Gain calibration methods for radio telescope arrays

• Published in: IEEE transactions on signal processing Vol. 51; no. 1; pp. 25 - 38
• Main Authors: Boonstra, A.-J., van der Veen, A.-J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-01-2003; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Array signal processing; Arrays; Calibration; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Filtering; Gain; Information, signal and communications theory; Interference; Iterative algorithms; Noise; Radio astronomy; Radio telescopes; Receivers; Sensor arrays; Signal and communications theory; Signal processing algorithms; Signal to noise ratio; Signal, noise; Sky; Telecommunications and information theory; Parameter estimation; Telescope; Factor analysis; Radio astronomy; Array signal processing; Simulation; Least squares method; Signal estimation; Iterative method; Calibration; Sensor array; Algorithm
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2002.806588

In radio telescope arrays, the complex receiver gains and sensor noise powers are initially unknown and have to be calibrated. Gain calibration can enhance the quality of astronomical sky images and, moreover, improve the effectiveness of array signal processing techniques for interference mitigation and spatial filtering. A challenging aspect is that the signal-to-noise ratio (SNR) is usually well below 0 dB, even for the brightest sky sources. The calibration method considered here consists of observing a single point source and extracting the gain and noise parameters from the estimated covariance matrix. We present several closed-form and iterative identification algorithms for this. Weighted versions of the algorithms are proven to be asymptotically efficient. The algorithms are validated by simulations and application to experimental data observed at the Westerbork Synthesis Radio Telescope (WSRT).