Frequency estimation based on discrete Fourier transform and least squares

Author(s):  
Zhang Gang-bing ◽  
Liu Yu ◽  
Xu Jia-jia ◽  
Hu Guo-bing
2003 ◽  
Vol 83 (8) ◽  
pp. 1661-1671 ◽  
Author(s):  
Stefan Franz ◽  
Sanjit K. Mitra ◽  
Gerhard Doblinger

2020 ◽  
Author(s):  
Chris Anto

For long, the least squares regression line has been a primary tool for analyzing linear data. In this paper, the author suggests a method involving a truncated fourier transform that would achieve everything the least squares method achieves and more, including details about the magnitude of deviation.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5066
Author(s):  
Xiangdong Huang ◽  
Lu Cao ◽  
Wei Lu

The closed-form robust Chinese Remainder Theorem (CRT) is a powerful approach to achieve single-frequency estimation from noisy undersampled waveforms. However, the difficulty of CRT-based methods’ extension into the multi-tone case lies in the fact it is complicated to explore the mapping relationship between an individual tone and its corresponding remainders. This work deals with this intractable issue by means of decomposing the desired multi-tone estimator into several single-tone estimators. Firstly, high-accuracy harmonic remainders are calculated by applying all-phase Discrete Fourier Transform (apDFT) and spectrum correction operations on the undersampled waveforms. Secondly, the aforementioned mapping relationship is built up by a novel frequency classifier which fully captures the amplitude and phase features of remainders. Finally, the frequencies are estimated one by one through directly applying the closed-form robust CRT into these remainder groups. Due to all the components (including closed-form CRT, the apDFT, the spectrum corrector and the remainder classifier) only involving slight computation complexity, the proposed scheme is of high efficiency and consumes low hardware cost. Moreover, numeral results also show that the proposed method possesses high accuracy.


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