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Method and device for frequency estimation of subsampled waveform under strong noise interference

A technology of frequency estimation and sampling frequency, which is applied in the field of frequency estimation of subsampled waveforms, can solve problems such as deviation, large error in reconstruction results, and unsuitable frequency estimation, and achieve high accuracy, strong adaptability, and improved anti-noise performance Effect

Inactive Publication Date: 2017-12-05
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0008] However, the above CRT method requires the remainder error to be strictly controlled within M / 4
Under the condition of strong noise interference, some residuals will have large deviations, sometimes exceeding M / 4. At this time, the error of the reconstruction result is large, and the closed CRT is invalid, which is not suitable for frequency estimation under strong noise interference.

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  • Method and device for frequency estimation of subsampled waveform under strong noise interference
  • Method and device for frequency estimation of subsampled waveform under strong noise interference
  • Method and device for frequency estimation of subsampled waveform under strong noise interference

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Embodiment 1

[0056] A frequency estimation method for undersampled waveforms under strong noise interference, see figure 1 , the frequency estimation method includes the following steps:

[0057] 101: respectively with f s1 ~ f sL For the sampling rate, L channels of low-speed sampling are performed on high-frequency signals containing noise interference to obtain L channels of sampling signals x i (n)(i=1,...,L);

[0058] 102: L channels of signal x obtained by sampling at a low rate i (n) Perform Fast Fourier Transform (FFT), and obtain f for each channel si (1≤i≤L) sample points and store them;

[0059] 103: Use the L-channel FFT spectrum distribution characteristics to extract the frequency corresponding to the peak position of the amplitude spectrum as the noise-containing remainder of each channel output, and set the residual error of each channel to be Δr i , that is Among them, r i is the signal frequency f 0 Modulo each sampling rate f si remainder obtained after.

...

Embodiment 2

[0066] Below in conjunction with specific calculation formula, example the scheme in embodiment 1 is described in detail:

[0067] 201: L-channel low-speed undersampling;

[0068] Let the received noisy signal be x(t)=a exp(j2πf 0 t)+ω(t), f 0 is the signal frequency, that is, the measured frequency. Perform L-way undersampling on it, and the sampling frequency is f s1 ~ f sL , sampling frequency f si (1≤i≤L) requires that the common divisor is M, and f si The factor Γ obtained after dividing by the common divisor M i It is pairwise prime. Then each sampling signal x i (n) is:

[0069]

[0070] 202: Perform FFT transformation on each channel of the sampled signal, analyze the spectrum characteristics, and extract the remainder;

[0071] For the L signal x obtained after sampling i (n), respectively do the sampling frequency f si Point FFT transformation, and obtain the magnitude spectrum of the i-th path, find out the frequency value corresponding to the largest...

Embodiment 3

[0094] Below in conjunction with concrete experimental data, accompanying drawing, the scheme in embodiment 1 and 2 is carried out feasibility verification, see the following description for details:

[0095] Analysis of results

[0096] Experiment 1 screening error remainder

[0097] It may be advisable to take L=6 channels of undersampling and K=4 channels with small error residuals as an example to illustrate the detailed process of screening error residuals. Assume that there is a large error in the remainder of the second path, that is, the error Δr 2 >M / 4, and set the sampling frequency as f s1 =18M,f s2 =19M, f s3 =23M, f s4 =25M, f s5 =29M,f s6 =31M, where M=801 is f s1 ~ f s6 greatest common divisor of . The signal frequency is set to f 0 =N=250000Hz.

[0098] According to the closed CRT algorithm of literature [10], the correct remainder set is r={4894 6496 10501 9700 177101690}, and the correct folded integer n i The set is n={17 16 13 12 10 10}, and th...

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Abstract

The invention discloses a method and device for frequency estimation of under-sampled waveforms under strong noise interference. The method comprises: performing L-channel low-speed sampling on high-frequency signals containing noise interference to obtain L-channel sampling signals; respectively sampling the L-channels The signal is subjected to FFT transformation at the sampling frequency fsi point; the frequency corresponding to the peak position of the amplitude spectrum is extracted by using the L-channel FFT spectrum distribution characteristics as the output of the noise-containing residual of each channel; the sampling rate of each channel and the filtered error residual are combined The improved Chinese remainder theorem under the condition of low signal-to-noise ratio obtains the frequency estimation of the original high-frequency signal. The device includes: an acquisition module, a transformation module, an extraction module and a frequency estimation module, and an output drive and display circuit for output. The invention realizes the frequency measurement after multi-channel under-sampling of the high-frequency signal, and improves the anti-noise robustness of the frequency estimation of the under-sampling signal under the condition of low signal-to-noise ratio.

Description

technical field [0001] The present invention relates to the field of digital signal processing, in particular to a method and device for estimating the frequency of undersampled waveforms under strong noise interference, and in particular to performing multi-channel undersampling on high-frequency signals under strong noise interference, and using samples to perform remainder A method for detecting errors and making high-precision measurements of the frequency of high-frequency signals. Background technique [0002] Frequency estimation and detection problems of high-frequency signals widely exist in the engineering field, such as phase resolution of radar communication arrival signals in literature [1][2] and array signal processing problems in sensor networks. The Nyquist sampling theorem requires that more than 2 sampling points need to be collected in one signal cycle. However, in fields such as radio engineering, it is more and more common to process signals with high f...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R23/02G01R23/16G01S7/02
Inventor 黄翔东白瑞朋靳旭康吕卫
Owner TIANJIN UNIV