Stefan J. Wijnholds and Simone Chiarucci, "Blind calibration of
phased arrays using sparsity constraints on the signal model,"
24th European Signal Processing Conference (EuSiPCo), Budapest
(Hungary), 29 August - 2 September 2016.
abstract:
Several blind calibration methods have been proposed in a compressive
sensing framework to mitigate the detrimental effects of uncertainties
in the measurement matrix due to sensor gain and phase errors. Most of
these methods operate on the signal domain samples of the receiving
elements. This becomes computationally intractable if a large number
of time samples is required, for example in low-SNR applications. In
this paper, we propose an iterative blind calibration method to
estimate the receiver path gains and phases as well as the observed
scene from the measured array covariance matrix under the assumption
that the observed scene is sparse. We successfully demonstrate the
effectiveness of our method using simulated data for a 20-element
uniform linear array as well as actual data from a 48-element station
(subarray) of the Low Frequency Array (LOFAR) radio astronomical
phased array.
back to publication
list
|