Wafer image correction method and program product

Abstract

Embodiments of the present application provide a wafer image correction method and program product, comprising: performing multiple image acquisitions on a target pattern region on a target wafer to obtain a set of acquired images. For each pair of acquired images corresponding to two adjacent image acquisitions, an initial acquisition position deviation sequence is determined. An optimized acquisition position deviation of each initial acquisition position deviation is determined. According to a plurality of optimized acquisition position deviations, vibration signal data corresponding to a vibration signal is determined. According to the vibration signal data, a real acquisition image of the target wafer is corrected for vibration interference. The technical solution provided by the embodiments of the present application can efficiently and in real time correct the vibration interference of the wafer image, greatly improving the accuracy of the acquired image corresponding to the target wafer. The technical solution provided by the present application does not require external sensor equipment, is more portable, greatly saves costs, and also improves detection accuracy and fully meets the real-time demand for solving the vibration signal interference problem.

Description

Technical Field

[0001] This application belongs to the field of semiconductor testing and measurement technology, and in particular relates to a wafer image correction method and program product. Background Technology

[0002] In the semiconductor chip manufacturing process, scanning electron microscopes (SEMs) and other inspection equipment can be used to accurately acquire images of the critical dimensions of each chip on the wafer. The accuracy and quality of the acquired images have a significant impact on improving chip production quality and yield.

[0003] However, various vibration signals may exist during current wafer image acquisition processes, such as internal mechanical vibrations of the acquisition equipment and environmental micro-vibrations. The presence of these vibration signals can cause deviations in the scanning trajectory of the electron beam on the wafer surface, leading to serious problems affecting image acquisition accuracy, such as pattern misalignment and large linewidth errors. Traditional methods for handling vibration signals involve monitoring them using external sensors. However, this approach suffers from low detection accuracy, requires a large amount of monitoring data for analysis to determine the vibration problem, has a significant delay impacting image acquisition efficiency, and involves high sensor usage and maintenance costs, resulting in substantial implementation costs.

[0004] Therefore, how to efficiently and accurately detect vibration signals and correct images in wafer acquisition images is an important problem that urgently needs to be solved. Summary of the Invention

[0005] This application provides a wafer image correction method and program product, which can efficiently correct wafer acquisition images that are subject to vibration signal interference, thereby improving the accuracy of the acquired images.

[0006] In a first aspect, embodiments of this application provide a wafer image correction method, including:

[0007] Multiple image acquisitions were performed on the target pattern region on the target wafer using an electron microscope to determine an image set containing multiple acquired images.

[0008] Based on the acquired images corresponding to each two adjacent image acquisitions in the acquired image set, an initial acquisition position deviation sequence is determined. The ranking order of each initial acquisition position deviation in the initial acquisition position deviation sequence is determined according to the image acquisition order. The initial acquisition position deviation represents the acquisition position difference between two acquired images in two adjacent image acquisitions.

[0009] For each initial acquisition position deviation, the optimized acquisition position deviation is determined based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence.

[0010] Based on multiple optimized acquisition position deviations, the vibration signal data corresponding to the acquired image set is determined;

[0011] Based on the vibration signal data, vibration interference correction is performed on the actual acquired image of the target wafer to obtain the corrected acquired image of the target wafer.

[0012] Secondly, embodiments of this application provide a wafer image correction apparatus, comprising:

[0013] The image acquisition unit is used to repeatedly acquire images of the target pattern area on the target wafer using an electron microscope, and to determine an image set including multiple acquired images.

[0014] The deviation determination unit is used to determine the initial acquisition position deviation sequence based on the acquisition images corresponding to each two adjacent image acquisitions in the acquisition image set. The ranking order of each initial acquisition position deviation in the initial acquisition position deviation sequence is determined according to the image acquisition order. The initial acquisition position deviation represents the acquisition position difference between two acquisition images in two adjacent image acquisitions.

[0015] The deviation optimization unit is used to determine the optimized acquisition position deviation for each initial acquisition position deviation based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence.

[0016] The vibration detection unit is used to determine the vibration signal data corresponding to the set of acquired images based on multiple optimized acquisition position deviations.

[0017] The image correction unit is used to correct vibration interference on the actual acquired image of the target wafer based on vibration signal data, so as to obtain the corrected acquired image of the target wafer.

[0018] Thirdly, embodiments of this application provide an electronic device, which includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the steps of any wafer image correction method of embodiments of this application.

[0019] Fourthly, embodiments of this application provide a readable storage medium storing a program or instructions, which, when executed by a processor, implement the steps of any wafer image correction method of embodiments of this application.

[0020] Fifthly, embodiments of this application provide a computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, enable the electronic device to perform the steps of any wafer image correction method according to embodiments of this application.

[0021] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0022] This application provides a wafer image correction method, comprising: First, repeatedly acquiring images of a target pattern region on a target wafer using an electron microscope to obtain an image set. Then, acquiring corresponding images for every two adjacent images in the image set to determine an initial acquisition position deviation sequence. Based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence for each initial acquisition position deviation, an optimized acquisition position deviation for that initial acquisition position deviation can be determined.

[0023] Finally, based on the determined multiple optimized acquisition position deviations, vibration signals in the acquired images can be detected, and the corresponding vibration signal data can be determined. Based on the vibration signal data, efficient and accurate vibration interference correction can be performed on the actual acquired images of the target wafer, resulting in corrected acquired images of the target wafer.

[0024] The technical solution provided in this application can accurately detect vibration signals that may affect the accuracy of the acquired images by repeatedly acquiring data from the same graphic area. Based on the detected vibration signal data, the technical solution provided in this application can also perform efficient and real-time vibration interference correction on wafer images, greatly improving the accuracy of the acquired images corresponding to the target wafer. Compared to signal monitoring based on vibration sensors with high usage and maintenance costs, the technical solution provided in this application does not require external sensor equipment, making it more portable and significantly saving costs while improving detection accuracy and fully meeting the real-time requirements for solving vibration signal interference problems.

[0025] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a schematic flowchart illustrating a wafer image correction method according to an embodiment of this application.

[0028] Figure 2 This is a schematic diagram of the overall process of a wafer image correction method provided in one embodiment of this application;

[0029] Figure 3 This is a schematic diagram of the structure of a wafer image correction device provided in another embodiment of this application;

[0030] Figure 4 This is a schematic diagram of the structure of a wafer image correction device provided in another embodiment of this application. Detailed Implementation

[0031] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0032] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0033] In the current semiconductor chip manufacturing process, precise measurements of critical wafer dimensions are achieved using instruments such as scanning electron microscopes (SEM). The acquired wafer surface images have a significant impact on chip production quality and yield assessment. However, vibration signals, such as mechanical vibrations within the acquisition equipment and external environmental interference, can cause trajectory deviations when the electron beam scans the wafer surface. This results in image errors such as pattern misalignment and linewidth distortion, severely affecting the accuracy of wafer surface dimensional data detection.

[0034] Currently, the main solution to vibration interference is to monitor potential vibration signals using external sensors. While this method can detect vibration signals to some extent, its accuracy is determined by the precision of the sensor itself, and it requires a large amount of monitoring data over a long period to analyze the vibration signal, resulting in significant time delays that severely impact the processing efficiency of wafer surface image acquisition. Furthermore, sensor-based vibration detection is costly in terms of sensor deployment and maintenance, which can negatively affect the allocation of production resources.

[0035] To address the aforementioned technical issues, this application provides a wafer image correction method and program product. The method includes: repeatedly acquiring images of a target pattern region on a target wafer using an electron microscope to obtain a set of acquired images. For each consecutive two acquisitions in the acquired image set, an initial acquisition position deviation sequence can be determined.

[0036] Then, based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence for each initial acquisition position deviation, the optimized acquisition position deviation for that initial acquisition position deviation can be determined. Finally, based on the determined multiple optimized acquisition position deviations, vibration signals in the acquired images are detected, and the corresponding vibration signal data is determined. For the actual acquired image of the target wafer, based on the determined vibration signal data, efficient and accurate vibration signal interference correction can be performed, ultimately obtaining the corrected acquired image of the target wafer.

[0037] The technical solution provided in this application can accurately and in real-time detect vibration signals that may affect the accuracy of the acquired images by repeatedly acquiring images of the same graphic area. Based on the detected vibration signal data, efficient and real-time vibration interference correction can also be performed on the wafer image, greatly improving the accuracy of the acquired image corresponding to the target wafer.

[0038] Compared to traditional technologies that use vibration sensors with high operating and maintenance costs for vibration signal monitoring, the technical solution provided in this application requires no external sensor equipment, making it more portable, significantly reducing costs, and substantially improving detection accuracy. Furthermore, the technical solution provided in this application possesses more effective real-time detection and vibration correction capabilities, significantly superior to traditional sensor monitoring methods.

[0039] The execution entity used in the embodiments of this application can be a terminal device, such as a desktop computer or laptop computer, or a remote device, such as a server. In addition, the execution entity used in the embodiments of this application can also be a software entity, such as a client or software program installed on a terminal device. The execution entity used in applying the technical solutions provided in the embodiments of this application is not strictly limited here, and can be flexibly selected according to the application scenario and actual needs.

[0040] In addition, it should be noted that this application does not strictly limit the specific application scenarios of the wafer image correction method and program product provided in the embodiments of this application, and can be determined according to actual needs.

[0041] For example, in applications where images of a wafer surface are acquired using an electron microscope to determine whether critical dimensional data on the wafer conform to design standards, the technical solution provided in this application can acquire multiple images of the same area on the wafer to be inspected, determining the corresponding set of acquired images. Then, for the set of acquired images, an initial acquisition position deviation sequence composed of the initial acquisition position deviation between every two acquired images can be determined.

[0042] Based on the initial acquisition position deviation sequence, the technical solution provided in this application can be further predicted and optimized to determine the optimized acquisition position deviations corresponding to the initial acquisition position deviation sequence. Based on multiple optimized acquisition position deviations, vibration signal data can be accurately determined, and vibration signal interference correction can be performed on the actual acquired image of the wafer to be inspected based on the vibration signal data. The corrected acquired image will no longer have acquisition errors caused by vibration interference and can be used for subsequent analysis and inspection of key dimension data on the wafer to be inspected.

[0043] In this application scenario, the technical solution provided in this application embodiment can accurately and efficiently detect and determine vibration signal interference that may exist during image acquisition, and can correct the acquired image for vibration interference in real time based on vibration signal data. This effectively improves the detection accuracy of the acquired image while significantly increasing the efficiency of obtaining accurate acquired images, and can greatly save production costs compared to monitoring vibration signals using sensors.

[0044] It should be noted that the application scenarios described in the above embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will understand that with the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems. The wafer image correction method and program product provided by the embodiments of this application can be applied to various application scenarios that require the detection of vibration signals during wafer image acquisition and the correction of vibration interference in the acquired wafer images.

[0045] Figure 1 This is a schematic flowchart of a wafer image correction method provided in one embodiment of this application.

[0046] like Figure 1 As shown, a wafer image correction method provided in one embodiment of this application includes steps S101 to S105.

[0047] S101: Repeatedly acquire images of the target pattern region on the target wafer using an electron microscope to determine a set of acquired images including multiple acquired images.

[0048] S102: Determine the initial acquisition position deviation sequence based on the acquisition images corresponding to each two adjacent acquisitions in the acquisition image set.

[0049] S103: For each initial acquisition position deviation, based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence, determine the optimized acquisition position deviation of the initial acquisition position deviation.

[0050] S104: Determine the vibration signal data corresponding to the acquired image set based on multiple optimized acquisition position deviations.

[0051] S105: Based on the vibration signal data, the actual acquired image of the target wafer is corrected for vibration interference to obtain the corrected acquired image of the target wafer.

[0052] In step S101, the technical solution provided in this application embodiment can perform multiple image acquisitions on the same target pattern area on the target wafer using an electron microscope. Each image acquisition is used as a single acquisition image, and multiple acquisition images can be combined to obtain a set of acquisition images for subsequent vibration signal analysis.

[0053] In this application, the specific type and function of the electron microscope used for image acquisition are not strictly limited. In some embodiments, the electron microscope may be, for example, a scanning electron microscope (SEM), a transmission electron microscope (TEM), a scanning transmission electron microscope (STEM), an environmental scanning electron microscope (ESEM), etc., which can be flexibly selected according to the application scenario and actual needs.

[0054] The target image region can be a portion of the target wafer, and the specific image content is not strictly limited in this embodiment. In some embodiments, to facilitate more efficient and intuitive analysis and determination of vibration signal data, a smaller linewidth region on the target wafer (e.g., metal traces, polysilicon gate regions, etc.) can be selected as the target image region, or it can be another wafer region with a simple graphic structure and no adjacent graphics. The selection and setting can be flexible according to the application scenario and the type of target wafer.

[0055] Regarding the specific acquisition process of each acquired image and the process of determining the acquired image set, this application embodiment takes into account that vibration signals in actual scenarios have vibration direction and vibration frequency. When scanning wafer images with an electron microscope, if the direction is consistent with or close to the vibration signal, the acquired image will be more significantly affected by the vibration signal.

[0056] Furthermore, there is a direct correlation between the image acquisition rate and the vibration signal frequency; that is, the faster the acquisition rate, the higher the frequency limit of the vibration signal reflected in the acquired image. Therefore, more targeted image acquisition can be performed based on the vibration direction and the target vibration frequency range, improving the practicality of the acquired images and providing a practical basis for subsequent vibration signal analysis.

[0057] Based on this, in one embodiment provided in this application, before acquiring images of the target wafer region using an electron microscope, the predicted vibration direction and vibration frequency detection standard for the vibration signal to be detected can be obtained first.

[0058] The predicted vibration direction represents the predicted vibration direction for the vibration signal to be detected, and can be used as the scanning direction for scanning the wafer surface with an electron microscope. The vibration frequency detection standard represents the range of vibration frequencies that the vibration signal to be detected may correspond to. Based on the vibration frequency detection standard, the image acquisition speed can be flexibly selected. According to the acquired images obtained at different acquisition speeds, vibration signals of different frequencies can be detected in the subsequent determination and analysis of vibration data.

[0059] Specifically, based on the vibration frequency detection standard, the corresponding image acquisition speed can be accurately determined. Then, using an electron microscope, images of a single target pattern region on the target wafer can be repeatedly acquired according to the predicted vibration direction and the determined image acquisition speed, thereby obtaining multiple acquired images of the same target pattern region at different acquisition times.

[0060] Next, in this embodiment, multiple acquired images can be arranged and combined according to the image acquisition order to finally obtain an acquired image set containing multiple acquired images.

[0061] The specific form of the aforementioned image set is not strictly limited in this application. It can be composed of multiple images stitched together to form a detection image, which is the image set.

[0062] For example, assuming each acquired image corresponds to a resolution of 512*1 (width*height), and a total of 512 acquisitions were performed on the target graphic region, resulting in 512 acquired images with a resolution of 512*1. Then, by stitching the images along the height of the resolution, a 512*512 detection image composed of the 512 acquired images can be obtained, serving as the acquired image set. In this example, each row of the acquired image set corresponds to one acquired image.

[0063] The above examples are only for understanding the process of determining the set of acquired images and do not constitute any limitation. In other embodiments, the specific form and determination method of the acquired image set may also be other forms, which can be flexibly set according to actual needs and application scenarios.

[0064] Furthermore, when acquiring images of a target wafer using an electron microscope, minimizing the actual physical distance between each pixel in the acquired image and the target wafer helps improve the resolution and clarity of the acquired image. This can be achieved by adjusting the magnification of the electron microscope, the scanning parameters, and the working distance.

[0065] The above embodiments enable efficient and accurate determination of the acquired image set. Furthermore, during the actual acquisition process, the vibration direction and frequency can be specifically set for the vibration signal to be detected, significantly enhancing the representation of the vibration signal in the acquired images. This provides a more practical and realistic basis for subsequent vibration signal analysis and data determination. It further improves the accuracy and practicality of subsequent vibration interference correction of the target acquired image based on vibration signal data.

[0066] In step S102, the technical solution provided in this application embodiment can acquire corresponding acquisition images for each two adjacent images in the acquisition image set, determine the initial acquisition position deviation between the two acquisition images, and thus determine the initial acquisition position deviation sequence corresponding to the acquisition image set.

[0067] The initial acquisition position deviation is used to represent the difference in acquisition position between two adjacent image acquisitions caused by vibration signal interference when the electron microscope scans the image with an electron beam. Specifically, it can be determined based on the pixel values ​​at the same positions in the two acquisition images or based on cross-correlation coefficients, etc.

[0068] The aforementioned initial acquisition position deviation sequence is composed of multiple initial acquisition position deviations arranged and combined according to the image acquisition order. For example, the initial acquisition position deviation between the first and second acquired images is the first initial acquisition position deviation in the initial acquisition position deviation sequence, the initial acquisition position deviation between the second and third acquired images is the second initial acquisition position deviation in the initial acquisition position deviation sequence, and so on, with multiple initial acquisition position deviations forming the initial acquisition position deviation sequence.

[0069] The specific determination process for each initial acquisition position deviation and the sequence of initial acquisition position deviations is not strictly limited in the embodiments of this application. In one embodiment provided in this application, the corresponding initial acquisition position deviation can be determined based on the pixel value difference between the acquired images corresponding to two adjacent image acquisitions.

[0070] Specifically, for each two adjacent image acquisitions in the image set, the pixel values ​​of each pixel in the two images can be determined. Then, since the image size and resolution of each acquired image are the same, the pixel value difference between pixels at the same location in the two acquired images can be determined based on the pixel values.

[0071] The initial acquisition position deviation between two acquired images can be further determined by the pixel value difference at the same image location. Specifically, a sliding window can be set for the pixel value difference, and the window width can be flexibly selected, such as 5 pixels.

[0072] Then, based on the difference between each pixel value and the sliding window, the cumulative error of the acquisition position corresponding to the sliding window can be calculated, and the minimum position offset can be determined based on the cumulative error, thereby obtaining the initial acquisition position deviation.

[0073] The above embodiments can accurately determine the initial acquisition position deviation corresponding to each two adjacent image acquisitions in the acquired image set, and then combine them according to the image acquisition order to obtain the above-mentioned initial acquisition position deviation sequence. By determining the initial acquisition position deviation and the initial acquisition position deviation sequence based on the above-mentioned pixel value difference method, the efficiency and accuracy of image deviation determination can be effectively improved, providing a practical basis for subsequent vibration signal data analysis and determination, and improving the processing efficiency and correction accuracy of the overall vibration interference correction process.

[0074] In addition to determining the initial acquisition position deviation based on the pixel value difference between the acquired images as described above, in another embodiment provided in this application, each initial acquisition position deviation can also be determined based on the normalized cross-correlation (NCC) corresponding to each candidate acquisition position deviation within the preset acquisition position deviation range.

[0075] Specifically, for each two adjacent image acquisitions in the acquired image set, while determining the corresponding pixel value data of the two acquired images, normalization processing can be performed on the corresponding pixel value data of the two acquired images to determine the normalized pixel value data of the two acquired images. The pixel value data can specifically represent image features such as grayscale distribution features corresponding to the acquired images.

[0076] Then, based on the normalized pixel value data corresponding to the two acquired images and the preset acquisition position deviation range, the cross-correlation coefficient corresponding to each candidate acquisition position deviation within the acquisition position deviation range is determined, i.e., the aforementioned normalized cross-correlation coefficient. The maximum cross-correlation coefficient and its corresponding candidate acquisition position deviation are then determined. Each candidate acquisition position deviation within the acquisition position deviation range can be an integer pixel-level position deviation.

[0077] To improve the accuracy of determining the initial acquisition position deviation, in this embodiment, sub-pixel level interpolation can be performed between the candidate acquisition position deviation corresponding to the maximum cross-correlation coefficient and adjacent candidate acquisition position deviations to determine a more accurate initial acquisition position deviation. Specifically, a function can be fitted based on the maximum cross-correlation coefficient and the cross-correlation coefficients corresponding to the adjacent candidate acquisition position deviations of the maximum cross-correlation coefficient. Position deviation interpolation is then performed based on the fitted function to determine the sub-pixel level initial acquisition position deviation.

[0078] Similarly, by arranging and combining the initial acquisition position deviations corresponding to every two acquired images according to the image acquisition order, the sequence of initial acquisition position deviations corresponding to the acquired image set can be determined.

[0079] The above embodiments can accurately determine the initial acquisition position deviation sequence corresponding to the acquired image set based on the normalized cross-correlation coefficient, providing a practical basis for subsequent vibration signal data analysis and determination. Furthermore, over-interpolation processing can achieve higher precision in determining the acquisition position deviation. This embodiment effectively improves the accuracy of acquisition position deviation determination, providing strong support for the accuracy of subsequent vibration signal data analysis and determination, as well as vibration interference correction based on vibration signal data.

[0080] In addition to the above, considering that the image acquisition using an electron microscope in step S101 may be affected by, for example, Gaussian noise or random noise, which may interfere with the accuracy of the acquired image.

[0081] Therefore, in one embodiment provided in this application, before performing the above-described initial acquisition position deviation determination process, noise filtering can be applied to each acquired image in the acquired image set to obtain a denoised acquired image set. Performing the initial acquisition position deviation determination process corresponding to the above embodiments on the denoised acquired image set can reduce the impact of noise and significantly improve the accuracy of the initial acquisition position deviation determination.

[0082] It should be noted that the specific filtering method used in the noise filtering process described above is not strictly limited in the embodiments of this application. In some embodiments, a Gaussian filter can be selected, for example, with a Gaussian kernel of 1*3, or other filtering methods can be used, which can be flexibly set according to actual needs and application scenarios.

[0083] In step S103, the technical solution provided in this application embodiment can optimize each initial acquisition position deviation in the initial acquisition position deviation sequence determined in the above steps, thereby further eliminating potential noise interference and random errors that may exist in the initial acquisition position deviation sequence on the basis of noise reduction filtering in step S102.

[0084] Specifically, in one embodiment provided in this application, for each initial acquisition position deviation in the initial acquisition position deviation sequence, the predicted acquisition position deviation between the two acquisition images to which the initial acquisition position deviation belongs can be predicted and determined based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the sequence.

[0085] Then, based on the predicted acquisition position deviation and the initial acquisition position deviation, the optimized acquisition position deviation corresponding to the initial acquisition position deviation can be determined.

[0086] Specifically, the preceding initial acquisition position deviation refers to the initial acquisition position deviation preceding each initial acquisition position deviation in the sequence. Since the first initial acquisition position deviation in the sequence has no preceding initial acquisition position deviation, it can be directly used as the optimized acquisition position deviation.

[0087] For each initial acquisition position deviation in the sequence except for the first initial acquisition position deviation, the prediction of the acquisition position deviation can be made based on the optimized position deviation of at least one preceding initial acquisition position deviation.

[0088] The predicted acquisition position deviation can represent the potential acquisition position deviation at the next acquisition moment, predicted from the physical laws of historical data (previous initial acquisition position deviation). By weighting and fusing the predicted acquisition position deviation with the corresponding initial acquisition position according to their respective weight ratios, the optimized acquisition position deviation can be determined. The specific process for determining the predicted acquisition position deviation can be referenced in the following formula (1):

[0089]

[0090] in, This represents the predicted acquisition position deviation corresponding to the k-th initial acquisition position deviation in the sequence, where k>1, x k-1|k-1 F represents the optimized acquisition position error corresponding to the deviation of the (k-1)th initial acquisition position. k The state transition matrix F, in the embodiments provided in this application, can be an identity matrix or an approximate identity matrix. Specifically, it is used to represent the influence of the sinusoidal change in time corresponding to the superposition of multiple harmonics in the vibration signal on the deviation of the (k-1)th initial acquisition position.

[0091] The specific process of weighting and fusing the predicted acquisition position deviation with the corresponding initial acquisition position according to the corresponding weight ratio to determine the optimized acquisition position deviation can be referred to in the following formulas (2) to (4):

[0092]

[0093] in, z represents the optimized acquisition position deviation corresponding to the k-th initial acquisition position deviation in the sequence. k H represents the deviation of the kth initial acquisition position. kGiven a pre-determined observation model matrix, and considering that the observation object in this embodiment is the displacement of the acquisition position, the acquisition position displacement can be used as a parameter for H. k The determination of K. k The gain weight, which in some embodiments may be the Kalman gain, is used to determine the initial acquisition position deviation z. k And the deviation of the predicted acquisition location The weight allocation can be determined by formula (3).

[0094] In formula (3), P k|k-1 The updated prediction error covariance matrix P is the prediction error based on the (k-1)th initial acquisition position deviation for the kth initial acquisition position deviation. k-1|k-1 The determined prediction error covariance matrix represents the prediction acquisition location deviation. The uncertainty of P. k|k-1 This can be understood as the predicted acquisition position deviation obtained through formula (1). Within a certain range of the standard prediction deviation, the prediction error covariance matrix P k|k-1 The larger the interval, the more it can be calculated using formula (4). R k The covariance matrix is ​​a predetermined set of observation noise, representing the actual observation error when the acquisition position deviation is determined.

[0095] The gain weight K can be accurately determined using formula (3). k , used in formula (2) to measure the initial acquisition position deviation z k and Determine the corresponding weights. Formula (4) is used to update the prediction error covariance matrix P based on the deviation of the (k-1)th initial acquisition position. k-1|k-1 Determine the prediction error covariance matrix P of the k-th initial acquisition position deviation. k|k-1 Among them, Q k The process noise covariance matrix, which is predetermined, can represent the dependence of the prediction result on the actual observation result. In the embodiments of this application, the process noise covariance matrix Q... k This can represent the initial acquisition position deviation z between every two acquired images due to factors such as image noise. k Inaccurate information.

[0096] Prediction error covariance matrix P k|k-1 The gain weight K can be determined k Then, an update is performed to accurately determine the prediction error covariance matrix P of the (k+1)th initial acquisition position deviation. k+1|k Prediction error covariance matrix P k|k-1 The update process can be referenced as shown in the following formula (5):

[0097] P k|k =(IK k H k )P k|k-1 Formula (5)

[0098] Among them, P k|k The prediction error covariance matrix P k|k-1 The corresponding updated prediction error covariance matrix is ​​used to determine the prediction error covariance matrix P of the (k+1)th initial acquisition position deviation using the above formula (4). k+1|k I is the identity matrix, and the other parameters have the same meaning as those in the above formula.

[0099] By optimizing the determination process of the acquisition position deviation in the above embodiments, potential noise problems and non-periodic abnormal data existing in the initial acquisition position deviation determined directly based on the acquired data can be accurately eliminated. This effectively improves the accuracy of deviation data determination, providing accurate and practical input data for subsequent vibration signal data analysis and determination, thereby improving the correction effect of vibration interference correction for subsequent real acquired images of the target wafer.

[0100] It should be noted that, in some embodiments, the process of determining the optimized acquisition position deviation in the above embodiments can be implemented using Kalman filtering. The initial acquisition position deviation sequence determined in step S102 is input into the Kalman filter. The Kalman filter enables efficient prediction of each initial acquisition position deviation and accurate determination of each optimized acquisition position deviation.

[0101] In step S104, the technical solution provided in this application embodiment can detect possible vibration signals in the acquired image set and determine the corresponding vibration signal data by frequency domain conversion based on the deviation sequence composed of multiple optimized acquisition position deviations determined by the above steps.

[0102] Specifically, in one embodiment provided in this application, a frequency domain transformation can be performed on a sequence of acquisition position deviations composed of multiple optimized acquisition position deviations to determine the corresponding spectral data.

[0103] The specific frequency domain transformation method is not strictly limited in this embodiment. In some embodiments, it may involve performing a one-dimensional Discrete Fourier Transform (DFT) on the aforementioned acquisition position deviation sequence, and a Hamming window function may be introduced to reduce spectral leakage. Other feasible frequency domain transformation methods may also be used in other embodiments, and are not strictly limited here. They can be flexibly selected according to the application scenario and actual needs.

[0104] Next, based on the determined spectral data, the vibration signal data contained within the spectral data can be further analyzed and identified. In real-world scenarios, vibration signals often contain more than one frequency signal; they are usually composed of multiple components of different frequencies superimposed on each other.

[0105] Therefore, in one embodiment provided in this application, the vibration signal can be specifically divided into first harmonic, second harmonic, third harmonic, and fourth harmonic components according to the different vibration frequencies. The vibration frequencies of the second harmonic, third harmonic, and fourth harmonic signals are two, three, and four times the vibration frequency of the first harmonic, respectively.

[0106] For component signals with different vibration frequencies, the embodiments of this application can determine corresponding signal data for each component signal in the vibration signal. The signal data may include, but is not limited to, signal frequency, amplitude, initial phase information, etc. The signal data corresponding to all component signals can be combined to form the vibration signal data corresponding to the vibration signal, which is used for subsequent vibration interference correction of the actual acquired image of the target wafer.

[0107] Through the frequency domain transformation and corresponding analysis described in the above embodiments, the vibration signal data corresponding to the acquired image set can be accurately detected and determined. This provides sufficient data support for the subsequent vibration interference correction process of the actual acquired images, improving the processing efficiency and correction effect of the vibration interference correction process, and thus obtaining more accurate wafer acquired images.

[0108] In addition to the above, this application embodiment also considers that since the acquired image set is obtained by repeatedly scanning the same target pattern area, and because the electron microscope accumulates charge when scanning the wafer surface repeatedly with the electron beam, repeated scanning will cause the target pattern area to gradually accumulate charge, which may cause the electron beam scanning path to deflect, resulting in image errors and affecting the accuracy of image acquisition.

[0109] Based on this, in one embodiment provided in this application, a function can be fitted to the multiple optimized acquisition positions determined in step S103, and the charge drift component can be determined based on the fitted function, thereby eliminating the charge drift problem caused by charge accumulation and improving the determination accuracy of vibration signal data in the above embodiment.

[0110] Specifically, based on the determined multiple optimized acquisition position deviations and the acquisition time corresponding to each acquisition image in the acquisition image set, a function can be fitted to the acquisition position sequence formed by the multiple optimized acquisition position deviations to determine the corresponding fitting function.

[0111] Furthermore, based on the determined fitting function, the charge accumulation drift component caused by charge accumulation can be identified for each optimized acquisition position deviation. Then, based on the charge accumulation drift component, drift component elimination can be performed on each optimized acquisition position deviation to determine the acquisition position deviation after drift elimination for each optimized acquisition position deviation.

[0112] Then, based on the acquisition position deviation sequence composed of the acquisition position deviation after drift elimination, the vibration signal data corresponding to the vibration signal can be determined through the above embodiments. The drift elimination process through the above function fitting can effectively solve the charge drift error that may be caused by charge accumulation in the optimized acquisition position deviation, improving the accuracy of the deviation data while also ensuring the accuracy of the vibration signal data.

[0113] In step S105, the technical solution provided in this application embodiment can perform vibration interference correction on the actual acquired image of the target wafer based on the vibration signal data determined in the above steps, thereby eliminating the error problem caused by the difference between the actual acquired image and the actual wafer surface due to vibration signal.

[0114] Specifically, in one embodiment provided in this application, a position compensation amount can be determined based on the image acquisition time corresponding to the actual acquired image and the vibration signal data determined in the above steps to compensate for the acquisition position offset caused by the vibration signal in the actual acquired image. Then, position compensation can be performed on the actual acquired image based on the position compensation amount to achieve vibration interference correction, and finally obtain the corrected acquired image corresponding to the actual acquired image.

[0115] The vibration signal data can be the signal data corresponding to the first, second, third, and fourth harmonic components mentioned in the above embodiments. The technical solution provided in this application can determine the corresponding position compensation amount for each component signal in the vibration signal, that is, for example, determine the position compensation amount corresponding to the first, second, third, and fourth harmonics of the actual acquired image.

[0116] Based on the position compensation amounts corresponding to the first, second, third, and fourth harmonics in the actual acquired images, the comprehensive position compensation amount corresponding to the vibration signals in the actual acquired images can be further determined. Based on the comprehensive position compensation amount, the image positions in the actual acquired images caused by acquisition errors due to vibration signals can be corrected, resulting in corrected acquired images.

[0117] The specific process for determining the position compensation amount corresponding to the actual acquired image and the signals of different components can be referred to the following formula (6):

[0118]

[0119] For each component signal in the vibration signal, A is the signal amplitude corresponding to the component signal, f is the signal frequency corresponding to the component signal, and x is the image position to be compensated in the actual acquired image. Specifically, it can be the number of rows in the actual acquired image formed by stitching together the acquired images of multiple continuous graphic regions. Given the phase corresponding to the image acquisition time of the actual acquired image, the position compensation amount Δy corresponding to each image position in the actual acquired image can be calculated and determined based on the image acquisition time according to formula (6).

[0120] Taking the vibration signal data in the above embodiment as an example, which may include the signal data corresponding to the first harmonic, second harmonic, third harmonic, and fourth harmonic, the compensation amount of each image position in the actual acquired image and the corresponding position of the first harmonic, second harmonic, third harmonic, and fourth harmonic can be determined by the above formula (6). The first harmonic corresponds to Δy1, the second harmonic corresponds to Δy2, the third harmonic corresponds to Δy3, and the fourth harmonic corresponds to Δy4.

[0121] Then, the position compensation amounts corresponding to each component signal can be summed to determine the comprehensive position compensation amount for each position in the actual acquired image, i.e., ΔY = Δy1 + Δy2 + Δy3 + Δy4, where ΔY is the comprehensive position compensation amount. Based on the determined comprehensive position compensation amount, the acquisition error caused by vibration signal interference in the actual acquired image can be image corrected, and the corrected acquired image can be obtained.

[0122] The above embodiments enable efficient and accurate correction of vibration interference in real-world images of a target wafer. Based on the steps outlined above, vibration signal data is accurately determined, and the positional compensation for each component signal is calculated, successfully resolving the error interference from vibration signals in the real-world images and significantly improving the accuracy of the acquired images. The corrected acquired images can provide practical reference for subsequent processes based on wafer images, such as wafer defect detection, production quality assessment, and process monitoring, improving processing efficiency and accuracy.

[0123] In addition to correcting vibration interference in the acquired images based on vibration signal data as described above, thereby eliminating vibration interference, this application embodiment also considers addressing the problem at its source, thus resolving the vibration interference problem at its root and improving the accuracy of the wafer surface image acquisition process.

[0124] Specifically, in another embodiment provided in this application, after determining the vibration signal data corresponding to the acquired image set through the above step S104, the vibration signal type corresponding to the vibration signal data can be determined based on the vibration signal data and the vibration signal judgment criteria predetermined based on historical vibration problems.

[0125] The vibration signal judgment criteria are used to determine the possible vibration signal type based on one or more data points in the vibration signal data. Vibration signal types can include, but are not limited to, vibration interference such as environmental vibration, power frequency interference, mechanical resonance, and electromagnetic noise.

[0126] For example, based on the vibration frequency in the vibration signal data, when the vibration frequency is within a preset range, the type of vibration signal corresponding to the vibration signal data can be determined (e.g., 0.1Hz-10Hz may belong to low-frequency environmental vibration, around 50Hz may belong to power supply frequency interference vibration, etc.). Alternatively, the vibration signal type can also be determined based on the vibration amplitude and phase change characteristics. The specific content of the vibration signal judgment criteria and the selection of judgment basis are not strictly limited in this application embodiment, and can be flexibly limited according to actual needs and application scenarios.

[0127] Based on the identified vibration signal type, hardware adjustments can be made to address the vibration anomalies causing the vibration signals, thus resolving vibration interference at its source. For example, power frequency filters can be added to suppress power frequency fluctuations, and piezoelectric active dampers or other damping devices can be added to counteract mechanical resonance. After hardware adjustments, image acquisition can be performed on the target image, resulting in a true image unaffected by vibration interference.

[0128] Based on the above embodiments, the vibration interference problem can be solved at its source, allowing the electro-optic microscope to avoid interference from vibration signals when acquiring images of the target wafer, and directly obtain accurate and error-free images. This method of solving vibration interference not only effectively improves the accuracy of the acquired images but also significantly improves the efficiency of accurate image acquisition, thereby enhancing the efficiency and accuracy of subsequent analysis and processing of the acquired images.

[0129] The above content describes the specific implementation methods and corresponding embodiments of each step in the wafer image correction method provided in this application. For ease of overall understanding, the overall flow of the wafer image correction method is further integrated below. For details, please refer to... Figure 2 As shown in the image.

[0130] Figure 2 This is a schematic diagram of the overall process of a wafer image correction method provided in one embodiment of the present application, including steps S201 to S209.

[0131] S201: Using an electron microscope, along the predicted vibration direction, and based on the vibration frequency detection standard corresponding to the image acquisition speed, repeatedly acquire images of the target pattern area on the target wafer to determine the acquired image set.

[0132] In step S201, the corresponding image acquisition speed can be determined according to the vibration frequency detection standard. Using an electron microscope, multiple images are acquired from the same target pattern area on the target wafer according to the determined image acquisition speed and the predicted vibration direction, resulting in multiple acquired images affected by the vibration signal. These multiple acquired images can be combined by stitching them together to form an image set.

[0133] S202: Perform noise filtering on the acquired image set to obtain the noise-filtered acquired image set.

[0134] In step S202, noise filtering processing, such as Gaussian filtering, can be performed on each acquired image in the set to be detected. The noise-reduced acquired image set can be used for the subsequent position deviation process.

[0135] S203: For each two adjacent images in the detection set, the corresponding image to be detected is acquired, and the initial acquisition position deviation is determined based on the pixel difference or based on the normalized cross-correlation coefficient, so as to obtain an initial acquisition position deviation sequence composed of multiple initial acquisition position deviations.

[0136] In step S203, the initial acquisition position deviation between the images to be detected corresponding to each two adjacent image acquisitions in the detection set can be determined. Specifically, this can be determined by the pixel value difference or by normalized cross-correlation coefficients and interpolation processing as described in step S102 above. Arranging and combining multiple initial acquisition position deviations according to the image acquisition order yields an initial acquisition position deviation sequence for subsequent vibration signal data analysis.

[0137] S204: Optimize each initial acquisition position deviation in the initial acquisition position deviation sequence using a Kalman filter to determine multiple corresponding optimized acquisition position deviations.

[0138] In step S204, a Kalman filter can be used to determine the predicted acquisition position deviation corresponding to each initial acquisition position deviation based on the previous initial acquisition position deviation, and further optimize the acquisition position deviation based on the predicted position deviation to effectively filter potential noise and aperiodic acquisition errors.

[0139] S205: Perform function fitting on the acquisition position deviation sequence composed of optimized acquisition position deviations, and eliminate charge drift of the optimized acquisition position deviations based on the fitting function.

[0140] In step S205, considering that repeated scanning of the same area by the electron beam will cause charge accumulation, the accuracy of the acquired image will be affected by charge drift. Therefore, the charge drift of harmful acquisition position deviation can be eliminated by function fitting, so as to obtain a more accurate optimized acquisition position deviation.

[0141] S206: Perform Discrete Fourier Transform processing on the optimized acquisition position deviation sequence, and determine the vibration signal data corresponding to the acquired image set based on the obtained spectrum data.

[0142] In step S206, the frequency domain transformation of the optimized acquisition position deviation sequence can be performed using Discrete Fourier Transform to determine the corresponding spectral data. Further, the signal data corresponding to each component signal in the vibration signal, such as frequency, amplitude, and phase information, can be determined based on the spectral data, and combined to obtain the vibration signal data corresponding to the vibration signal.

[0143] S207: Based on the vibration signal data, calculate the position compensation amount corresponding to each component signal in the vibration signal using the sine function formula, and further determine the comprehensive position compensation amount.

[0144] S208: Based on the comprehensive position compensation amount, the vibration interference correction is performed on the actual acquired image of the target wafer to obtain the corrected acquired image.

[0145] Steps S207 and S208 can be used to correct for interference in real images affected by vibration signals, effectively eliminate acquisition errors caused by vibration signals, and significantly improve the accuracy of acquired images.

[0146] S209: Determine the vibration signal type based on the vibration signal data, and make hardware adjustments for the vibration anomalies corresponding to the vibration signal type. After adjustment, acquire a real image of the target wafer without vibration interference.

[0147] In step S209, vibration interference can be eliminated by addressing the source of vibration, enabling the electron microscope to directly and accurately acquire images of the target wafer, thereby improving acquisition accuracy and efficiency.

[0148] The specific details of steps S201 to S209 are described in detail in the corresponding embodiments of steps S101 to S105, and will not be repeated here.

[0149] The above describes the specific implementation of the wafer image correction method provided in this application. The technical solution provided in this application can achieve accurate detection of vibration signals that may affect the accuracy of the acquired images by repeatedly acquiring images of the same pattern area. When determining the positional error between images, Kalman filter optimization and additional processing to eliminate charge drift through function fitting can be performed, significantly improving the accuracy of determining the acquisition position deviation and providing a practical basis for subsequent vibration signal analysis.

[0150] Based on the detected vibration signal data, the technical solution provided in this application can also perform efficient and real-time vibration interference correction on wafer images, greatly improving the accuracy of the acquired images corresponding to the target wafer. Furthermore, this application can also directly adjust the hardware based on the vibration signal data to address vibration anomalies, thus solving the vibration problem at its root.

[0151] Compared to signal monitoring based on vibration sensors with high usage and maintenance costs, the technical solution provided in this application does not require external sensor equipment, making it more convenient and significantly saving costs. At the same time, it can improve detection accuracy and fully meet the real-time requirements for solving vibration signal interference problems.

[0152] Based on the wafer image correction method provided in the above embodiments, this application also provides specific implementation methods of the wafer image correction device, please refer to the following embodiments.

[0153] Figure 3 This is a schematic diagram of the structure of a wafer image correction apparatus provided in another embodiment of this application. The wafer image correction apparatus 300 includes:

[0154] Image acquisition unit 301 is used to repeatedly acquire images of the target pattern area on the target wafer using an electron microscope, and to determine an image set including multiple acquired images. The initial acquisition position deviation represents the difference in acquisition position between two acquired images in two adjacent image acquisitions.

[0155] The deviation determination unit 302 is used to determine the initial acquisition position deviation sequence based on the acquisition images corresponding to each two adjacent image acquisitions in the acquisition image set. The ranking order of each initial acquisition position deviation in the initial acquisition position deviation sequence is determined according to the image acquisition order.

[0156] The deviation optimization unit 303 is used to determine the optimized acquisition position deviation of each initial acquisition position deviation based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence.

[0157] The vibration detection unit 304 is used to determine the vibration signal data corresponding to the set of acquired images based on multiple optimized acquisition position deviations.

[0158] The image correction unit 305 is used to correct vibration interference on the actual acquired image of the target wafer based on vibration signal data, so as to obtain the corrected acquired image of the target wafer.

[0159] In some embodiments, the image acquisition unit 301 is specifically used for:

[0160] Obtain the predicted vibration direction and vibration frequency detection standard corresponding to the vibration signal to be detected;

[0161] The image acquisition speed is determined based on the vibration frequency detection standard;

[0162] Multiple images were obtained by repeatedly acquiring images of the target graphic region along the predicted vibration direction using an electron microscope, based on the image acquisition speed.

[0163] Based on the image acquisition order, multiple acquired images are arranged and combined to obtain an image set.

[0164] In some embodiments, the deviation determination unit 302 is specifically used for:

[0165] For each two adjacent images in the acquired image set, acquire the corresponding acquired image and determine the pixel values ​​corresponding to multiple pixels in the two acquired images;

[0166] Based on the pixel values, determine the difference in pixel values ​​between pixels at the same image location in two acquired images;

[0167] The initial acquisition position deviation between the two acquired images is determined based on the pixel value difference.

[0168] The initial acquisition position deviation sequence is determined based on multiple initial acquisition position deviations and the image acquisition sequence.

[0169] In some embodiments, the deviation determination unit 302 is specifically used for:

[0170] For each two adjacent images in the acquired image set, acquire the corresponding acquired images and determine the pixel value data corresponding to the two acquired images;

[0171] The pixel value data corresponding to the two acquired images are normalized respectively to obtain the normalized pixel value data corresponding to the two acquired images.

[0172] Based on the normalized pixel value data corresponding to the two acquired images and the preset acquisition position deviation range, determine the cross-correlation coefficient corresponding to each candidate acquisition position deviation in the acquisition position deviation range.

[0173] Based on the maximum cross-correlation coefficient and the cross-correlation coefficients corresponding to the adjacent candidate acquisition position deviations of the candidate acquisition position deviation to which the maximum cross-correlation coefficient belongs, the initial acquisition position deviations corresponding to the two acquisition images are determined.

[0174] The initial acquisition position deviation sequence is determined based on multiple initial acquisition position deviations and the image acquisition sequence.

[0175] In some embodiments, the deviation optimization unit 303 is specifically used for:

[0176] The first initial acquisition position deviation in the initial acquisition position deviation sequence is taken as the optimized acquisition position deviation of the first initial acquisition position deviation.

[0177] For each initial acquisition position deviation except the first initial acquisition position deviation, based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation of the initial acquisition position deviation, the acquisition position deviation of the two acquisition images to which the initial acquisition position deviation belongs is predicted, and the predicted acquisition position deviation of the initial acquisition position deviation is determined.

[0178] The predicted acquisition position deviation and the initial acquisition position deviation are weighted and fused to determine the optimized acquisition position deviation of the initial acquisition position deviation.

[0179] In some embodiments, the deviation optimization unit 303 is specifically used for:

[0180] Based on multiple optimized acquisition position deviations and the acquisition times corresponding to multiple acquired images, function fitting is performed to determine the fitting function corresponding to the multiple optimized acquisition position deviations.

[0181] Based on the fitting function, the charge accumulation drift component corresponding to each optimized acquisition position deviation is determined;

[0182] For each optimized acquisition position deviation, charge drift elimination is performed based on the charge accumulation drift component corresponding to the optimized acquisition position deviation, resulting in the acquisition position deviation after drift elimination.

[0183] The vibration detection unit 304 described above is specifically used for:

[0184] Based on the positional deviation after multiple drift eliminations, the vibration signal data corresponding to the acquired image set is determined.

[0185] In some embodiments, the vibration detection unit 304 is specifically used for:

[0186] Determine the spectral data corresponding to the acquisition position deviation sequence composed of multiple optimized acquisition position deviations;

[0187] Based on the spectrum data, determine the vibration signal data corresponding to the vibration signal in the collected image set. The vibration signal includes the first harmonic, second harmonic, third harmonic and fourth harmonic.

[0188] In some embodiments, the image correction unit 305 is specifically used for:

[0189] Based on the image acquisition time and vibration signal data corresponding to the actual acquired images, the position compensation amounts corresponding to the first, second, third, and fourth harmonics of the actual acquired images are determined respectively.

[0190] The comprehensive position compensation amount is determined based on the position compensation amounts corresponding to the first, second, third, and fourth harmonics, respectively.

[0191] Based on the comprehensive position compensation amount, vibration interference position compensation is performed on the actual acquired image to obtain the corrected acquired image.

[0192] In some embodiments, the wafer image correction apparatus 300 further includes a hardware adjustment unit 306, which is specifically used for:

[0193] Based on the vibration signal data and the preset vibration signal judgment criteria, determine the vibration signal type corresponding to the vibration signal data;

[0194] Hardware adjustments were made to address vibration anomalies corresponding to different vibration signal types. After adjustments, images of the target wafer were re-acquired to obtain real images free from vibration interference.

[0195] Figure 4 This is a schematic diagram of the structure of a wafer image correction device provided in another embodiment of this application.

[0196] The wafer image correction device may include a processor 401 and a memory 402 storing computer program instructions.

[0197] Specifically, the processor 401 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0198] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 402 may include removable or non-removable (or fixed) media. Where appropriate, memory 402 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 402 is non-volatile solid-state memory.

[0199] In a particular embodiment, memory 402 includes read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0200] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any of the wafer image correction methods in the above embodiments.

[0201] In one example, the wafer image correction device may also include a communication interface 403 and a bus 410. Wherein, as Figure 4 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 410 and complete communication with each other.

[0202] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0203] Bus 410 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 410 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0204] Furthermore, in conjunction with the wafer image correction methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the wafer image correction methods in the above embodiments.

[0205] This application also provides a computer program product, including a computer program that, when executed, implements any of the wafer image correction methods described in the above embodiments.

[0206] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0207] The functional blocks shown in the above-described structural diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0208] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0209] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0210] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A wafer image correction method, characterized in that, include: The target pattern region on the target wafer is repeatedly imaged using an electron microscope to obtain a set of acquired images, which includes multiple acquired images. Based on the acquired images from every two adjacent acquisitions in the acquired image set, an initial acquisition position deviation sequence is determined. The ranking order of each initial acquisition position deviation in the initial acquisition position deviation sequence is determined according to the image acquisition order. The initial acquisition position deviation represents the acquisition position difference between two acquired images from two adjacent acquisitions. For each initial acquisition position deviation, an optimized acquisition position deviation is determined based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence. Based on the multiple optimized acquisition position deviations, the vibration signal data corresponding to the acquired image set is determined; Based on the vibration signal data, vibration interference correction is performed on the actual acquired image of the target wafer to obtain the corrected acquired image of the target wafer; For each initial acquisition position deviation, determining the optimized acquisition position deviation based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation in the initial acquisition position deviation sequence includes: The first initial acquisition position deviation in the initial acquisition position deviation sequence is taken as the optimized acquisition position deviation of the first initial acquisition position deviation; For each initial acquisition position deviation other than the first initial acquisition position deviation, based on the optimized acquisition position deviation corresponding to at least one preceding initial acquisition position deviation of the initial acquisition position deviation, acquisition position deviation prediction is performed on the two acquisition images to which the initial acquisition position deviation belongs, and the predicted acquisition position deviation of the initial acquisition position deviation is determined. The predicted acquisition position deviation and the initial acquisition position deviation are weighted and fused to determine the optimized acquisition position deviation of the initial acquisition position deviation.

2. The method according to claim 1, characterized in that, Multiple repeated image acquisitions were performed on the target pattern region on the target wafer using an electron microscope to determine an image set comprising multiple acquired images, including: Obtain the predicted vibration direction and vibration frequency detection standard corresponding to the vibration signal to be detected; The image acquisition speed is determined based on the vibration frequency detection standard. The target graphic region is repeatedly imaged using the electron microscope along the predicted vibration direction, based on the image acquisition speed, to obtain the multiple acquired images. According to the image acquisition order, the multiple acquired images are arranged and combined to obtain the acquired image set.

3. The method according to claim 1, characterized in that, Based on the acquired images corresponding to each two adjacent image acquisitions in the acquired image set, the initial acquisition position deviation sequence is determined, including: For each two adjacent images in the acquired image set, the corresponding acquired images are acquired, and the pixel values ​​corresponding to multiple pixels in the two acquired images are determined. Based on the pixel values, determine the pixel value difference between pixels at the same image position in the two acquired images; Based on the pixel value difference, the initial acquisition position deviation corresponding to the two acquired images is determined; The initial acquisition position deviation sequence is determined based on multiple initial acquisition position deviations and the image acquisition order.

4. The method according to claim 1, characterized in that, Based on the acquired images corresponding to each two adjacent image acquisitions in the acquired image set, the initial acquisition position deviation sequence is determined, including: For each two adjacent images in the acquired image set, acquire the corresponding acquired image and determine the pixel value data corresponding to the two acquired images; The pixel value data corresponding to the two acquired images are normalized respectively to obtain the normalized pixel value data corresponding to the two acquired images. Based on the normalized pixel value data corresponding to the two acquired images and the preset acquisition position deviation range, determine the cross-correlation coefficient corresponding to each candidate acquisition position deviation in the acquisition position deviation range; The initial acquisition position deviation corresponding to the two acquired images is determined based on the maximum cross-correlation coefficient and the cross-correlation coefficient corresponding to the adjacent candidate acquisition position deviations of the candidate acquisition position deviation to which the maximum cross-correlation coefficient belongs. The initial acquisition position deviation sequence is determined based on multiple initial acquisition position deviations and the image acquisition order.

5. The method according to claim 1, characterized in that, Before determining the vibration signal data corresponding to the acquired image set based on multiple optimized acquisition position deviations, the method further includes: Based on the multiple optimized acquisition position deviations and the acquisition times corresponding to the multiple acquired images, a function fitting is performed to determine the fitting function corresponding to the multiple optimized acquisition position deviations; Based on the fitting function, determine the charge accumulation drift component corresponding to each optimized acquisition position deviation; For each optimized acquisition position deviation, charge drift elimination is performed based on the charge accumulation drift component corresponding to the optimized acquisition position deviation, to obtain the drift-eliminated acquisition position deviation corresponding to the optimized acquisition position deviation. Based on multiple optimized acquisition position deviations, the vibration signal data corresponding to the acquired image set is determined, including: Based on the positional deviations acquired after multiple drift eliminations, the vibration signal data corresponding to the acquired image set is determined.

6. The method according to claim 1, characterized in that, Based on multiple optimized acquisition position deviations, the vibration signal data corresponding to the acquired image set is determined, including: Determine the spectral data corresponding to the acquisition position deviation sequence composed of multiple optimized acquisition position deviations; Based on the spectrum data, the vibration signal data corresponding to the vibration signal in the acquired image set is determined, and the vibration signal includes the first harmonic, the second harmonic, the third harmonic and the fourth harmonic.

7. The method according to claim 6, characterized in that, Based on the vibration signal data, vibration interference correction is performed on the actual acquired image of the target wafer to obtain the corrected acquired image of the target wafer, including: Based on the image acquisition time corresponding to the actual acquired image and the vibration signal data, the position compensation amount corresponding to the actual acquired image and the first harmonic, the second harmonic, the third harmonic and the fourth harmonic is determined respectively; The comprehensive position compensation amount is determined based on the position compensation amounts corresponding to the first harmonic, the second harmonic, the third harmonic, and the fourth harmonic, respectively. Based on the comprehensive position compensation amount, vibration interference position compensation is performed on the actual acquired image to obtain the corrected acquired image.

8. The method according to claim 1, characterized in that, Before performing vibration interference correction on the actual acquired image of the target wafer based on the vibration signal data to obtain the corrected acquired image of the target wafer, the method further includes: Based on the vibration signal data and the preset vibration signal judgment criteria, determine the vibration signal type corresponding to the vibration signal data; Hardware adjustments were made to address the vibration anomalies corresponding to the vibration signal type. After the adjustments, the target wafer was re-acquired to obtain a true image without vibration interference.

9. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device performs the wafer image correction method as described in any one of claims 1-8.

Images