The ATA Digital Processing Requirements are Driven by RFI Concerns

As a new generation radio telescope, the Allen Telescope Array (ATA) is a prototype for the SKA. Here we describe recently developed design constraints for the ATA digital signal processing chain as a case study for SKA processing. As radio frequency interference (RFI) becomes increasingly problematical for radio astronomy, radio telescopes must support a wide range of RFI mitigation strategies including online deterministic and adaptive RFI nulling. We observe that at the ATA, the requirements for digital accuracy and control speed are not driven by astronomical imaging but by RFI. This can be understood from the fact that high precision is necessary to remove strong RFI signals from the weak astronomical background, and because RFI signals may change rapidly compared with celestial sources. We review and critique lines of reasoning that lead us to some of the design specifications for ATA digital processing. Introduction Some of the worst sources of radio frequency interference (RFI) for radio astronomy are low earth orbit (LEO) satellites. Unlike ground-based RFI sources, there is no place on earth where we can hide from such satellites. They broadcast strong signals that sometimes impinge on protected radio astronomical radio bands. Because of their low orbit, their angular position on the sky can vary faster than 1o per second. This presents a major challenge for astronomers attempting to reduce the damaging effects of these sources, and high speed calculations are required to simulate and remove their signals. The square kilometer array (SKA) must face up to this challenge. Because RFI mitigation is so important for the SKA’s success, it must be built into its design from the start. In this regard the Allen Telescope Array (ATA) provides a case study. Having just completed the detailed design, we report that ATA’s digital signal processing requirements are driven by RFI mitigation. Indeed, we discovered that at current technology and funding levels we cannot build a system that is flexible enough to support all desired methods of RFI suppression. In this paper we use simulations of active deterministic nulling of RFI from LEO satellites to quantify requirements for ATA signal processing. Although the simulations assume deterministic nulling, our results can be generalized to adaptive nulling and postcorrelation image processing. ATA Digital Processing and Simulations The ATA is a privately-funded interferometer currently under construction at Hat Creek Radio Observatory in northern California. It is being built in stages, first with 32 elements, then 206, then 350 elements for a total collecting area of about one hectare. The ATA data processing system has been developed and examined in several previous reports. , , , 3 4 5 6 Radio frequency signals from each antenna are downconverted and digitized with 150 MHz bandwidth. These signals are digitally delayed, downsampled to 100 MHz, and then fringe rotation is removed in the digital domain. After this processing, the signals are passed on to an imaging correlator , , 8 9 10 or to beamformers. The ATA beamformer is conceptually depicted in Fig. 1. This is a single-tap beamformer since only one value of delay, τ, is specified for each antenna signal before they are combined. After the delay, fringe rotation is corrected in each antenna signal with a single complex coefficient, c. RFI mitigation through synthetic beam pattern control is also accomplished via manipulation of the coefficients, c. This includes both deterministic and adaptive nulling. In this paper we focus on the requirements for digital control of τ and c. We discuss the communication interface between two subsystems of the ATA. The first is the ATA control software (host), which is distributed over multiple computers and linked by a local area network. The second subsystem is the IF processor, which consists of hundreds of custom-designed, field programmable gate array circuit boards. The host software precalculates τ and c and funnels this information to the IF processor where these coefficients are applied. The information content of these data is quite high, and it is desirable to find a representation that compresses τ and c to manageable rates. As we shall see, appropriate compression of this data is more subtle than it appears at first glance. To elucidate the information content of τ and c, we perform simulations with the currently proposed configuration of the ATA-350. For simplicity, the observation source is placed at telescope zenith. The RFI source is assumed to be in polar orbit on a path that passes directly over the observatory, and the simulations put the satellite in the vicinity of elevation 50o. These calculations use techniques we have developed specifically for the ATA, that generate wide frequency band nulls in a single-tap beamformer. We ignore antenna primary beam variations, whose angular scale is about 100 times larger than that of the synthetic beam pattern. This amounts to the assumption that the primary beam pattern is well characterized at each antenna element, and has been corrected for prior to synthetic beam formation. Specifying Delay, Phase and Amplitude We expect that RFI mitigation will be very important for the success of the ATA and design the data processing chain to be as flexible as possible for real-time RFI removal. This is especially important for devices that rely on beamformer outputs, since postcorrelation techniques for RFI removal are not possible in this case. With this in mind, we notice that some RFI sources are ground-stationary while others (satellites, airplanes) move across the sky at varying speeds. We begin with the assumption that RFI removal (e.g. deterministic or adaptive nulling) requires capabilities similar to tracking and forming a beam on the moving RFI source. At the ATA the requirement was set, somewhat arbitrarily, that we can track RFI sources moving at least as fast as a 350 km altitude low earth orbit (LEO) satellite. This includes almost all present or planned LEO’s but is not fast enough to follow the international space station or an airplane flying directly over the site. The linear velocity of a LEO is nearly independent of altitude and can be approximated by equating the centripetal force with the force of gravity, giving 8 ≈ ≈ rg v km/s. If we approximate the earth’s surface with a plane, we can estimate the angular velocity of a satellite (as viewed from the ground) in an overhead pass as a function of elevation angle θ , and altitude : h = = max 2 , sin θ θ θ & & h v 1.3o / s. [1] The ATA antennas are arrayed over a 1 km x 1 km area. For an antenna at the extreme edge of the array (d = 500 m from center), the path length difference relative to the array center is θ cos d p = , leading to a signal delay of θ θ τ cos 10 x 1.6 cos 6 − = = c d seconds. [2] From this we can estimate the maximal delay and maximal rate of change of delay . s / samples 6 10 x 4 ~ and , samples 000 1 s 10 x 7 4 ~