Exit pupil uniformity optimization method based on polarization body holographic grating

Abstract

The invention discloses an exit pupil uniformity optimization method based on a polarization body holographic grating, and the method comprises the steps: stipulating a limiting function and an optimization target, and determining a to-be-optimized parameter; performing optimization convergence on the to-be-optimized parameters through a self-compiled genetic model algorithm to obtain optimized parameters; after the optimized parameters are subjected to data processing, whether the optimized exit pupil uniformity reaches an optimization target or not is judged, if the optimization target is not reached, the self-compiled genetic model algorithm is repeated until the optimization target is reached, and the parameters reaching the optimization target are obtained; and finely adjusting the parameters which reach the optimization target in a negligible error range to obtain optimized actual parameters. According to the method, the defects that parameters are finely adjusted through experience according to conclusions and experiments are repeated at present are overcome, the uniformity optimization efficiency and accuracy are improved, and compared with an existing optimization algorithm model, the method has the advantages of avoiding falling into a local optimal solution and multi-objective optimization, and it can be ensured that the optimization result is more reliable.

Description

Technical Field

[0001] This invention relates to a method for optimizing the exit pupil uniformity based on a polarizing holographic grating, belonging to the field of optical system simulation technology. Background Technology

[0002] In the field of optical display technology, polarization volume holographic gratings, as a novel optical element, have attracted widespread attention in recent years. Compared with traditional volume holographic gratings, polarization volume holographic gratings possess unique polarization selectivity, enabling independent control of light waves with different polarization states. This characteristic provides a new technical path for improving the performance of near-eye display systems. Especially in applications such as augmented reality (AR) and virtual reality (VR), polarization volume holographic gratings, due to their excellent diffraction characteristics and compact structural design, have become an important choice for achieving high-quality optical displays.

[0003] However, existing polarization-body holographic gratings still face several key challenges in practical applications. First, due to the polarization sensitivity of the grating, light waves of different polarization states often exhibit significant efficiency differences during diffraction, leading to uneven intensity distribution in the exit pupil and affecting display quality. Second, traditional grating design methods rely heavily on empirical adjustments, lacking systematic theoretical guidance and making it difficult to achieve optimal polarization control. Furthermore, light propagation in polarization-body holographic waveguide systems suffers from poor exit pupil uniformity due to multiple propagations within the waveguide and the influence of diffraction efficiency. Moreover, existing optimization schemes typically require the introduction of additional optical components or complex structural designs, which not only increases system complexity but may also lead to increased light energy loss and cost.

[0004] To address these issues, there is an urgent need to develop a new optimization method that can effectively improve the uniformity of the exit pupil intensity while taking into account the diffraction efficiency of the polarizing holographic grating. Summary of the Invention

[0005] Objective: To overcome the problem that the exit pupil uniformity of polarization holographic waveguide structures in existing technologies relies on empirical adjustments without systematic theoretical guidance, this invention provides an exit pupil uniformity optimization method based on polarization volume holographic gratings. This method can calculate waveguide design optimization parameters at the algorithm level, solving the drawbacks of current methods that rely on empirical parameter fine-tuning based on conclusions and repeated experiments, thus improving the efficiency and accuracy of uniformity optimization. Compared with current optimization algorithm models, it has the advantages of avoiding getting trapped in local optima and multi-objective optimization, ensuring more reliable optimization results.

[0006] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for optimizing exit pupil uniformity based on a polarizing holographic grating, specifically including:

[0008] Step 1: Input the required polarizer holographic grating parameters and waveguide system parameters.

[0009] Step 2: Perform simulation imaging and data processing based on the polarization holographic grating parameters and waveguide system parameters to obtain the processed data.

[0010] Step 3: Based on the processed data and the required uniformity of the exit pupil, define the limiting function and optimization objective, and determine the parameters to be optimized.

[0011] Step 4: After the parameters to be optimized are optimized and converged by the self-written genetic model algorithm, the optimized parameters are obtained.

[0012] Step 5: After processing the optimized parameters, determine whether the uniformity of the exit pupil has reached the optimization target. If it has not reached the optimization target, repeat steps 4 and 5 until the optimization target is reached, and then proceed to step 6.

[0013] Step 6: Obtain the parameters after achieving the optimization goal.

[0014] Step 7: Fine-tune the parameters within a negligible error range to achieve the optimization target and obtain the optimized actual parameters.

[0015] As a preferred embodiment, the required polarizing holographic grating parameters and waveguide system parameters are required to ensure complete imaging within the eyebox range, without any discontinuity in the exit pupil or imaging exceeding the eyebox range.

[0016] As a preferred embodiment, the polarizing holographic grating parameters and waveguide system parameters include, but are not limited to, the Bragg period, transverse period, exposure angle during exposure, grating size and shape, grating thickness, and waveguide thickness of the polarizing holographic grating.

[0017] As a preferred embodiment, the condition that the imaging is complete and within the eyebox range is determined by the minimum and maximum transmission angles propagating within the waveguide.

[0018] As a preferred embodiment, the simulation imaging and data processing based on the polarizing holographic grating parameters and waveguide system parameters includes:

[0019] Simulation imaging is performed based on the parameters of the polarizing holographic grating and the waveguide system. After obtaining the simulation results, the illuminance value of each landing point of the light rays in the simulation results is derived. The maximum and minimum illuminance values ​​of the eye box region are calculated based on the illuminance value of each landing point.

[0020] As a preferred option, the relationship between the specified constraint function, the optimization objective, and the parameters to be optimized is set to linear, nonlinear, and multidimensional cross-influence. Furthermore, the constraint function, the optimization objective, and the parameters to be optimized are multi-objective, and the relationship between the optimization objective and the parameters to be optimized is established by inputting a parameter correlation model.

[0021] As a preferred embodiment, the limiting function is set to process accuracy and diffraction efficiency, the optimization target is set to the energy of each light ray exiting the coupling region, and the parameter to be optimized is the thickness of the coupling grating region.

[0022] As a preferred embodiment, the limiting function is set to process accuracy and diffraction efficiency, the optimization target is set to the energy of each light ray exiting the coupling region, and the parameter to be optimized is the duty cycle of the coupling grating region.

[0023] As a preferred option, the uniformity of the exit pupil is determined by comparing the energy density distribution of the irradiance in the output coupling grating region before and after the optimization target.

[0024] As a preferred embodiment, the self-written genetic model algorithm includes determining the limiting function as diffraction efficiency, determining the crossover probability, mutation probability and maximum number of iterations, selecting the initial number of individuals and generating them randomly, and gradually approximating the thickness or duty cycle of the out-coupled grating region when the uniformity is optimal through an optimization strategy, thereby generating the optimal thickness or duty cycle of the out-coupled grating region.

[0025] As a preferred embodiment, the formula for calculating the diffraction efficiency is as follows:

[0026]

[0027] in, Let represent the ideal diffraction efficiency of the beam in the i-th output coupling grating region, where i ranges from 1 to N, and N is the number of regions divided by the output coupling grating. For coupling energy, Let represent the ideal energy at which the a-th coupling will propagate forward and backward. Let represent the ideal energy that will propagate forward and backward during the b-th coupling, where a represents the number of couplings of the incident light and b represents the number of couplings of the incident light, and b > a.

[0028]

[0029]

[0030] Where n represents the total number of times the incident light is coupled out as it propagates through the coupling grating region.

[0031] As a preferred option, the optimized actual parameters are fine-tuned within a negligible error range, including: confirming the accuracy achievable by the current process, comparing the optimized parameters with the process accuracy, and adjusting them within a negligible error range to obtain the optimized actual parameters.

[0032] Beneficial Effects: This invention provides a method for optimizing exit pupil uniformity based on a polarizing holographic grating. This invention offers process guidance for the optimized design of existing polarizing holographic gratings and their waveguide systems, improves imaging quality, reduces process exploration complexity, and provides multi-objective optimization. By combining algorithmic models and process design, this invention is expected to achieve a more compact and efficient optical system, providing technical support for the development of next-generation near-eye display devices. Compared to existing technologies, the advantages of this invention are as follows:

[0033] 1. This invention provides theoretical guidance for the uniformity control of diffractive waveguide structures based on polarizing holographic gratings. It does not rely on empirical control and is closely integrated with the process level, meeting the current accuracy requirements of the process and avoiding the optimization results remaining only at the theoretical level.

[0034] 2. The self-developed genetic optimization model of this invention can avoid getting trapped in local optima, improve the accuracy of the results, and can also optimize multiple factors affecting uniformity at the same time, increasing the optimization dimensionality. Attached Figure Description

[0035] Figure 1 This is a flowchart of a method for optimizing the exit pupil uniformity based on a polarizing holographic grating, provided in the implementation of this invention.

[0036] Figure 2 This is a schematic diagram illustrating the relationship between diffraction efficiency and grating diffraction number when the coupled light energy intensity is consistent, as per the present invention.

[0037] Figure 3 This is a schematic diagram of the waveguide structure before and after optimization obtained in Embodiment 1 of the present invention, wherein, Figure 3 (a) is a schematic diagram of the waveguide structure before optimization. Figure 3 (b) is a schematic diagram of the optimized waveguide structure.

[0038] Figure 4 This is a schematic diagram showing the irradiance distribution before and after optimization obtained from simulation in Embodiment 1 of the present invention, wherein, Figure 4 (a) is a schematic diagram of the irradiance distribution before optimization. Figure 4 (b) is a schematic diagram of the optimized irradiance distribution.

[0039] Figure 5 This is a schematic diagram of the waveguide structure before and after optimization obtained in Embodiment 2 of the present invention, wherein, Figure 5 (a) is a schematic diagram of the waveguide structure before optimization. Figure 5 (b) is a schematic diagram of the optimized waveguide structure.

[0040] Figure 6 This is a schematic diagram showing the irradiance distribution before and after optimization obtained from simulation in Embodiment 2 of the present invention, wherein, Figure 6 (a) is a schematic diagram of the irradiance distribution before optimization. Figure 6 (b) is a schematic diagram of the optimized irradiance distribution. Detailed Implementation

[0041] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0042] The present invention will be further described below with reference to specific embodiments.

[0043] Example 1:

[0044] This embodiment introduces a method for optimizing exit pupil uniformity based on a polarizing holographic grating, such as... Figure 1 As shown, it specifically includes:

[0045] Step 1: Input the required polarizer holographic grating parameters and waveguide system parameters.

[0046] Step 2: Perform simulation imaging and data processing based on the polarization holographic grating parameters and waveguide system parameters to obtain the processed data.

[0047] Step 3: Based on the processed data and the required uniformity of the exit pupil, define the limiting function and optimization objective, and determine the parameters to be optimized.

[0048] Step 4: After the parameters to be optimized are optimized and converged by the self-written genetic model algorithm, the optimized parameters are obtained.

[0049] Step 5: After processing the optimized parameters, determine whether the uniformity of the exit pupil has reached the optimization target. If it has not reached the optimization target, repeat steps 4 and 5 until the optimization target is reached, and then proceed to step 6.

[0050] Step 6: Obtain the parameters after achieving the optimization goal.

[0051] Step 7: Fine-tune the parameters within a negligible error range to achieve the optimization target and obtain the optimized actual parameters.

[0052] Furthermore, the required polarizing holographic grating parameters and waveguide system parameters must be able to form a complete image within the eyebox, without any discontinuity in the exit pupil or the image exceeding the eyebox range.

[0053] Furthermore, specifically, the parameters of the polarization holographic grating and the waveguide system include, but are not limited to, the Bragg period, the transverse period, the exposure angle during the exposure process, the size and shape of the grating, the grating thickness, and the waveguide thickness of the polarization holographic grating.

[0054] Furthermore, specifically, the condition for complete imaging within the eyebox is determined by the minimum and maximum transmission angles propagating within the waveguide, and their expressions are as follows:

[0055]

[0056]

[0057] in: For minimum transmission angle, For the maximum transmission angle, Let be the refractive index of the incident medium, which is typically air. The refractive index of the waveguide, The radius of the exit pupil after collimation. The waveguide thickness is [value].

[0058] Further data processing includes:

[0059] Simulation imaging is performed based on the parameters of the polarizing holographic grating and the waveguide system. After obtaining the simulation results, the illuminance value of each light drop point is derived from the simulation results. The maximum and minimum illuminance values ​​of the eyebox region are calculated based on the illuminance values ​​of each drop point. This is used to calculate the diffraction efficiency of the coupled grating region.

[0060] Furthermore, the relationship between the defined constraint function, the optimization objective, and the parameters to be optimized can be linear, nonlinear, or multidimensional cross-influence. The constraint function, the optimization objective, and the parameters to be optimized can be multi-objective, and the relationship between the optimization objective and the parameters to be optimized is established by inputting a parameter correlation model.

[0061] Specifically, the parameter correlation model is determined by the correlation function between the parameters to be optimized and the optimization objective.

[0062] Furthermore, the uniformity of the exit pupil is determined by comparing the irradiance (energy) density distribution in the output coupling grating region before and after the optimization target. The specific formula for exit pupil uniformity is as follows:

[0063]

[0064] in, For uniformity of exit pupil, This represents the standard deviation of the energy (irradiance) of all outgoing rays in the coupled grating region. This represents the average energy (irradiance) of all outgoing rays in the coupled grating region.

[0065] Furthermore, a self-developed genetic model algorithm was developed, including determining the diffraction efficiency as the limiting function, determining the crossover probability, mutation probability, and maximum number of iterations, selecting and randomly generating the initial number of individuals, and gradually approximating the thickness when uniformity is optimal through optimization strategies such as parallel fitness calculation, elite selection, uniform crossover, and Gaussian mutation, thereby generating the optimal grating thickness.

[0066] like Figure 2 As shown, the horizontal axis represents the total number of regions into which the coupling grating region is divided, where n refers to the nth grating region. The vertical axis corresponds to the diffraction efficiency. As the number of diffractions of the grating increases, the diffraction efficiency required to achieve uniform coupled light energy also gradually increases. The relationship between the two is used to control the uniformity of the coupling grating region.

[0067] Its diffraction efficiency can be expressed as:

[0068]

[0069]

[0070]

[0071] The formula itself is based on the assumption that the coupling energy is... Preferably, 1, dividing the output coupling grating into N regions, Let represent the ideal diffraction efficiency of the beam in the i-th output coupling grating region, and let a and b represent the a-th and b-th outputs of the incident light, respectively. Let represent the ideal energy at which the a-th coupling will propagate forward and backward. Let represent the ideal energy at which the b-th coupling will propagate forward and backward, and n represent the total number of times the incident light will be coupled out during its propagation in the coupling grating region.

[0072] Furthermore, the optimized actual parameters are fine-tuned within a negligible error range, including: confirming the accuracy achievable by the current process, comparing the optimized parameters with the process accuracy, and adjusting them within a negligible error range to obtain the optimized actual parameters.

[0073] Example 2:

[0074] This embodiment introduces a simulation of the diffraction efficiency control of the grating thickness in the out-coupling region of a one-dimensional expanded pupil polarized holographic waveguide structure using an out-pupil uniformity optimization method based on a polarized holographic grating. The out-pupil uniformity before and after optimization is compared.

[0075] This embodiment first constructs a one-dimensional pupil-expanding polarizing holographic diffraction waveguide structure. The waveguide dimensions are set to 60mm × 40mm, with a refractive index of 1.67 and a thickness of 1mm. The input coupling grating dimensions are set to 25mm × 5mm with a thickness of 4µm, and the output coupling grating dimensions are set to 30mm × 20mm with a thickness of 3µm. Optimization mainly targets the output coupling region; the parameters of the input coupling grating remain unchanged during optimization. Figure 3 As shown, (1) is a schematic diagram of the original diffractive waveguide structure before optimization, and (2) is a schematic diagram of the waveguide structure after optimization by a self-written genetic optimization algorithm model with controlled diffraction efficiency of the partitioned grating thickness.

[0076] The coupling region was divided into three equal regions along the light propagation direction, each with a width of 10 mm. The grating thickness of each coupling region was set as the parameter to be optimized, while accuracy and diffraction efficiency were set as constraint functions. The optimization objective was set as the energy of each ray exiting the coupling region. The optimization algorithm was deployed in a ray tracing algorithm for calculation. The optimized region thicknesses were 0.5 μm, 0.9 μm, and 2.4 μm, respectively. The illuminance distribution of the coupling grating region collected by Zemax software was used to represent the energy density distribution of the coupling grating region, thereby characterizing the uniformity of the exit pupil. Figure 4 As shown, (a) is the original one-dimensional diffracted waveguide illuminance distribution, and (b) is the illuminance distribution after optimization by a self-written genetic optimization algorithm model with control of the diffraction efficiency of the partitioned grating thickness. The distribution in the figure is the logarithm of the illuminance value.

[0077] Example 3:

[0078] This embodiment introduces a simulation of the output pupil uniformity optimization method based on a polarizing holographic grating to control the duty cycle diffraction efficiency of a one-dimensional expanding pupil polarizing holographic diffraction waveguide structure, and compares the output pupil uniformity before and after optimization.

[0079] This embodiment constructs the same one-dimensional pupil-expanding polarizer holographic diffraction waveguide structure as the previous embodiment. The output coupling region is divided into three equal regions along the light propagation direction, each with a width of 10 mm. By reducing the width of the output coupling grating region near the input coupling grating, the duty cycle between the non-grating region and the grating region in each output coupling region is obtained. The duty cycle of each region is set as the parameter to be optimized, while accuracy and diffraction efficiency are set as constraint functions. The optimization objective is set as the energy of each light ray exiting the coupling region. The remaining grating parameters are consistent with those in the first embodiment. The optimization algorithm is deployed in the ray tracing algorithm for calculation. The optimized grating region widths are 4.2 mm, 4.8 mm, and 7.8 mm, respectively. The optimization mainly targets the output coupling region; the parameters of the input coupling grating remain unchanged during the optimization process. Figure 5 As shown, (a) is a schematic diagram of the original diffractive waveguide structure before optimization, and (b) is a schematic diagram of the waveguide structure with partitioned grating duty cycle diffraction efficiency after optimization by a self-written genetic optimization algorithm model.

[0080] Similarly, the uniformity of the exit pupil is characterized by the illuminance distribution in the region of the coupling grating, such as... Figure 6 As shown, (a) is the original one-dimensional diffracted waveguide illuminance distribution, and (b) is the illuminance distribution after optimization by a self-written genetic optimization algorithm model with control of the duty cycle diffraction efficiency of the partitioned grating. The distribution in the figure is the logarithm of the illuminance value.

[0081] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing exit pupil uniformity based on a polarizing volume holographic grating, characterized in that: Specifically, it includes: Step 1: Input the required polarizing holographic grating parameters and waveguide system parameters; Step 2: Perform simulation imaging and data processing based on the polarization holographic grating parameters and waveguide system parameters to obtain the processed data; Step 3: Based on the processed data and the required uniformity of the exit pupil, define the limiting function and optimization objective, and determine the parameters to be optimized; Step 4: After the parameters to be optimized are optimized and converged by the self-written genetic model algorithm, the optimized parameters are obtained; Step 5: After processing the optimized parameters, determine whether the uniformity of the exit pupil has reached the optimization target. If the optimization target has not been reached, repeat steps 4 and 5 until the optimization target is reached, and then proceed to step 6. Step 6: Obtain the parameters after achieving the optimization goal; Step 7: Fine-tune the parameters within a negligible error range to achieve the optimization target and obtain the optimized actual parameters.

2. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: The required polarizing holographic grating parameters and waveguide system parameters must be able to form a complete image within the eyebox, without any discontinuity in the exit pupil or the image exceeding the eyebox range.

3. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: The parameters of the polarizing holographic grating and the waveguide system include, but are not limited to, the Bragg period, the transverse period, the exposure angle during the exposure process, the size and shape of the grating, the grating thickness, and the waveguide thickness of the polarizing holographic grating.

4. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: The simulation imaging and data processing based on the polarizer holographic grating parameters and waveguide system parameters includes: Simulation imaging is performed based on the parameters of the polarizing holographic grating and the waveguide system. After obtaining the simulation results, the illuminance value of each landing point of the light rays in the simulation results is derived. The maximum and minimum illuminance values ​​of the eye box region are calculated based on the illuminance value of each landing point.

5. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: The relationship between the defined constraint function, the optimization objective, and the parameters to be optimized is set as linear, nonlinear, and multidimensional cross-influence. Furthermore, the constraint function, the optimization objective, and the parameters to be optimized are multi-objective, and the relationship between the optimization objective and the parameters to be optimized is input through a parameter correlation model.

6. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 5, characterized in that: The limiting function is set as process accuracy and diffraction efficiency, the optimization target is set as the energy of each light ray exiting the coupling region, and the parameter to be optimized is the thickness of the coupling grating region.

7. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 5, characterized in that: The limiting function is set as process accuracy and diffraction efficiency, the optimization target is set as the energy of each light ray exiting the coupling region, and the parameter to be optimized is the duty cycle of the coupling grating region.

8. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: Whether the uniformity of the exit pupil has reached the optimization target is determined by comparing the energy density distribution of the irradiance in the output coupling grating region before and after.

9. The exit pupil uniformity optimization method based on a polarizing holographic grating according to claim 1, characterized in that: The self-written genetic model algorithm includes determining the diffraction efficiency as the limiting function, determining the crossover probability, mutation probability and the maximum number of iterations, selecting the initial number of individuals and generating them randomly, and gradually approximating the thickness or duty cycle of the out-coupled grating region when the uniformity is optimal through an optimization strategy, thereby generating the optimal thickness or duty cycle of the out-coupled grating region.

10. A method for optimizing exit pupil uniformity based on a polarizing holographic grating according to any one of claims 6, 7, or 9, characterized in that: The formula for calculating the diffraction efficiency is as follows: ； in, To represent the ideal diffraction efficiency of the beam in the i-th output coupling grating region, where i ranges from 1 to N, and N is the number of regions divided by the output coupling grating; For coupling energy, Let represent the ideal energy at which the a-th coupling will propagate forward and backward. Let represent the ideal energy that will propagate forward and backward during the b-th coupling, where a represents the number of couplings of the incident light and b represents the number of couplings of the incident light, and b > a. ； ； Where n represents the total number of times the incident light is coupled out as it propagates through the coupling grating region.

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