• High Power Laser Science and Engineering
  • Vol. 9, Issue 2, 02000e15 (2021)
Xinlei Qian1、2, Wei Fan1、2、*, Xinghua Lu1, and Xiaochao Wang1
Author Affiliations
  • 1National Laboratory on High Power Laser and Physics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai201800, China
  • 2Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing100049, China
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    DOI: 10.1017/hpl.2021.2 Cite this Article Set citation alerts
    Xinlei Qian, Wei Fan, Xinghua Lu, Xiaochao Wang. Smooth pulse recovery based on hybrid wavelet threshold denoising and first derivative adaptive smoothing filter[J]. High Power Laser Science and Engineering, 2021, 9(2): 02000e15 Copy Citation Text show less

    Abstract

    Based on the pulse-shaping unit in the front end of high-power laser facilities, we propose a new hybrid scheme in a closed-loop control system including wavelet threshold denoising for pretreatment and a first derivative adaptive smoothing filter for smooth pulse recovery, so as to effectively restrain the influence of electrical noise and FM-to-AM modulation in the time–power curve, and enhance the calibration accuracy of the pulse shape in the feedback control system. The related simulation and experiment results show that the proposed scheme can obtain a better shaping effect on the high-contrast temporal shape in comparison with the cumulative average algorithm and orthogonal matching pursuit algorithm combined with a traditional smoothing filter. The implementation of the hybrid scheme mechanism increased the signal-to-noise ratio of the laser pulse from about 11 dB to 30 dB, and the filtered pulse is smooth without modulation, with smoothness of about 98.8%.
    \begin{align}f(t)\in L{(R)}^2\iff \int {\left|f(t)\right|}^2\mathrm{d}t<+\infty,\end{align}((1))

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    \begin{align}{C}_{\varPsi }=\underset{-\infty }{\overset{+\infty }{\int }}{\left|\omega \right|}^{-1}{\left|\hat{\varPsi}(t)\right|}^2\ \mathrm{d}\omega <\infty.\end{align}((2))

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    \begin{align}{\varPsi}_{a,b}(t)={\left|a\right|}^{-1/2}\varPsi \left(\frac{x-b}{a}\right),\end{align}((3))

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    \begin{align}\left({W}_{\varPsi}\right)\left(a,b\right)=\left\langle f,{\varPsi}_{a,b}\right\rangle ={\left|a\right|}^{-1/2}{\int}_{\!\!-\infty}^{+\infty }f(t)\overline{\varPsi \left(\frac{t-b}{a}\right)\ \mathrm{d}t}.\end{align}((4))

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    \begin{align}\mathrm{s}(t)=g(t)+n(t),\end{align}((5))

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    \begin{align}V=1\bigg/\left(1+F{\sin}^2\frac{\delta }{2}\right),\end{align}((6))

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    \begin{align}F=4r/{\left(1-r\right)}^2,\end{align}((7))

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    \begin{align}D=\left|\frac{\left({y}_1-{y}_0\right)}{\left({x}_1-{x}_0\right)}\right|.\end{align}((8))

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    \begin{align}W=\frac{q}{D},\end{align}((9))

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    \begin{align}{S}_{y_1}=\left({y}_0+W {y}_1\right)/\left(1+W\right).\end{align}((10))

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    \begin{align}R=\frac{\sum_{i=1}^{n-1}{\left[{h}_1\left(i+1\right)-{h}_1(i)\right]}^2}{\sum_{i=1}^{n-1}{\left[h\left(i+1\right)-h(i)\right]}^2},\end{align}((11))

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    \begin{align}\mathrm{y}=P\cdot x=\sum_k{\phi}_k\cdot {x}_k={y}_{\mathrm{omp}},\end{align}((12))

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    \begin{align}{\mathit{s}}_1=\left\{\!\!\begin{array}{c}k,\left|k\right|>T,\\{}0,\left|k\right|\le T,\end{array}\right.\end{align}((13))

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    \begin{align}{s}_2=\left\{\!\!\begin{array}{l}\operatorname{sign}(k)\left(\left|k\right|-T\right),\left|k\right|>T,\\{}0,\left|k\right|\le T,\end{array}\right.\end{align}((14))

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    Xinlei Qian, Wei Fan, Xinghua Lu, Xiaochao Wang. Smooth pulse recovery based on hybrid wavelet threshold denoising and first derivative adaptive smoothing filter[J]. High Power Laser Science and Engineering, 2021, 9(2): 02000e15
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