Glancing Through Massive Binary Radio Lenses: Hardware-Aware Interferometry With 1-Bit Sensors. (arXiv:1905.12528v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Stein_M/0/1/0/all/0/1">Manuel S. Stein</a>
Energy consumption and hardware cost of signal digitization together with the
management of the resulting data volume form serious issues for high-rate
measurement systems with multiple sensors. Switching to binary sensing
front-ends results in resource-efficient systems but is commonly associated
with significant distortion due to the nonlinear signal acquisition. In
particular, for applications that require to solve high-resolution processing
tasks under extreme conditions, it is a widely held belief that low-complexity
1-bit analog-to-digital conversion leads to unacceptable performance
degradation. In the Big Science context of radio astronomy, we propose a
telescope architecture based on simplistic binary sampling, precise
hardware-aware probabilistic modeling, and advanced statistical data
processing. We sketch the main principles, system blocks and advantages of such
a radio telescope system which we refer to as The Massive Binary Radio Lenses.
The open engineering science questions which have to be answered before
building a physical prototype are outlined. We set sail for the academic
technology study by deriving an algorithm for interferometric imaging from
binary radio array measurements. Without bias, the method aims at extracting
the full discriminative information about the spatial power distribution
embedded in a binary sensor data stream. We use radio measurements obtained
with the LOFAR telescope to test the developed imaging technique and present
visual and quantitative results. These assessments shed light on the fact that
binary radio telescopes are suited for surveying the universe.
Energy consumption and hardware cost of signal digitization together with the
management of the resulting data volume form serious issues for high-rate
measurement systems with multiple sensors. Switching to binary sensing
front-ends results in resource-efficient systems but is commonly associated
with significant distortion due to the nonlinear signal acquisition. In
particular, for applications that require to solve high-resolution processing
tasks under extreme conditions, it is a widely held belief that low-complexity
1-bit analog-to-digital conversion leads to unacceptable performance
degradation. In the Big Science context of radio astronomy, we propose a
telescope architecture based on simplistic binary sampling, precise
hardware-aware probabilistic modeling, and advanced statistical data
processing. We sketch the main principles, system blocks and advantages of such
a radio telescope system which we refer to as The Massive Binary Radio Lenses.
The open engineering science questions which have to be answered before
building a physical prototype are outlined. We set sail for the academic
technology study by deriving an algorithm for interferometric imaging from
binary radio array measurements. Without bias, the method aims at extracting
the full discriminative information about the spatial power distribution
embedded in a binary sensor data stream. We use radio measurements obtained
with the LOFAR telescope to test the developed imaging technique and present
visual and quantitative results. These assessments shed light on the fact that
binary radio telescopes are suited for surveying the universe.
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