Phased arrays have a long history in radio astronomy. Large, sparse synthesis arrays have been in use for decades to capture high-resolution images of deep space objects. More recent work has extended the range of applications to other types of arrays, including aperture arrays (AAs) and phased array feeds (PAFs) for multibeam reflector antennas. The extreme sensitivity required for astronomical instrumentation is driving advances in numerical electromagnetic modeling, design optimization of large arrays, low noise amplifiers, minimization of receiver noise, cryogenic PAFs, array calibration, optimal beamforming, interferometric imaging, and array signal processing algorithms for radio-frequency interference mitigation. We give an overview of research progress, current and planned array-based instruments, and open challenges in these areas related to the new generation of sparse arrays, PAFs, and AAs that are in development for astronomical observatories around the world.

Adaptive interference canceling beamformers are known to suffer from beampattern distortion, particularly when interferers approach the nominal mainlobe. In some applications such as radio astronomy, even small pattern variations can be problematic. We address the issue of computing power spectral density (PSD) estimates at the output of a beamforming array in the presence of strong moving interference. A bias corrected PSD estimation algorithm is introduced which uses subspace projection methods to cancel interference at the beamformer. A correction step eliminates both pattern-distortion-induced PSD bias and spatial response errors over the long-term PSD averaging window.

High-frequency approximations to the physical optics (PO) theory of scattering from exponentially correlated rough surfaces are examined and used to interpret the expected accuracy of the PO theory. As an introduction, a review of the PO theory for Gaussian-correlated surfaces is provided, and in this process an analytical summation of the PO series for specular scattering from Gaussian-correlated surfaces is obtained. A similar form is then derived for specular scattering from exponentially correlated surfaces and contrasted to the Gaussian case. These series allow the accuracy of the leading order term (i.e., the geometrical optics limit) in the high-frequency approximation of PO scattering for Gaussian or exponentially correlated surfaces to be investigated analytically. The leading order term in the high-frequency expansion for general PO scattering from exponentially correlated surfaces (Hagfors' Law) is then reviewed and interpreted in terms of a recently published theory of PO for surfaces with infinite rms slopes. The approximate ldquocutoffrdquo wavenumber from Hagfors' Law at which the high-frequency portion of the spectrum of an exponentially correlated surface can be truncated without producing large errors in PO predicted scattering is also discussed. Using this cutoff wavenumber, an approximate region of validity of the complete PO theory for exponentially correlated surfaces is obtained. The validity condition indicates that, for fixed surface statistics, the PO method produces accurate predictions of true surface scattering only up to a specific frequency, and that PO is inaccurate in the high-frequency limit. Comparisons of PO predictions with those of a Monte Carlo numerical simulation are used to show that the validity condition derived appears to provide a reasonable indication of PO accuracy. These results have important implications for current investigations of scattering from exponentially correlated surfaces and for the use of Hagfors' Law, as it is traditional to accept PO as the appropriate high-frequency limit in most existing approximate models of surface scattering.

An electromagnetic (EM) bias model for microwave frequencies is derived using the physical optics scattering approximation with a sea surface model that includes the effects of hydrodynamic modulation and non-Gaussian long-wave statistics. Correlation of long-wave slopes with displacement and hydrodynamic modulation of short-wave amplitudes are the two major contributors to the EM bias. The fact that the bias is caused by physical processes with different dependencies on frequency and sea state parameters accounts for some of the difficulties encountered with previous bias modeling efforts. The frequency dependence of the bias is weak because the trends of the hydrodynamic and height-slope skewness contributions with respect to frequency are in opposition. The model provides theoretical support for previous empirical observations of weak correlation of relative bias with wind speed and strong correlation with root-mean-square long-wave slope. While the presence of wind-generated small-wave roughness is crucial to the portion of the bias caused by hydrodynamic modulation, the magnitude of the bias thus induced is largely independent of local wind speed. The bias model is validated by comparison to measured data from two tower radar experiments, the Gulf of Mexico experiment (1991-1992) and the Brigham Young University off-nadir experiment (2003). Both quantitative and qualitative agreements between model and measurements are observed.

Spatial filtering and subspace projection methods have been proposed for removing interference signals at radio astronomy (RA) imaging arrays. Given the fact that RA signal levels are usually below noise levels, and since high gain antennas significantly reduce the interference to noise level at antenna feeds, it is often difficult to form the accurate interference signal parameter estimates. By adding a few (1-3) low gain "auxiliary" antennas to an imaging array, it is possible to overcome this problem. Using low cost auxiliaries with an existing array can improve interference rejection by tens of decibels. New extensions to subspace projection spatial filtering methods are presented, along with simulated results for performance comparison.

Sea surface height measurements using remote sensing instruments have become increasingly accurate as satellite altimetry technology has matured. Early satellite missions had altimetry errors on the order of tens of centimetres. As these errors have been eliminated, the electromagnetic (EM) bias has become increasingly significant. The latest satellite missions, TOPEX/Poseidon and Jason-1, have EM bias error budgets of 4.2 cm and 2.5 cm, respectively. The purpose of our research has been to investigate methods to reduce the EM bias estimation errors to the sub-cm level. Most current EM bias models create estimates from geophysical properties that can be measured remotely. Typically these parameters are wind speed and significant wave height. The current operational model for the TOPEX/Poseidon and Jason-1 satellite missions is of this type. The operational model uses nonparametric methods to improve the accuracy of the estimates. In addition to improving the bias estimates, the latest operational model has shown a stronger agreement between satellite and tower EM bias models. Combining nonparametric techniques with the wind speed and significant wave height has created the most accurate empirical models to date. However, the amount of variance in the bias requires new methods to improve bias estimates. We made a preliminary study based on the angular dependence of the EM bias. Theoretical scattering models indicate that the bias is dependent on incidence angle, which may allow improved operational correction of the bias using a wide-swath altimeter.