Multisource self-calibration for sensor arrays
IEEE Transactions on Signal Processing
Robust approaches to remote calibration of a transmitting array
Signal Processing
Spatial rank estimation in cognitive radio networks with uncalibrated multiple antennas
Proceedings of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management
| Hi-index | 35.69 |
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).