A Nyquist folding analog-to-information receiver
Abstract
Many radar and communications applications require detection and estimation of signal information across an extremely wide radio frequency (RF) bandwidth. In practice, however, direct digitization of this broadband RF environment is problematic. Physical limitations in analog-to-digital converter (ADC) technology restrict the total bandwidth that can be digitized, as well as the ability to digitize high RF signals directly. This paper describes a novel ldquoanalog-to-informationrdquo receiver, motivated by recent developments in compressed sensing (CS), which overcomes both of these challenges in certain settings. The proposed receiver performs frequency modulated pulsed sampling at sub-Nyquist/Shannon rates to compress a broadband RF environment into an analog interpolation filter. The RF sample clock modulation induces a Nyquist-zone dependent frequency modulation on the received signals, allowing separation and recovery of the signal information from a sparse broadband RF environment.
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The NYFR is an undersampling receiver that can intercept signals in the entire frequency band with a single ADC and without frequency sweeping in theory.
“The NYFR is an undersampling receiver that can intercept signals in the entire frequency band with a single ADC and without frequency sweeping in theory.”
Cites
Photonic analog-to-digital converters
Valley, G. C. (2007) · Optics Express · doi:10.1364/oe.15.001955 · Cited by 784 · see citing works
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Pace, P. E., Kusmanoff, A., & Fudge, G. L. (2009) · 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers · doi:10.1109/acssc.2009.5470156 · Cited by 11 · see citing works
Self-citationParameter Estimation of SAR Signal Based on SVD for the Nyquist Folding Receiver
Li, T., Zhu, Q., & Chen, Z. (2018) · Sensors · doi:10.3390/s18061768 · Cited by 8 · see citing works
Liu, X., Li, T., Fan, X., & Chen, Z. (2019) · Sensors · doi:10.3390/s19061477 · Cited by 8 · see citing works
“It can be seen that m is a frequency-dependent signature on each component of the original signal [9].”
BackgroundParameter estimation of LFM signals intercepted by a composite local oscillation SNYFR
Li, T., Fan, X., Zhu, Q., & Chen, Z. (2017) · 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) · doi:10.1109/ispacs.2017.8266510 · Cited by 9 · see citing works
- Authors
- Fudge, G. L., Bland, R. E., Chivers, M. A., Ravindran, S., Haupt, J., & Pace, P. E.
- Affiliations
- University of Wisconsin–Madison (US)
- Naval Postgraduate School (US)
- Venue
- 2008 42nd Asilomar Conference on Signals, Systems and Computers
- Publisher
- IEEE
- Published
- 2008-10
- Pages
- 541-545
- ISSN
- 1058-6393 (ISSN-L)
- OpenAlex
- W2171737517
- Cited by
- 76
- References
- 1
- Citations by year
- 2026: 4 · 2025: 2 · 2024: 3 · 2023: 4 · 2022: 8 · 2021: 3 · 2020: 1 · 2019: 3 · 2018: 6 · 2017: 8 · 2016: 4 · 2015: 2 · 2014: 2 · 2013: 4 · 2012: 7
- FWCI
- 9.91
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Asilomar Conference on Signals, Systems and Computers (ACSSC) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Computational Mechanics › Sparse and Compressive Sensing Techniques
- Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical Analysis and Transform Methods
- Keywords
- sub-Nyquist sampling, compressed sensing, sparse signal recovery
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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