Cited by 29Radar Systems and Signal ProcessingAdvanced Signal Processing TechniquesAdvanced Electrical Measurement Techniques

PARAMETER ESTIMATION OF LFM SIGNAL INTERCEPTED BY SYNCHRONOUS NYQUIST FOLDING RECEIVER

Zeng, Deguo, Cheng, Hao, Zhu, Jun, Tang, Bin·2011·Progress In Electromagnetics Research C

Abstract

Abstract—Nyquist folding receiver (NYFR) is a new kind of intercep-tion architecture, which can simultaneously intercept wideband signals in multi-Nyquist zones with one or two analog-to-digital converters (ADCs). A parameter estimation algorithm of the linear frequency modulated (LFM) signal intercepted by an improved NYFR is pre-sented. Firstly, the NYFR is improved by introducing a synchronous mechanism, and we denote this structure as a synchronous NYFR (SNYFR). Secondly, taking LFM as an example, the input and output noise distributions of an SNYFR are discussed. Then, a fast param-eter estimation algorithm is derived from the frequency spectrum of the output signal, and an advice for the design of local oscillator signal is given. Simulations show that the parameter estimation accuracy is close to the maximum likelihood when the signal to noise ratio (SNR) is above −3 dB. 1.

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Crossref · 10.2528/pierc11062801

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Authors
Zeng, D., Cheng, H., Zhu, J., & Tang, B.
Venue
Progress In Electromagnetics Research C
Published
2011
Volume
23
Pages
69-81
ISSN
1937-8718 (ISSN-L)
OpenAlex
W2042128058
Cited by
29
References
0
Citations by year
2025: 2 · 2024: 1 · 2023: 3 · 2022: 5 · 2021: 2 · 2020: 1 · 2019: 2 · 2018: 4 · 2017: 5 · 2016: 3
FWCI
0.58
Type
journal article
Language
en
Open access
closed
Locations
Progress In Electromagnetics Research C (publishedVersion)
Topics
  • Physical Sciences › Engineering › Aerospace Engineering › Radar Systems and Signal Processing
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Signal Processing Techniques
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Electrical Measurement Techniques
Keywords
linear frequency modulated signals, parameter estimation, analog-to-digital converter, noise distribution, frequency spectrum, maximum likelihood estimation

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