Back in the US-SR: Unlimited Sampling and Sparse Super-Resolution with its Hardware Validation

Ayush Bhandari

doi:10.1109/lsp.2022.3161865

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arXiv · 2207.13230

Back in the US-SR: Unlimited Sampling and Sparse Super-Resolution with its Hardware Validation

Ayush Bhandari

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Abstract

The Unlimited Sensing Framework (USF) is a digital acquisition protocol that allows for sampling and reconstruction of high dynamic range signals. By acquiring modulo samples, the USF circumvents the clipping or saturation problem that is a fundamental bottleneck in conventional analog-to-digital converters (ADCs). In the context of the USF, several works have focused on bandlimited function classes and recently, a hardware validation of the modulo sampling approach has been presented. In a different direction, in this paper we focus on non-bandlimited function classes and consider the well-known super-resolution problem; we study the recovery of sparse signals (Dirac impulses) from low-pass filtered, modulo samples. Taking an end-to-end approach to USF based super-resolution, we present a novel recovery algorithm (US-SR) that leverages a doubly sparse structure of the modulo samples. We derive a sampling criterion for the US-SR method. A hardware experiment with the modulo ADC demonstrates the empirical robustness of our method in a realistic, noisy setting, thus validating its practical utility.

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Ayush Bhandari. 2022-07-27. Back in the US-SR: Unlimited Sampling and Sparse Super-Resolution with its Hardware Validation. https://doi.org/10.1109/lsp.2022.3161865

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