NDLI: A NSZT Method for Frequency Estimation and Anti-noise Performance Analysis

Content Provider	IET Digital Library
Author	Zhang, Wenxin Liu, Xiaojun Chen, Xiuwei Liu, Qing Fang, Guangyou
Abstract	Among all the frequency estimation algorithm, the spectrum zooming method has superiority for high resolution and excellent anti-noise performance, but it needs more computational resource. The typical spectrum zooming methods include Zoom fast Fouriertransform (ZFFT), Chirp-Z transform (CZT) and zeropadding, which are all uniform spectrum zooming methods. A Nonuniform spectrum zooming transform (NSZT) method with higher accuracy, better anti-noise ability and higher efficiency is presented. To verify the proposed method, the Monte-Carlo simulations are performed. Results are presented and compared with the Cramer-Rao bound (CRB) method, showing that the proposed algorithm has the least Mean square error (MSE) among these algorithms. This NSZT method is used in a 24GHz Frequency modulated continuous wave (FMCW) radar system and an experiment for the real-time ranging is conducted. The experimental results show that the ranging error of the radar system is about 5mm in 10m, which verifies the feasibility of our proposed method.
Starting Page	648
Ending Page	657
Page Count	10
ISSN	10224653
Volume Number	27
e-ISSN	20755597
Issue Number	Issue 3, May (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/27/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2017.10.007
Journal	Chinese Journal of Electronics
Publisher Date	2018-05-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	(NSZT) Method Anti-noise Ability Cramer-Rao Bound Method CW Radar Excellent Anti-noise Performance Fast Fourier Transform FM Radar Frequency 24.0 GHz Frequency Estimation Frequency Estimation Algorithm Frequency Modulation Image Resolution Integral Transforms Mean Square Error Method Monte Carlo Method Nonuniform Spectrum Zooming NSZT Method Radar Equipment Signal Processing Signal Processing And Detection Size 10.0 M Size 5.0 Mm Spectral Analysis Spectrum Zooming Method Statistics System And Application Typical Spectrum Zooming Method Uniform Spectrum Zooming Method Zoom Fast Fourier
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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