Open AccessFlexible and Accurate Frequency Estimation for Complex Sinusoid Signal by Interpolation Using DFT Samples
Author(s) -
XIANG Jinzhi,
CUI Wei,
SHEN Qing
Publication year - 2018
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2017.09.019
Subject(s) - estimator , mathematics , additive white gaussian noise , window function , frequency domain , algorithm , mean squared error , cramér–rao bound , noise (video) , signal (programming language) , interpolation (computer graphics) , computer science , white noise , statistics , spectral density , telecommunications , artificial intelligence , mathematical analysis , frame (networking) , image (mathematics) , programming language
A flexible and accurate frequency estimator is first proposed for frequency estimation of a complex sinusoid weighted with a rectangular window function in additive white Gaussian noise. This proposed frequency estimator can be operated in the application of an arbitrary length discrete Fourier transform where the original input data is padded with any zeroes, which makes it more flexible in practice. The proposed frequency estimator utilizes the maximum sample value and its two adjacent samples in the frequency domain to perform the fine frequency estimation with unbiased results obtained. Then a modified frequency estimator is proposed to estimate the frequency when the complex sinusoid signal is weighted with different nonrectangular window functions. Although the modified frequency estimator is nonanalytic and biased, it can still improve the estimation performance for certain applications. Simulation results demonstrate that both of the proposed frequency estimators are effective to achieve the high frequency estimation accuracy. And the root mean square errors of the proposed frequency estimators approach the Cramer‐Rao bound when the signal‐to‐noise ratio is large enough to make the coarse frequency estimation work effectively.