughs are needed.
  Data is collected and processed in groups of antennas before transport for
central processing. This processing includes beamforming, primarily so as to
reduce the amount of data sent. The principal existing technique points to a
region of interest independently of the sky model and how the other stations
beamform.
  We propose a new collaborative beamforming algorithm in order to maximize
information captured at the stations (thus reducing the amount of data
transported). The method increases the diversity in measurements through
randomized beam- forming. We demonstrate through numerical simulation the
effectiveness of the method. In particular, we show that randomized beamforming
can achieve the same image quality while producing 40% less data when compared
to the prevailing method matched beamforming.
