Model for a Noise-Matched Phased Array Feed

Abstract

We present a model for a noise-matched phased array feed (PAF) system and compare model predictions with the measurement results. The PAF system consists of an array feed, a receiver, a beamformer, and a parabolic reflector. The novel aspect of our model is the characterization of the PAF system by a single matrix. This characteristic matrix is constructed from the open-circuit voltage covariance (OCVC) at the output of the PAF due to a signal from the observing source, ground spillover noise, sky background noise, and (low-noise) amplifier (LNA) noise. The best signal-to-noise ratio (SNR) on the source achievable with the PAF system will be the maximum eigenvalue of the characteristic matrix. The voltage covariance due to signal and spillover noise is derived by applying the Lorentz reciprocity theorem. The receiver noise covariance and noise temperature are obtained in terms of Lange invariants such that they are suitable for noise matching the array feed. The model predictions are compared with the measured performance of a 1.4 GHz, 19-element, dual-polarized PAF on the Robert C. Byrd Green Bank Telescope. We show that the model predictions, obtained with an additional noise contribution due to the measured losses ahead of the LNA, compare well with the measured ratio of system temperature to aperture efficiency as a function of frequency and as a function of offset from the boresight. Furthermore, our modeling indicates that the bandwidth over which this ratio is optimum can be improved by a factor of at least two by noise matching the PAF with the LNA.