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A Denoising Method of Multi-component LFM Signal Based on Lu Distribution

A chirp signal, multi-component technology, applied in transmission systems, electrical components, etc., can solve the problem of lack of denoising technology, and achieve the effect of moderate computational complexity

Inactive Publication Date: 2019-05-14
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] Names of existing denoising techniques the complexity features Based on short-time Fourier transform (STFT) Low Works only at positive SNR, fails at negative SNR Based on the Wiener-Willi distribution (WVD) middle Works only at positive SNR, fails at negative SNR Based on wavelet transform middle Works only at positive SNR, fails at negative SNR weighted filter based middle Works only at positive SNR, fails at negative SNR Based on Intrinsic Mode Function (IMF) Low Not suitable for LFM signals Based on optimization model high Can work under negative SNR
[0006] Analyzing Table 1, it can be seen that there is currently a lack of a denoising technology for multi-component LFM signals that can work under strong noise (negative SNR) and moderate computational complexity

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  • A Denoising Method of Multi-component LFM Signal Based on Lu Distribution
  • A Denoising Method of Multi-component LFM Signal Based on Lu Distribution
  • A Denoising Method of Multi-component LFM Signal Based on Lu Distribution

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Embodiment Construction

[0041] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0042] Under the computer MATLAB environment, the simulated signal generated according to formula (1) is: the number of components K=2; the amplitude is 1; the center frequency is f 1 =-6.5Hz, f 2 =-1.5Hz; modulation frequency is γ 1 = 1Hz / s, γ 2 =0.75Hz / s; sampling frequency f s =128Hz, signal sampling points N s =256. According to the original signal generated by this parameter, the embodiment of the present invention, the time-domain graph based on the fractional Fourier transform denoising signal is in figure 2 shown.

[0043] Here, the denoising method based on fractional Fourier transform is as follows: first perform fractional Fourier transform on the noisy signal; then perform signal detection in the fractional Fourier domain to obtain the signal peak value; finally perform fractional Fourier inverse on the signal peak value tr...

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Abstract

The invention belongs to the field of time-frequency analysis in signal processing, and in particular relates to a multi-component linear frequency modulation signal denoising technology based on Lu distribution. Aiming at multi-component linear frequency modulation signals, the present invention proposes signal reconstruction based on Lu distribution, and combines signal detection technology to perform denoising processing on signals under strong noise pollution, and the result is a denoising signal close to the original signal in the time domain. Since the Lu distribution has the characteristics of high energy aggregation and strong noise suppression for multi-component linear frequency modulation signals, the present invention can effectively denoise and reconstruct signals under negative signal-to-noise ratio (that is, the noise power is greater than the signal power), and the calculation The complexity is moderate, and the mean square error value between the denoised signal and the original signal is better than that of the prior art.

Description

technical field [0001] The invention belongs to the field of time-frequency analysis in signal processing, in particular to a multi-component linear frequency modulation (Linear Frequency Modulated, LFM) signal denoising method based on Lv Distribution (LVD). Background technique [0002] Usually, wireless signals are polluted by noise during propagation. After receiving the signal at the receiving end, denoising processing is often required to obtain a signal as clean as possible and reduce noise interference. The LFM signal is not easy to extract from the noise due to its wide bandwidth. Therefore, existing technologies such as: denoising based on short-time Fourier transform, denoising based on Wiener-Willi distribution, denoising based on wavelet transform and weighted filter Techniques such as denoising are not effective in denoising LFM signals. [0003] Especially when the noise power is higher than the signal power, the signal-to-noise ratio (Signal-to-Noise Ratio,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B1/10
CPCH04B1/10H04B1/1027
Inventor 林蓉平罗钐肖泳罗一粟
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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