• Infrared and Laser Engineering
  • Vol. 51, Issue 3, 20220007 (2022)
Yushi Zhao, Wenjun He, Zhiying Liu, and Yuegang Fu
Author Affiliations
  • School of Opto-electronic Engineering, Changchun University of Science and Technology, Changchun 130022, China
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    DOI: 10.3788/IRLA20220007 Cite this Article
    Yushi Zhao, Wenjun He, Zhiying Liu, Yuegang Fu. Development of convex blazed grating in coded aperture spectral imager[J]. Infrared and Laser Engineering, 2022, 51(3): 20220007 Copy Citation Text show less

    Abstract

    Aiming at the performance requirements of a DMD-based Offner spectral imager encoding in spectral dimension for a convex blazed grating, a macro-micro integrated optimization design method for convex blazed gratings was proposed. The three-dimensional polarization ray tracing algorithm was used to organically integrate the optical design of the Offner system in macro-level and the groove design of the convex blazed grating in micro-level. The composition and working principle of the coded aperture Offner spectral imaging system were introduced, and a MWIR convex blazed grating with an average diffraction efficiency of 85.47% was designed according to the requirements of the system. On this basis, a convex blazed grating with curvature radius of 120 mm, grating period of 99.945 μm, blazed angle of 1.1783°, groove depth of 1.834 μm was successfully fabricated by using an ultra-precision single-point diamond lathe. The test results show that in the spectral range of 3-5 μm, the maximum diffraction efficiency is 93.46% and the average diffraction efficiency is 84.29%, which is in good agreement with the theoretical design value. Thus, the proposed design method of the convex blazed grating is verified to be effective and valuable.
    $ {R_{\rm{M}}} = 2{R_{\rm{G}}} $(1)

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    $ {R_{\rm{G}}} = \frac{{d\delta }}{{m\left( {{\lambda _2} - {\lambda _1}} \right)}} $(2)

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    $ {{\boldsymbol{E}}_{out}} = {{\boldsymbol{P}}_{{\text{total}}}} \cdot {{\boldsymbol{E}}_{in}} $(3)

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    $ {{\boldsymbol{P}}_{total}} = \prod\limits_{q = N, - 1}^1 {{{\boldsymbol{P}}_q}} $(4)

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    $ {{\boldsymbol{P}}_q} = {O_{out,q}} \cdot {J_q} \cdot O_{in,q}^{ - 1} $(5)

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    $ {O_{out,q}} = \left( {\begin{array}{*{20}{c}} {\hat s_{x,q}'}&{\hat p_{x,q}'}&{{{\hat k}_{x,q}}}\\ {\hat s_{y,q}'}&{\hat p_{y,q}'}&{{{\hat k}_{y,q}}}\\ {\hat s_{z,q}'}&{\hat p_{z,q}'}&{{{\hat k}_{z,q}}} \end{array}} \right) $(6)

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    $ {J_q} = \left( {\begin{array}{*{20}{c}} {{\alpha _{s,q}}}&0&0 \\ 0&{{\alpha _{p,q}}}&0 \\ 0&0&1 \end{array}} \right) $(7)

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    $ O_{in,q}^{ - 1} = \left( {\begin{array}{*{20}{c}} {{{\hat s}_{x,q}}}&{{{\hat s}_{y,q}}}&{{{\hat s}_{z,q}}} \\ {{{\hat p}_{x,q}}}&{{{\hat p}_{y,q}}}&{{{\hat p}_{z,q}}} \\ {{{\hat k}_{x,q - 1}}}&{{{\hat k}_{y,q - 1}}}&{{{\hat k}_{z,q - 1}}} \end{array}} \right) $(8)

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    $ {\hat s_q} = \dfrac{{{{\hat k}_{q - 1}} \times {{\hat k}_q}}}{{\left| {{{\hat k}_{q - 1}} \times {{\hat k}_q}} \right|}}\text{,}{\hat p_q} = {\hat k_{q - 1}} \times {\hat s_q}\text{,}\hat p_q' = {\hat k_q} \times {\hat s_q}\text{,} $(9)

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    $ d\left( {\sin i - sin\theta } \right) = m{\lambda _B} $(10)

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    $ 2\gamma = \theta - i $(11)

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    $ h\left( {\tan \gamma + \dfrac{1}{{\tan \gamma }}} \right) = d $(12)

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    $ {{\boldsymbol{\eta}} _G} = \dfrac{{\displaystyle\sum\limits_{\kappa = 1}^K {\displaystyle\sum\limits_{\lambda = {\lambda _1}}^{{\lambda _2}} {\displaystyle\sum\limits_{m = 1}^M {\displaystyle\sum\limits_{n = 1}^N {{\boldsymbol{\eta}} _{m,n}^{\lambda ,\kappa }} } } } }}{{K \times Y \times m \times n}} $(13)

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    $ \left\{ {\begin{array}{*{20}{l}} {{\boldsymbol{P}} = \left[ {{{\boldsymbol{X}}^t}} \right],{{\boldsymbol{X}}^t} = \left[ {{\gamma _t},{h_t}} \right]} \\ {{{\boldsymbol{\eta }}_g} = F\left( {\left[ {{\boldsymbol{X}}_g^t} \right]} \right) = \left[ {{\boldsymbol{\eta}} _g^t} \right]} \\ {{{\boldsymbol{\eta}}_t} = F\left( {\left[ {{\boldsymbol{X}}_t^g} \right]} \right) = \left[ {{\boldsymbol{\eta}} _t^g} \right]} \end{array}} \right. $(14)

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    $ \left\{\begin{array}{c}{{\boldsymbol{\eta}} }_{g}^{best}=\mathrm{max}\left({\boldsymbol{\eta}}_{g}\right)=F\left({{\boldsymbol{X}}}_{g}^{best}\right)\\ {{\boldsymbol{\eta}}}_{t}^{best}=\mathrm{max}\left({\boldsymbol{\eta}}_{t}\right)=F\left({{\boldsymbol{X}}}_{t}^{best}\right)\end{array}\right. $(15)

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    $ \left\{ {\begin{array}{*{20}{l}} {\Delta _g^t = {\boldsymbol{X}}_{g - 1}^t - {\boldsymbol{X}}_g^t} \\ {\Delta _g^{best} = {\boldsymbol{X}}_g^t - {\boldsymbol{X}}_g^{best}} \\ {\Delta _t^{best} = {\boldsymbol{X}}_g^t - {\boldsymbol{X}}_t^{best}} \end{array}} \right. $(16)

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    $ \left\{ {\begin{array}{*{20}{l}} {\Delta _{g + 1}^t = {k_1}\Delta _g^t + {k_2}\Delta _g^{best} + {k_3}\Delta _t^{best}} \\ \begin{gathered} {\boldsymbol{X}}_{g + 1}^t = {\boldsymbol{X}}_g^t + \Delta _g^t \hfill \\ {{\boldsymbol{P}}_{g + 1}} = [{\boldsymbol{X}}_{g + 1}^t] \hfill \\ \end{gathered} \end{array}} \right. $(17)

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    $ {{\boldsymbol{\eta}} _\lambda } = \dfrac{{{P_{G,\lambda }}}}{{r_\lambda ^2 \cdot {P_{0,\lambda }}}} $(18)

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    Yushi Zhao, Wenjun He, Zhiying Liu, Yuegang Fu. Development of convex blazed grating in coded aperture spectral imager[J]. Infrared and Laser Engineering, 2022, 51(3): 20220007
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