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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 beamforming. 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.