A method for optimizing the optical performance of a cooled mid-wave infrared zoom lens

Abstract

This application relates to the field of infrared optical lens technology and discloses a method for optimizing the optical performance of a cooled mid-wave infrared zoom lens, comprising the following steps: obtaining the basic optical parameters of the cooled mid-wave infrared zoom lens to be optimized within the full focal length range, and constructing a multi-focal-length optical performance benchmark library; based on the multi-focal-length optical performance benchmark library, performing a pre-evaluation of the cold reflection effect of the lens, identifying optical surfaces with a risk of cold reflection and performing pre-optimization; by constructing a multi-focal-length optical performance benchmark library and conducting a pre-evaluation of the cold reflection effect, the high-risk optical surfaces of the cooled lens that are prone to cold reflection are identified in advance, and pre-optimization is performed by combining coating adjustment and angle fine-tuning, which solves the problem that existing methods do not specifically address the unique defects of cooled lenses and are prone to cold spot ghosting, thereby improving the basic imaging clarity and contrast of the lens from the source.

Description

Technical Field

[0001] This application relates to the field of infrared optical lens technology, and in particular to a method for optimizing the optical performance of a cooled mid-wave infrared zoom lens. Background Technology

[0002] Cooled mid-wave infrared zoom lenses can acquire clear images in environments where ordinary optical lenses struggle to function properly, such as at night, in fog, or during sandstorms. They are widely used in security monitoring, forest fire prevention, power line inspection, and industrial testing. With the rapid development of related industries, increasingly higher demands are being placed on the imaging accuracy, zoom stability, and performance consistency of these lenses in mass production.

[0003] Currently, there are some significant shortcomings in the optical performance optimization methods for cooled mid-wave infrared zoom lenses. First, they fail to specifically address the unique cold reflection problem of cooled infrared lenses. Reflected light from the optical surface, after entering the low-temperature detector, easily forms cold spots or ghosting in the image, directly affecting image clarity and contrast. Second, existing optimization methods mostly only adjust a few isolated focal lengths such as short, medium, and long focal lengths, without considering the changes in optical characteristics at different focal lengths during zooming. This can easily lead to uneven image quality across the entire focal length range, with some focal lengths exhibiting blurred edges and reduced contrast. Furthermore, there is currently no standardized batch optimization process. Production relies mainly on the experience of technical personnel for adjustments, resulting in low optimization efficiency, high production costs, and difficulty in ensuring consistent lens performance across mass production. Summary of the Invention

[0004] The optical performance optimization method for a cooled mid-wave infrared zoom lens provided in this application adopts the following technical solution:

[0005] A method for optimizing the optical performance of a cooled mid-wave infrared zoom lens includes the following steps: obtaining the basic optical parameters of the cooled mid-wave infrared zoom lens to be optimized across the entire focal length range, and constructing a multi-focal-length optical performance benchmark library; based on the multi-focal-length optical performance benchmark library, performing a pre-evaluation of the cold reflection effect of the lens, identifying optical surfaces with cold reflection risks and performing pre-optimization; dividing the entire focal length range into multiple continuous focal length segments, performing tangential and arc modulation transfer function tests on the lens within each focal length segment, evaluating the imaging uniformity of each focal length segment and performing targeted optimization; performing a continuous zoom test across the entire focal length range on the optimized lens, detecting the image plane drift during the zoom process, performing dynamic compensation adjustments, and generating a lens optical performance optimization priority table.

[0006] Preferably, the construction process of the multi-focal length optical performance benchmark library is as follows: select typical focal lengths of the lens to be optimized, including the short focal length, medium focal length and long focal length, and obtain the lens structure parameters, optical material parameters and initial imaging parameters at each focal length; perform full field-of-view scanning tests on the lens at each focal length, record the basic imaging data at different field-of-view positions, and store all parameters and data after standardization processing to form a multi-focal length optical performance benchmark library.

[0007] Preferably, the specific process of the pre-evaluation of the cold reflection effect is as follows: based on the optical surface parameters in the multi-focal-length optical performance benchmark library, calculate the reflectivity of each optical surface under the normal incident condition of the 3-5μm mid-wave infrared band; compare the reflectivity of each optical surface with the preset cold reflection threshold; if the reflectivity of a certain optical surface is greater than or equal to the cold reflection threshold, then mark the optical surface as a high-risk optical surface.

[0008] Preferably, the process of pre-optimizing optical surfaces with cold reflection risk is as follows: adjusting the coating parameters of high-risk optical surfaces to reduce their reflectivity in the 3-5μm band; adjusting the tilt angle of high-risk optical surfaces without compromising the basic imaging quality of the lens to make the reflected light deviate from the imaging area of ​​the cold detector; repeating the pre-evaluation of cold reflection effect until the reflectivity of all optical surfaces is less than the cold reflection threshold.

[0009] Preferably, the process of dividing the full focal length range into multiple consecutive focal length segments is as follows: based on the zoom curve characteristics of the lens, the full focal length range is divided into three consecutive focal length segments: short focal length segment, medium focal length segment, and long focal length segment, and each focal length segment contains at least two consecutive typical focal length points.

[0010] Preferably, the specific process of evaluating the imaging uniformity of each focal length segment and performing targeted optimization is as follows: For each typical focal point within each focal length segment, obtain the tangential modulation transfer function (TMF) and arc modulation transfer function (AMF) values ​​for the center field of view, 0.7 field of view, and edge field of view, respectively; calculate the tangential-arc difference value for the same focal point within the same field of view; if the tangential-arc difference value is greater than or equal to a preset tangential-arc difference threshold, then finely adjust the position of the optical lens group corresponding to that focal point and field of view along the optical axis; repeat the test and adjustment until the tangential-arc difference value for all focal points in all fields of view within the focal length segment is less than the tangential-arc difference threshold.

[0011] Preferably, the tangential difference value is calculated as follows: the absolute value of the difference between the tangential modulation transfer function value and the arc modulation transfer function value at the same focal length point in the same field of view is obtained.

[0012] Preferably, the process of detecting and dynamically compensating for image plane drift during zooming is as follows: Under the same object distance and ambient temperature conditions, the lens is controlled to continuously zoom from the short focal length end to the long focal length end, and image plane position data is collected once every preset focal length interval to calculate the image plane drift between adjacent focal length points; if the image plane drift in a certain focal length interval is greater than or equal to a preset drift threshold, the zoom cam curve parameters corresponding to that focal length interval are adjusted to compensate for the image plane drift; the continuous zoom test and adjustment are repeated until the image plane drift in the entire focal length range is less than the drift threshold.

[0013] Preferably, the process of generating the lens optical performance optimization priority table is as follows: 1) Calculate the number of optical lens groups requiring adjustment and the axial displacement adjustment range within each focal length segment, and calculate the optimization difficulty coefficient for each focal length segment; 2) Calculate the number of cold reflection adjustments for each optical surface and the number of image plane drift adjustments for each focal length interval, and, combined with the degree of influence of each optimization step on the final image quality, calculate the influence weight of each optimization step; 3) Generate the lens optical performance optimization priority table in order of optimization difficulty coefficient from high to low and influence weight from large to small.

[0014] Preferably, the method further includes the following steps: based on the generated lens optical performance optimization priority table, establish a batch optimization process parameter library for lenses of the same model, and perform cold reflection pre-optimization, imaging uniformity optimization, and image plane drift dynamic compensation adjustment on the batch-produced lenses of the same model in sequence according to the priority table.

[0015] In summary, this application includes the following beneficial technical effects:

[0016] 1. By constructing a multi-focal-length optical performance benchmark library and conducting a pre-evaluation of the cold reflection effect, high-risk optical surfaces that are prone to cold reflection in cooled lenses are identified in advance. Pre-optimization is carried out by combining coating adjustment and angle fine-tuning, which solves the problem that existing methods do not specifically address the unique defects of cooled lenses and are prone to cold spot ghosting, thereby improving the basic image sharpness and contrast of the lens from the source.

[0017] 2. By dividing the continuous focal length segments according to the characteristics of the zoom curve and carrying out field-of-view tangential equalization optimization, covering the entire focal length and field of view, and correcting the difference between tangential and arc imaging by fine-tuning the position of the corresponding lens group, the problem of edge blurring in some focal length segments and uneven imaging quality across the entire focal length caused by traditional single-point optimization is solved, ensuring that the imaging effect of the lens is stable and consistent under different usage conditions.

[0018] 3. By generating an optimization priority table and establishing a batch optimization process parameter library, the optimization experience of a single lens is transformed into a standardized production process. This solves the problems of existing methods that rely too much on the personal experience of technical personnel, have low optimization efficiency, and have large performance differences in batch products. While ensuring optimization quality, it significantly improves production efficiency and reduces debugging costs. Attached Figure Description

[0019] Figure 1 Core flowchart of cold reflection pre-optimization.

[0020] Figure 2 Flowchart of imaging equalization and batch optimization. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0022] Reference Figure 1-2 This invention provides a method for optimizing the optical performance of a cooled mid-wave infrared zoom lens, comprising the following steps: obtaining the basic optical parameters of the cooled mid-wave infrared zoom lens to be optimized across the entire focal length range, and constructing a multi-focal-length optical performance benchmark library; based on the multi-focal-length optical performance benchmark library, performing a pre-evaluation of the cold reflection effect of the lens, identifying optical surfaces with cold reflection risks and performing pre-optimization; dividing the entire focal length range into multiple consecutive focal length segments, performing tangential and arc modulation transfer function tests on the lens within each focal length segment, evaluating the imaging uniformity of each focal length segment and performing targeted optimization; performing a continuous zoom test across the entire focal length range on the optimized lens, detecting the image plane drift during the zoom process, performing dynamic compensation adjustments, and generating a lens optical performance optimization priority table.

[0023] First, an optical inspection system consisting of a collimator, an infrared resolution board, and a cooled infrared detector is used to collect basic data for the lens to be optimized at all focal lengths, from the short focal length to the long focal length. This includes the curvature, thickness, spacing, and refractive index of each lens in the front fixed group, zoom group, compensation group, and rear fixed group, as well as parameters such as initial image sharpness and contrast at different positions. This data is then organized and stored to form a multi-focal-length optical performance benchmark library, providing a standardized reference for all subsequent optimization steps. Next, based on the parameters of each optical surface in the benchmark library, the reflection of these optical surfaces in the mid-infrared band is calculated and analyzed in advance. High-risk optical surfaces that may reflect light back to the cooled detector are identified, and these surfaces are prioritized for adjustment to reduce cold reflection defects at the source. Next, based on the movement patterns of the zoom group and compensation group during lens zooming, the entire zoom range was divided into several consecutive focal length segments with similar optical characteristics. For the lens within each focal length segment, the imaging transmission capabilities in both tangential and arc directions were tested at the center, middle, and edge field of view positions. The imaging differences at each position were compared and analyzed, and corrections were made for positions with excessive differences by fine-tuning the positions of the corresponding lens groups. Finally, the zoom cam was rotated by a drive motor to control the lens to continuously and smoothly zoom from the short focal length end to the long focal length end. Throughout the process, an infrared detector was used to collect image plane position data in real time, and the image plane offset between adjacent focal length points was calculated. For focal length ranges with excessive offsets, compensation was made by adjusting the curve parameters of the zoom cam to ensure that the image plane remained stable throughout the zoom process. After completing all optimization steps, the difficulty of adjusting each optimization step and its impact on the final image quality were statistically analyzed. A priority table for lens optical performance optimization was generated, arranged in order of difficulty from easiest to easiest and impact from largest to smallest.

[0024] By constructing a unified benchmark library, the accuracy and consistency of the optimization data are ensured. Pre-optimization is first performed on the cold reflection problem unique to cooled lenses, which can fundamentally eliminate imaging cold spots and ghosting defects. Imaging uniformity optimization at different focal lengths and fields of view ensures uniform imaging quality across the entire focal length and field of view. Image plane drift compensation during continuous zoom across the entire focal length solves the imaging blur problem during zooming. The generated optimization priority table can guide subsequent optimization work in an orderly manner, avoid blind debugging, and significantly improve optimization efficiency and effect.

[0025] In a preferred embodiment, the construction process of the multi-focal length optical performance benchmark library is as follows: select typical focal lengths of the lens to be optimized, including the short focal length, medium focal length, and long focal length, and obtain the lens structure parameters, optical material parameters, and initial imaging parameters at each focal length; perform a full field-of-view scanning test on the lens at each focal length, record the basic imaging data at different field-of-view positions, and store all parameters and data after standardization processing to form a multi-focal length optical performance benchmark library.

[0026] When constructing the benchmark library, three typical focal lengths—short focal length, medium focal length, and long focal length—were selected to best represent the optical characteristics of the lens. At these three focal lengths, optical measuring instruments were used to measure structural parameters such as the radius of curvature, center thickness, and air gap of each lens element, as well as optical material parameters such as refractive index and transmittance of each lens material in the 3-5μm mid-wave infrared band. Simultaneously, an infrared imaging system was used to acquire initial imaging images of the lens at these three focal lengths, obtaining initial imaging parameters such as imaging resolution and contrast. Then, the lens was controlled to perform point-by-point scanning tests from the center field of view to the edge field of view at each typical focal length, recording imaging data at different field-of-view positions to ensure coverage of the entire imaging area of ​​the lens. Finally, all acquired structural parameters, material parameters, and imaging data were converted into a standard format using a unified mathematical method to eliminate errors caused by different measuring equipment and conditions. The standardized data was then stored in a database, forming a multi-focal-length optical performance benchmark library.

[0027] By selecting representative focal length points and conducting full-field scanning tests, the optical characteristics of the lens under different focal lengths and fields of view can be comprehensively and accurately reflected. Standardization ensures the comparability and consistency of the data, and the constructed benchmark library provides reliable basic data support for all subsequent optimization steps, avoiding optimization deviations caused by inaccurate data.

[0028] In a preferred embodiment, the specific process of the pre-evaluation of the cold reflection effect is as follows: based on the optical surface parameters in the multi-focal-length optical performance benchmark library, calculate the reflectivity of each optical surface under the normal incident condition of the 3-5μm mid-wave infrared band; compare the reflectivity of each optical surface with a preset cold reflection threshold; if the reflectivity of a certain optical surface is greater than or equal to the cold reflection threshold, then mark the optical surface as a high-risk optical surface.

[0029] Cooled mid-wave infrared lenses operate at low temperatures. When light reflected from an optical surface inside the lens enters the cryogenic detector, it can create cold spots or ghosting in the image. During cold reflection pre-evaluation, parameters such as curvature and material refractive index of each optical surface are extracted from a benchmark library. Based on the law of optical reflection, the reflectivity of each optical surface in the 3-5μm mid-wave infrared band under perpendicular incidence is calculated. This band is the operating band of the cooled mid-wave infrared lens, and normal incidence is the most likely condition to produce strong reflection. Then, based on industry experience and lens performance requirements, a cold reflection threshold is pre-set. The calculated reflectivity of each optical surface is compared to this threshold. Optical surfaces with reflectivity greater than or equal to the threshold indicate that the reflected light intensity is sufficient to form significant cold reflection defects in the image. Therefore, these optical surfaces are marked as high-risk optical surfaces and require focused optimization.

[0030] By specifically calculating the reflectivity of optical surfaces under the lens's operating wavelength and the most unfavorable incident conditions, it is possible to accurately identify all high-risk optical surfaces that may produce cold reflection defects, lock in the optimization target in advance, and avoid the need for a complete rework after discovering cold reflection problems later, thus greatly improving the targeting and efficiency of optimization.

[0031] In a preferred embodiment, the process of pre-optimizing the optical surfaces with cold reflection risk is as follows: adjusting the coating parameters of the high-risk optical surfaces to reduce their reflectivity in the 3-5μm band; adjusting the tilt angle of the high-risk optical surfaces without compromising the basic imaging quality of the lens to make the reflected light deviate from the imaging area of ​​the cold detector; repeating the cold reflection effect pre-evaluation until the reflectivity of all optical surfaces is less than the cold reflection threshold.

[0032] For optical surfaces marked as high-risk, optimization is first achieved by adjusting coating parameters. This involves changing the number of antireflective coating layers, the thickness of each layer, and the material ratio to reduce the reflectivity of the optical surface in the 3-5μm mid-infrared band, fundamentally reducing the intensity of reflected light. If adjusting the coating still fails to reduce the reflectivity below the cold reflection threshold, or if adjusting the coating introduces other adverse effects, then, while ensuring the overall image quality of the lens is not significantly affected, the tilt angle of the optical surface is fine-tuned to change the propagation direction of the reflected light, preventing it from illuminating the effective imaging area of ​​the cooled detector and thus avoiding cold reflection defects in the image. After one optimization, the reflectivity of all optical surfaces is recalculated, and a pre-assessment of the cold reflection effect is performed again to confirm whether there are still high-risk optical surfaces. If so, optimization continues until the reflectivity of all optical surfaces is below the cold reflection threshold.

[0033] By combining coating adjustment and angle fine-tuning, the cold reflection problem under different conditions can be effectively solved. This can fundamentally reduce the intensity of reflected light and prevent reflected light from entering the detector by changing the direction of light propagation. The two methods complement each other and can completely eliminate cold reflection defects without compromising the basic imaging quality of the lens, thus ensuring the clarity of the lens image.

[0034] In a preferred embodiment, the process of dividing the full focal length range into multiple consecutive focal length segments is as follows: based on the zoom curve characteristics of the lens, the full focal length range is divided into three consecutive focal length segments: short focal length segment, medium focal length segment, and long focal length segment, and each focal length segment contains at least two consecutive typical focal length points.

[0035] The optical characteristics of a zoom lens change with focal length. This change is not uniform but exhibits a certain curvilinear characteristic. Within different focal length ranges, the movement speed and relative position of the zoom group and compensation group differ, leading to variations in the lens's imaging characteristics. Therefore, when dividing focal length ranges, the lens's zoom curve is first analyzed to identify the ranges where the optical characteristics change relatively smoothly. The entire focal length range is then divided into three consecutive parts: short focal length, medium focal length, and long focal length. The optical characteristics of the lens are similar within each focal length range, facilitating unified optimization adjustments. Furthermore, to ensure that the optimization effect within each focal length range covers the entire range, at least two consecutive typical focal length points are selected within each focal length range for testing and optimization, ensuring that no position within the focal length range is overlooked.

[0036] Dividing focal length segments based on the zoom curve characteristics of the lens ensures that the optical characteristics of the lens remain relatively consistent within each focal length segment, facilitating targeted optimization and adjustment. Each focal length segment contains at least two typical focal length points, ensuring that the optimization effect can cover the entire focal length segment and avoiding the problem of poor image quality at intermediate focal lengths caused by optimizing only a single focal length point.

[0037] In a preferred embodiment, the specific process of evaluating the imaging uniformity of each focal length segment and performing targeted optimization is as follows: for each typical focal point within each focal length segment, the tangential modulation transfer function (TMF) values ​​and arc modulation transfer function (AMF) values ​​of the center field of view, 0.7 field of view, and edge field of view are obtained respectively; the tangential-arc difference value under the same focal point in the same field of view is calculated; if the tangential-arc difference value is greater than or equal to a preset tangential-arc difference threshold, the position of the optical lens group corresponding to that focal point in that field of view is finely adjusted along the optical axis; the test and adjustment are repeated until the tangential-arc difference value of all focal points in all fields of view within the focal length segment is less than the tangential-arc difference threshold.

[0038] Lenses exhibit varying imaging capabilities at different fields of view, and their imaging transfer capabilities also differ in the tangential and arc directions. Excessive variation in these differences can lead to issues such as blurred edges and distortion in the image. To evaluate imaging uniformity, for each typical focal length point within a given focal length range, the lens's tangential and arc modulation transfer function (MTF) values ​​are tested using an optical testing system at three representative field-of-view locations: the center field of view, the 0.7 field of view, and the edge field of view. These two values ​​accurately reflect the lens's imaging sharpness in the corresponding direction and field of view. The difference between the tangential and arc values ​​at the same focal length point within the same field of view is then calculated and compared to a preset tangential-arc difference threshold. If the difference is greater than or equal to the threshold, the imaging uniformity at that location is poor and requires optimization. At this point, based on the optical characteristics corresponding to that field of view and focal length point, the positions of the front fixed group, zoom group, or compensation group lenses along the optical axis are fine-tuned to change the light propagation path, thereby adjusting the imaging transfer capabilities in both directions. After completing one adjustment, the test is repeated, and the tangent difference value is calculated until the tangent difference value of all fields of view and all focal points within the focal length segment is less than the threshold.

[0039] By testing the modulation transfer function value in separate fields of view and directions, the imaging uniformity of the lens at different positions can be accurately quantified. By fine-tuning the axial position of the corresponding lens group for targeted optimization, the difference between tangential and arc imaging can be effectively reduced, ensuring that the imaging quality of the lens is uniform and consistent across the entire focal length and field of view, and avoiding the problem of local imaging blur.

[0040] In a preferred embodiment, the tangential difference value is calculated as follows: the absolute value of the difference between the tangential modulation transfer function value and the arc modulation transfer function value at the same focal length point in the same field of view is obtained.

[0041] The tangential modulation transfer function (TMF) and arc modulation transfer function (AMF) values ​​reflect the lens's imaging transfer capability in two perpendicular directions, respectively. A greater difference between the two values ​​indicates a greater difference in sharpness between the two directions at that location, and a poorer image uniformity. When calculating the tangential-arc difference, the tangential value measured at the same focal length point in the same field of view is subtracted from the arc value, and the absolute value is taken. This method accurately reflects the magnitude of the difference in imaging capability between the two directions, unaffected by the sign of the difference, facilitating unified comparison and evaluation.

[0042] This calculation method is simple and intuitive, and can accurately quantify the difference between tangential and arc imaging capabilities. The calculation results are not affected by the positive or negative value of the difference, which makes it easy to set a unified evaluation threshold and conduct batch comparisons, providing an accurate and reliable quantitative basis for the evaluation of imaging uniformity.

[0043] In a preferred embodiment, the process of detecting and dynamically compensating for image plane drift during zooming is as follows: Under the same object distance and ambient temperature conditions, the lens is continuously zoomed from the short focal length end to the long focal length end, and image plane position data is collected every preset focal length interval to calculate the image plane drift between adjacent focal length points; if the image plane drift in a certain focal length range is greater than or equal to a preset drift threshold, the zoom cam curve parameters corresponding to that focal length range are adjusted to compensate for the image plane drift; the continuous zoom test and adjustment are repeated until the image plane drift in the entire focal length range is less than the drift threshold.

[0044] During zooming, the image plane position can shift due to movement errors of the zoom and compensation groups, mechanical gaps, and changes in optical characteristics, resulting in blurred images. To detect image plane drift, the test object distance and ambient temperature are kept constant to avoid external factors affecting the image plane position. Then, a drive motor rotates the zoom cam, smoothly and continuously zooming the lens from the short focal length end to the long focal length end. During zooming, at preset focal length intervals, an infrared detector collects the sharp position data of the image plane. The change in image plane position between two adjacent collection points, i.e., the image plane drift, is then calculated. The image plane drift for each focal length interval is compared with a preset drift threshold. If the drift is greater than or equal to the threshold, the image plane shift in that focal length interval is too large and requires compensation. The lift parameters of the zoom cam curve corresponding to that focal length interval are adjusted to change the movement pattern of the zoom and compensation groups within that interval, thereby compensating for the image plane shift. After completing one adjustment, repeat the full-focal-length continuous zoom test to detect the image plane drift until the image plane drift is less than the threshold throughout the entire focal length range.

[0045] Under the same test conditions, continuous zoom testing can accurately detect image plane drift in each focal length range during zooming. By adjusting the zoom cam curve parameters for dynamic compensation, image plane shift can be effectively corrected, ensuring that the image plane remains stable throughout the zoom process. This avoids image blurring during zooming and improves the zooming experience of the lens.

[0046] In a preferred embodiment, the process of generating the lens optical performance optimization priority table is as follows: The number of optical lens groups requiring adjustment and the axial displacement adjustment range within each focal length segment are counted, and the optimization difficulty coefficient for each focal length segment is calculated; the number of cold reflection adjustments for each optical surface and the number of image plane drift adjustments for each focal length interval are counted, and the influence weight of each optimization step is calculated based on the degree of influence of each optimization step on the final image quality; the lens optical performance optimization priority table is generated in order of optimization difficulty coefficient from high to low and influence weight from large to small.

[0047] After optimizing a single lens, a priority table needs to be generated to guide the batch optimization of subsequent lenses of the same model, clearly defining the order of each optimization step. First, the number of optical lens groups requiring adjustment and the axial displacement adjustment range of each lens group within each focal length segment are calculated. The more lens groups adjusted and the larger the adjustment range, the higher the optimization difficulty for that focal length segment. Based on this, the optimization difficulty coefficient for each focal length segment is calculated. Next, the number of adjustments to each optical surface during cold reflection optimization and the number of adjustments to each focal length range during image plane drift compensation are calculated. The more adjustments, the higher the probability of problems occurring in that step. Simultaneously, considering the impact of cold reflection, image balance, and image plane drift on the final image quality, different influence weights are assigned to each step. Finally, the optimization steps and focal length segments are sorted according to optimization difficulty coefficient from high to low and influence weight from large to small, generating a lens optical performance optimization priority table.

[0048] In a preferred embodiment, the method further includes the following steps: based on the generated lens optical performance optimization priority table, a batch optimization process parameter library for lenses of the same model is established, and cold reflection pre-optimization, imaging uniformity optimization, and image plane drift dynamic compensation adjustment are performed on the mass-produced lenses of the same model in sequence according to the priority table.

[0049] Lenses of the same model may exhibit slight differences in optical characteristics during production due to machining and assembly errors in components, but the overall optimization principles remain consistent. After optimizing a single lens and generating an optimization priority table, all process parameters obtained during this optimization process, including coating parameters and tilt angles for each high-risk optical surface, axial positions of lens groups corresponding to each focal length and field of view, and zoom cam curve parameters for each focal length range, are organized and stored in a database to establish a batch optimization process parameter library for lenses of the same model. During subsequent batch production of lenses of the same model, each lens is sequentially optimized according to the order determined in the optimization priority table, including cold reflection pre-optimization, imaging uniformity optimization, and image plane drift dynamic compensation adjustment. During optimization, standard parameters from the process parameter library are prioritized for adjustment, with only minor fine-tuning performed on individual lenses exhibiting significant differences.

[0050] The foregoing description, with reference to preferred embodiments, illustrates an exemplary implementation of a method for optimizing the optical performance of a cooled mid-wave infrared zoom lens provided by this disclosure. However, those skilled in the art will understand that various modifications and alterations can be made to the above specific embodiments without departing from the spirit of this disclosure, and various combinations can be made to the various technical features and structures proposed in this disclosure without exceeding the protection scope of this disclosure, the protection scope of which is determined by the appended claims.

Claims

1. A method of optimizing the optical performance of a refrigeration type mid-wave infrared zoom lens, comprising the steps of: Obtain the basic optical parameters of the cooled mid-wave infrared zoom lens to be optimized across the entire focal length range, and construct a multi-focal-length optical performance benchmark library; Based on the aforementioned multi-focal length optical performance benchmark library, a pre-evaluation of the cold reflection effect of the lens is performed, and optical surfaces with cold reflection risk are identified and pre-optimized. The full focal length range is divided into multiple consecutive focal length segments. Tangential and arc modulation transfer functions of the lens in each focal length segment are tested for sub-field of view to evaluate the imaging uniformity of each focal length segment and make targeted optimizations. The optimized lens is then subjected to a full focal length continuous zoom test to detect the amount of image plane drift during zooming, and dynamic compensation adjustments are made to generate a priority table for lens optical performance optimization.

2. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 1, characterized in that: The construction process of the multi-focal length optical performance benchmark library is as follows: select typical focal lengths of the lens to be optimized, including the short focal length, medium focal length and long focal length, and obtain the lens structure parameters, optical material parameters and initial imaging parameters at each focal length. Full field-of-view scanning tests were conducted on the lens at each focal length point to record basic imaging data at different field-of-view positions. All parameters and data were standardized and stored to form a multi-focal-length optical performance benchmark library.

3. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 2, characterized in that: The specific process of the pre-evaluation of the cold reflection effect is as follows: based on the optical surface parameters in the multi-focal length optical performance benchmark library, calculate the reflectivity of each optical surface under the normal incident condition of the 3-5μm mid-wave infrared band; compare the reflectivity of each optical surface with the preset cold reflection threshold; if the reflectivity of a certain optical surface is greater than or equal to the cold reflection threshold, then mark the optical surface as a high-risk optical surface.

4. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 3, characterized in that: The process of pre-optimizing optical surfaces with cold reflection risk is as follows: the coating parameters of high-risk optical surfaces are adjusted to reduce their reflectivity in the 3-5μm band; without compromising the basic imaging quality of the lens, the tilt angle of the high-risk optical surfaces is adjusted so that the reflected light deviates from the imaging area of ​​the cold detector; the cold reflection effect pre-evaluation is repeated until the reflectivity of all optical surfaces is less than the cold reflection threshold.

5. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 1, wherein: The process of dividing the full focal length range into multiple consecutive focal length segments is as follows: based on the zoom curve characteristics of the lens, the full focal length range is divided into three consecutive focal length segments: short focal length segment, medium focal length segment, and long focal length segment. Each focal length segment contains at least two consecutive typical focal length points.

6. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 5, characterized in that: The specific process for evaluating the imaging uniformity of each focal length segment and performing targeted optimization is as follows: For each typical focal point within each focal length segment, the tangential modulation transfer function (TMF) and arc modulation transfer function (AMF) values ​​for the center field of view, 0.7 field of view, and edge field of view are obtained respectively; the tangential-arc difference value under the same focal point in the same field of view is calculated; if the tangential-arc difference value is greater than or equal to the preset tangential-arc difference threshold, the position of the optical lens group corresponding to that focal point in that field of view is finely adjusted along the optical axis; the test and adjustment are repeated until the tangential-arc difference value of all focal points in all fields of view within that focal length segment is less than the tangential-arc difference threshold.

7. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 6, characterized in that: The tangential difference value is calculated as follows: the absolute value of the difference between the tangential modulation transfer function value and the arc modulation transfer function value at the same focal length point in the same field of view is obtained.

8. The method for optimizing optical performance of a refrigeration type mid-wave infrared zoom lens according to claim 6, characterized in that: The process of detecting and dynamically compensating for image plane drift during zooming is as follows: Under the same object distance and ambient temperature conditions, the lens is continuously zoomed from the short focal length end to the long focal length end, and image plane position data is collected every preset focal length interval to calculate the image plane drift between adjacent focal length points; if the image plane drift in a certain focal length interval is greater than or equal to a preset drift threshold, the zoom cam curve parameters corresponding to that focal length interval are adjusted to compensate for the image plane drift; the continuous zoom test and adjustment are repeated until the image plane drift in the entire focal length range is less than the drift threshold.

9. The method of claim 8, wherein the method is performed by a computer system. The process of generating the lens optical performance optimization priority table is as follows: The number of optical lens groups requiring adjustment and the axial displacement adjustment range within each focal length segment are counted, and the optimization difficulty coefficient for each focal length segment is calculated; the number of cold reflection adjustments for each optical surface and the number of image plane drift adjustments for each focal length interval are counted, and the influence weight of each optimization step is calculated based on the degree of influence of each optimization step on the final image quality; the lens optical performance optimization priority table is generated in order of optimization difficulty coefficient from high to low and influence weight from large to small.

10. The method for optimizing the optical performance of a cooled mid-wave infrared zoom lens according to claim 1, characterized in that, It also includes the following steps: Based on the generated lens optical performance optimization priority table, a batch optimization process parameter library for lenses of the same model is established. For lenses of the same model produced in batches, cold reflection pre-optimization, imaging uniformity optimization, and image plane drift dynamic compensation adjustment are performed in sequence according to the priority table.

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