Spectral Estimation of Weak Signals with Strong Interference via Modulo Sampling

Shoaib Ahmed, Cengcang Zeng, Hongbin Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper introduces a framework for spectral analysis of weak signals in the presence of strong interference that can potentially exceed the dynamic range of the analog-to-digital converter (ADC) employed for data acquisition. The framework combines modulo sampling to avoid ADC saturation with interference cancellation (IC) and adaptive spectral estimators such as amplitude and phase estimation of a sinusoid (APES) and Capon for high-resolution spectral analysis. Numerical simulations validate the proposed approach's ability to accurately recover weak signals' spectrum with significantly lower mean-squared error (MSE) in amplitude estimation compared to conventional methods in the considered scenarios. Notably, it is shown that APES and Capon are able to effectively reject the out-of-range interference and reveal weak spectral content, without requiring the interference cancellation step.

Original languageEnglish
Title of host publication2025 59th Annual Conference on Information Sciences and Systems, CISS 2025
ISBN (Electronic)9798331513269
DOIs
StatePublished - 2025
Event59th Annual Conference on Information Sciences and Systems, CISS 2025 - Baltimore, United States
Duration: 19 Mar 202521 Mar 2025

Publication series

Name2025 59th Annual Conference on Information Sciences and Systems, CISS 2025

Conference

Conference59th Annual Conference on Information Sciences and Systems, CISS 2025
Country/TerritoryUnited States
CityBaltimore
Period19/03/2521/03/25

Keywords

  • adaptive spectral estimator
  • ADC saturation
  • modulo sampling
  • strong interference
  • Weak signal

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