The SKA LOW telescope is an interferometer composed of 512 stations. Each station consists of 256 electronically steered antennas. The Low Frequency Aperture Array is the portion of the SKA-LOW telescope including the antennas and the related electronics. The LFAA signal processing chain amplifies, transports and combines the signals from the antennas composing each station into a coherent beam. Beamforming is performed in the frequency domain, with stringent requirements on bandpass flatness, linearity in a RFI contaminated spectral region, and allowed signal degradation. We adopted an architecture including a highly optimized oversampled polyphase filterbank for channelization, and a distributed network beamformer. The system has been validated as part of the Aperture Array Verification System, a single station operating at the SKA site in Western Australia.
KEYWORDS: Prototyping, Analog electronics, Signal processing, Electronic filtering, Digital filtering, Data conversion, Software development, Field programmable gate arrays, Polarization, Antennas
A novel version of digital hardware Italian Tile Processing Module (ITPM) 1.6 has been released for the Low-Frequency Aperture Array (LFAA) component of the Square Kilometre Array (SKA). This back-end includes two plugged-in main blocks, as an analog device , the Pre-ADU board, and an Analog to Digital Unit (ADU), a 6U board containing sixteen dual-inputs Analog to Digital Converters and two Field Programmable Gate Array (FPGA) devices, capable of digitizing and processing 32 RF input signals (50-650 MHz). We present the main features of the upgrade of the board compared to previous versions: there are new and high performance components improving processing capability, mechanical changes matching the design of the housing sub-rack and finally a general reduction of the overall power consumption. The ITPM ADU 1.6 version, now in engineering phase together with its sub-rack system, is currently the last prototype before the design of the industrial line for mass production, necessary for the LFAA deployment. Results of system performances will be presented.
Accurate information extraction from images can only be realised if the data is blur free and contains no artificial artefacts. In astronomical images, apart from hardware limitations, biases are introduced by phenomena beyond control such as atmospheric turbulence. The induced blur function does vary in both time and space depending on the astronomical “seeing” conditions as well as the wavelengths being recorded. Multi-frame blind image deconvolution attempts to recover a sharp latent image from an image sequence of blurry and noisy observations without knowledge of the blur applied to each image within the recorded sequence. Finding a solution to this inverse problem that estimates the original scene from convolved data is a heavily ill-posed problem. In this paper we describe a novel multi-frame blind deconvolution algorithm, that performs image restoration by recovering the frequency and phase information of the latent sharp image in two separate steps. For every given image in the sequence a point-spread function (PSF) is estimated that allows iterative refinement of our latent sharp image estimate. The datasets generated for testing purposes assume Moffat or complex Kolmogorov blur kernels. The results from our implemented prototype are promising and encourage further research.
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