Sun azimuth determination method and device

Abstract

The invention relates to the technical field of data processing, and discloses a solar azimuth determination method and device. The method comprises the following steps: acquiring imaging characteristics of imaging points of solar rays; determining a target distance between the imaging points based on the imaging features; wherein the target distance is used for representing the minimum distance between the imaging points; determining a target reference point corresponding to the imaging point from a preset reference table based on the target distance; and determining the sun orientation based on the target reference point and the imaging point. By analyzing the imaging characteristics of the solar rays in detail, the position of the imaging point can be more accurately determined, and fuzziness and errors caused by the pinhole imaging principle are reduced. And mapping the imaging point to a more accurate target reference point by using a preset reference table. The mapping relation can be based on a large amount of experimental data and calibration results, so that the precision of azimuth inference is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, computer equipment, storage medium and program product for determining the sun's position. Background Art

[0002] As a vital optical attitude sensor in the aerospace field, the core function of the solar sensor is to determine the position of the sun in the spacecraft's stellar coordinate system by accurately sensing the orientation of the solar vector, thereby providing key navigation information for the spacecraft's orbital control and attitude control. This technology not only ensures the stable operation of spacecraft in complex space environments, but is also crucial for protecting high-precision instruments (such as star sensors and earth sensors) from abnormal attitudes. In addition, the solar sensor also undertakes the important task of providing reference signals for the positioning of the spacecraft's solar panels, ensuring the efficient operation of the spacecraft's energy system.

[0003] At present, solar sensors are mainly divided into single-hole type and narrow-slit type. Single-hole and narrow-slit solar sensors use the principle of pinhole imaging to infer the position information of the spacecraft relative to the sun by directly calculating the relative position of the imaging point and the single hole / narrow slit.

[0004] However, although this type of method has a simple structure, it is limited by the limitations of pinhole imaging, its accuracy is often not high, and the field of view is small, making it difficult to meet high-precision application requirements. Summary of the invention

[0005] In view of this, the present invention provides a method, device, computer equipment, storage medium and program product for determining the solar position to solve the problem that single-hole and narrow-slit solar sensors are limited by the limitations of pinhole imaging, their accuracy is often not high, and the field of view angle is small, making it difficult to meet the application requirements of high precision and large field of view.

[0006] In a first aspect, the present invention provides a method for determining the position of the sun, comprising: acquiring imaging features of imaging points of sunlight; determining a target distance between each imaging point based on the imaging features; wherein the target distance is used to characterize the minimum distance between each imaging point; based on the target distance, determining a target reference point corresponding to the imaging point from a preset reference benchmark table; and determining the position of the sun based on the target reference point and the imaging point.

[0007] The method for determining the solar position provided in this embodiment can more accurately determine the position of the imaging point by analyzing the imaging characteristics of the sun's rays in detail, thereby reducing the ambiguity and error caused by the pinhole imaging principle. The imaging point is mapped to a more accurate target reference point using a preset reference datum table. This mapping relationship can be based on a large amount of experimental data and calibration results, thereby significantly improving the accuracy of azimuth inference. In addition, by simultaneously analyzing the positions and characteristics of multiple imaging points, a wider field of view can be covered. This method is no longer limited to the field of view of a single pinhole or narrow slit, thereby effectively expanding the field of view.

[0008] In an optional embodiment, the process of constructing a preset reference datum table includes: obtaining reference points of the mask and reference point numbers; wherein the reference points include: anchor points and cursors, the cursors are used to indicate points of a single aperture, and the anchor points are used to indicate points of a combination of multiple apertures; respectively determining the aperture center of the anchor point and the aperture center of the cursor; based on the aperture center of the anchor point and the aperture center of the cursor, determining the minimum distance between the anchor point and the cursor; using the minimum distance between the anchor point and the cursor as the first minimum base, determining the ratio between adjacent reference points; and constructing the preset reference datum table based on the reference point numbers and the ratio between adjacent reference points.

[0009] The method for determining the sun's position provided in this embodiment can more accurately indicate the key points of imaging by defining anchor points and cursors as reference points. The anchor points correspond to points of multiple aperture combinations, providing a more stable positioning reference; while the cursors target points of a single aperture and can capture more subtle position changes. This combination enables the system to handle both macro and micro positioning requirements, thereby improving overall positioning accuracy. In addition, by numbering each reference point and the ratio between adjacent reference points, the position of each reference point can be accurately determined, thereby making the preset reference reference table more accurate.

[0010] In an optional embodiment, the reference point numbering includes: row reference point numbering and column reference point numbering; wherein, based on the reference point numbering and the ratio between adjacent reference points, a preset reference benchmark table is constructed, including: based on the row reference point numbering and the ratio between adjacent reference points, determining the first reference benchmark table corresponding to the reference points arranged in rows; based on the column reference point numbering and the ratio between adjacent reference points, determining the second reference benchmark table corresponding to the reference points arranged in columns; and constructing a preset reference benchmark table based on the first reference benchmark table and the second reference benchmark table.

[0011] The method for determining the solar position provided in this embodiment can further divide the reference points by dividing them into row reference points and column reference points, so that the imaging points corresponding to the reference points can be determined more accurately by using a preset reference datum table.

[0012] In an optional embodiment, the imaging features include: centroid coordinates; wherein, based on the imaging features, determining the target distance between each imaging point includes: determining the distance between each imaging point based on the centroid coordinates of each imaging point; and comparing the distances between each imaging point to determine the target distance.

[0013] In the method for determining the sun's position provided in this embodiment, the centroid coordinates are obtained by calculating the weighted center of the grayscale value or brightness value of all pixels in the imaging point. This process fully considers the overall distribution characteristics of the imaging point. Therefore, the distance calculated based on the centroid coordinates is more accurate and can reduce the error caused by the irregular shape of the imaging point or the uneven brightness distribution. In addition, by determining the distance between every two imaging points and then determining the target distance from all the distances, the accuracy of the target distance determination can be improved.

[0014] In an optional embodiment, the imaging feature at least includes: image point area; wherein, based on the target distance, the target reference point corresponding to the imaging point is determined from a preset reference reference table, including: based on the image point area, determining a first imaging point corresponding to an anchor point in the imaging point and a second imaging point corresponding to a cursor; wherein the area of ​​the first imaging point is greater than the area of ​​the second imaging point; using the target distance as a second minimum cardinality, determining a ratio between imaging points arranged in rows and a ratio between imaging points arranged in columns; determining a first target ratio from a preset reference reference table based on a ratio between the first imaging point, the second imaging point and imaging points arranged in rows; determining a second target ratio from a preset reference reference table based on a ratio between the first imaging point, the second imaging point and imaging points arranged based on columns; determining each first reference point arranged in rows based on the first target ratio; determining each second reference point arranged in columns based on the second target ratio; and using the first reference point and the second reference point as target reference points.

[0015] The method for determining the sun's position provided in this embodiment can effectively distinguish the imaging points corresponding to the anchor point and the cursor by the difference in the image point area. The anchor point usually corresponds to a larger imaging area, while the cursor corresponds to a smaller imaging area. This distinction enables the system to more accurately identify different types of imaging points, thereby improving the accuracy of subsequent processing.

[0016] In addition, by using the target distance as the second minimum base number to determine the proportional relationship between the imaging points arranged in rows and columns, the proportional relationship can be flexibly adjusted according to different imaging conditions, thereby corresponding to the preset reference benchmark table, and then accurately determining the reference point corresponding to the imaging point.

[0017] In addition, the target reference point can be more accurately located from the preset reference table by combining the target distance and the pixel area. This not only improves the response speed of the system, but also reduces the error introduced by wrong matching.

[0018] In an optional embodiment, the method also includes: obtaining the minimum distance between multiple apertures in the anchor point and the distance between the mask and the imaging plane; detecting whether the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet a first preset condition, whether the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet a second preset condition, and whether the distance between the mask and the imaging plane meets a third preset condition; if the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet the second preset condition, and the distance between the mask and the imaging plane meets the third preset condition, then the preset reference benchmark table is determined to be qualified.

[0019] The method for determining the sun's position provided in this embodiment performs multiple checks on multiple key parameters by setting the first, second and third preset conditions. This multiple check mechanism can significantly improve the reliability of the system and ensure that the target reference point corresponding to the imaging point can still be accurately determined under complex and changeable observation conditions.

[0020] In a second aspect, the present invention provides a device for determining the solar position, which includes: an acquisition module for acquiring imaging characteristics of imaging points of sunlight; a first determination module for determining a target distance between each imaging point based on the imaging characteristics; wherein the target distance is used to characterize the minimum distance between each imaging point; a second determination module for determining a target reference point corresponding to the imaging point from a preset reference benchmark table based on the target distance; and a third determination module for determining the solar position based on the target reference point and the imaging point.

[0021] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for determining the solar position of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for determining the sun's position according to the first aspect or any corresponding embodiment thereof.

[0023] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for determining the sun's position according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 is a schematic flow chart of a method for determining the sun's position according to an embodiment of the present invention;

[0026] Figure 2 is a schematic diagram of an image of a mask according to an embodiment of the present invention;

[0027] Figure 3 is a schematic diagram of an imaging point according to an embodiment of the present invention;

[0028] Figure 4 is a schematic diagram of an “imaging point—reference point” association relationship according to an embodiment of the present invention;

[0029] Figure 5 is a structural block diagram of a device for determining the sun's position according to an embodiment of the present invention;

[0030] Figure 6 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0032] Based on relevant technologies, the core function of the solar sensor, as a vital optical attitude sensor in the aerospace field, is to accurately sense the orientation of the solar vector and determine the position of the sun in the spacecraft's stellar coordinate system, thereby providing key navigation information for the spacecraft's orbital control and attitude control. This technology not only ensures the stable operation of spacecraft in complex space environments, but is also crucial for protecting high-precision instruments (such as star sensors and earth sensors) from abnormal attitudes. In addition, the solar sensor also undertakes the important task of providing reference signals for the positioning of the spacecraft's solar panels, ensuring the efficient operation of the spacecraft's energy system.

[0033] At present, solar sensors are mainly divided into single-hole type and narrow-slit type. Single-hole and narrow-slit solar sensors use the principle of pinhole imaging to infer the position information of the spacecraft relative to the sun by directly calculating the relative position of the imaging point and the single hole / narrow slit.

[0034] However, although this type of method has a simple structure, it is limited by the limitations of pinhole imaging, its accuracy is often not high, and the field of view is small, making it difficult to meet high-precision application requirements.

[0035] In addition, the multi-aperture solution has the potential for large field of view and high precision in theory, but it still faces many challenges in practical applications. First, the multi-aperture solution needs to solve the problem of correct, fast and robust matching between apertures, which is a prerequisite for ensuring the high refresh rate of the solar sensor and adapting to various scene angles. However, the existing multi-aperture solar sensors often have shortcomings in aperture matching. For example, the solution proposed in the document "Zhang L, Zhan H, Liu X, et al. A wide-field and high-resolution lensless compound eye microsystem for real-time target motion perception. Microsystems & Nanoengineering, 2022, 8 (1): 83." Although multi-aperture imaging is achieved by designing a dedicated MEMS mask pattern, the aperture type is single and only relies on the absolute value of the distance between the apertures for matching, which is easy to cause mismatching, and the calculation is large, and the matching efficiency and speed are difficult to improve.

[0036] Based on this, the method for determining the sun's position provided by the present invention can more accurately determine the position of the imaging point by analyzing the imaging characteristics of the sun's rays in detail, thereby reducing the ambiguity and error caused by the pinhole imaging principle. Using a preset reference datum table, the imaging point is mapped to a more accurate target reference point. This mapping relationship can be based on a large amount of experimental data and calibration results, thereby significantly improving the accuracy of azimuth inference. In addition, by simultaneously analyzing the positions and characteristics of multiple imaging points, a wider field of view can be covered. This method is no longer limited to the field of view of a single pinhole or narrow slit, thereby effectively expanding the field of view.

[0037] According to an embodiment of the present invention, an embodiment of a method for determining the position of the sun is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0038] In this embodiment, a method for determining the sun's position is provided, which can be used in computer devices, such as computers, servers, etc. Figure 1 FIG. 1 is a flow chart of a method for determining the sun's position according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0039] Step S101, acquiring imaging features of imaging points of sunlight.

[0040] Imaging features can be used to characterize the key features of imaging points. Among them, imaging features may include: centroid coordinates, grayscale values, and image point areas, etc., which are not specifically limited here. The centroid coordinates can be the weighted center position of all pixel grayscale values, representing the average position of the imaging point. The centroid coordinates can be obtained by calculating the weighted average position of the grayscale values ​​of all pixels in the imaging point. The grayscale value of the imaging point reflects its brightness information and is one of the basic features in image processing. The grayscale value is proportional to the brightness of the imaging point. The imaging area of ​​the imaging point refers to the number of pixels or the area occupied by it on the imaging plane, reflecting the size and shape of the imaging point. Specifically, the centroid coordinates, grayscale values, and image point areas of the imaging point can be automatically extracted using image processing software (such as MATLAB, Python's OpenCV library), or these imaging features can be directly obtained through hardware devices (such as dedicated image processing modules), etc., which are not specifically limited here and can be implemented by those skilled in the art. For example: the pixel matrix of an imaging point is 3x3, and the grayscale values ​​are [50, 60, 70; 80, 90, 100; 110, 120, 130] respectively. Then, its centroid coordinates, grayscale value (usually the average value or maximum value, etc.) and image point area (9 pixels) can be obtained by calculation.

[0041] Step S102, based on the imaging features, determining the target distance between the imaging points; wherein the target distance is used to characterize the minimum distance between the imaging points.

[0042] The target distance is used to characterize the minimum distance between each imaging point. For example, if the distance between imaging point A and imaging point B is 5, and the distance between imaging point A and imaging point C is 3, then the target distance can be 3. Specifically, the target distance can be determined by Euclidean distance, Manhattan distance, Chebyshev distance, etc., which is not specifically limited here and can be implemented by those skilled in the art.

[0043] Step S103: based on the target distance, determine the target reference point corresponding to the imaging point from a preset reference table.

[0044] The preset reference benchmark table contains a database or table of multiple reference points and their corresponding information, which is used to provide an accurate reference position for the imaging point. Specifically, the target reference point corresponding to the imaging point that matches it is searched in the preset reference benchmark table. The reference benchmark table is usually a database or table containing multiple reference points and their corresponding information. Among them, efficient algorithms such as binary search and hash tables can be used to quickly locate the target reference point in the reference benchmark table, and machine learning or deep learning algorithms can also be used for matching, etc., which are not specifically limited here and can be implemented by those skilled in the art. For example: There is an entry in the preset reference benchmark table, whose target distance range matches the target distance calculated in step S102, and contains information of one or more target reference points (such as coordinates, numbers, etc.), then these target reference points can be used as reference points corresponding to the imaging point.

[0045] Step S104, determining the sun's position based on the target reference point and the imaging point.

[0046] The solar position is used to characterize the direction information of the sun's rays relative to the sun sensor, usually including parameters such as azimuth and elevation. Specifically, the solar position can be calculated using traditional methods such as triangulation and geometric analysis, and a neural network model can be used for more accurate calculations. For example: the sun's rays shine through the target reference point at the imaging point to form a first ray, and the sun's rays perpendicular to the target reference point form a second ray, and then the direction angle of the sun's rays is determined by the first ray and the second ray, thereby determining the position of the sun's rays.

[0047] The method for determining the solar position provided in this embodiment can more accurately determine the position of the imaging point by analyzing the imaging characteristics of the sun's rays in detail, thereby reducing the ambiguity and error caused by the pinhole imaging principle. The imaging point is mapped to a more accurate target reference point using a preset reference datum table. This mapping relationship can be based on a large amount of experimental data and calibration results, thereby significantly improving the accuracy of azimuth inference. In addition, by simultaneously analyzing the positions and characteristics of multiple imaging points, a wider field of view can be covered. This method is no longer limited to the field of view of a single pinhole or narrow slit, thereby effectively expanding the field of view.

[0048] In an optional implementation, the process of constructing a preset reference benchmark table includes:

[0049] Step a1, obtaining the reference points of the mask and the reference point numbers; wherein the reference points include: anchor points and cursors, the cursors are used to indicate points of a single aperture, and the anchor points are used to indicate points of a combination of multiple apertures.

[0050] A mask can be a template or layer that defines a specific area or filters specific information during imaging or measurement; the mask can be attached to the sun sensor, and then sunlight is used to illuminate the holes in the sun sensor and image through the mask. Verniers are used to indicate points of a single aperture, and anchor points are used to indicate points of multiple aperture combinations. The number of the reference point can be used to characterize the identity information of each reference point. For example: there is an anchor point consisting of three small holes on the mask, which is numbered A1, and a single vernier point, which is numbered C1.

[0051] Specifically, image processing software (such as MATLAB, Python's OpenCV library) can be used to automatically identify and extract reference points and their numbers on the mask. Reference points can also be located by a preset algorithm or template matching technology, etc., which is not specifically limited here and can be implemented by those skilled in the art.

[0052] Step a2, respectively determining the aperture center of the anchor point and the aperture center of the cursor.

[0053] The aperture center can be the geometric center of all pixels or light spots in the aperture, which is used to indicate the position of the aperture. Among them, the aperture center of the cursor is the center point of a single aperture, and the aperture center of the anchor point can be the joint center after averaging the geometric centers of M closely arranged apertures. Specifically, the center of mass calculation method in image processing can be used to determine the aperture center, and other methods can also be used to determine the aperture center. No specific limitation is made here, and it can be implemented by those skilled in the art. For example: the aperture center coordinates of anchor point A1 calculated by image processing software are (x1, y1), and the aperture center coordinates of cursor C1 are (x2, y2).

[0054] Step a3, determining the minimum distance between the anchor point and the cursor based on the aperture center of the anchor point and the aperture center of the cursor.

[0055] The minimum distance between the anchor point and the cursor can be the straight-line distance between the anchor point and the cursor, that is, the minimum distance between their aperture centers. Specifically, the distance between two points can be calculated using the Euclidean distance formula. If the mask has specific calibration marks or grids, these marks can also be used to calculate the distance, etc., which is not specifically limited here and can be implemented by those skilled in the art. Then, after determining the distance between the anchor point and the cursor, all distances are compared, and then the minimum distance between the anchor point and the cursor is determined.

[0056] Step a4, taking the minimum distance between the anchor point and the cursor as the first minimum base, determining the ratio between adjacent reference points.

[0057] The first minimum cardinality can be used to characterize the minimum distance, and then the ratio between adjacent reference points is determined based on the first minimum cardinality. For example, if the minimum distance between the anchor point S1 and the cursor C1 is known to be d, and the distance between the adjacent anchor points S2 and S1 is 2d through measurement, then the ratio between them is 2:1.

[0058] Step a5: construct a preset reference datum table based on the numbers of the reference points and the ratios between adjacent reference points.

[0059] Using the reference point numbers and their proportional relationships, a preset reference table containing the position information of all reference points is constructed. This reference table can be used for positioning and calibration in subsequent imaging or measurement processes.

[0060] The method for determining the sun's position provided in this embodiment can more accurately indicate the key points of imaging by defining anchor points and cursors as reference points. The anchor points correspond to points of multiple aperture combinations, providing a more stable positioning reference; while the cursors target points of a single aperture and can capture more subtle position changes. This combination enables the system to handle both macro and micro positioning requirements, thereby improving overall positioning accuracy. In addition, by numbering each reference point and the ratio between adjacent reference points, the position of each reference point can be accurately determined, thereby making the preset reference reference table more accurate.

[0061] In an optional implementation, the reference point numbering includes: row reference point numbering and column reference point numbering; wherein the above step a5 includes:

[0062] Step a51, determining a first reference datum table corresponding to the reference points arranged in the row based on the row reference point numbers and the ratios between adjacent reference points.

[0063] Step a52, determining a second reference datum table corresponding to the reference points arranged in the column based on the column reference point numbers and the ratios between adjacent reference points.

[0064] Reference points can be divided into row reference points and column reference points, that is, each row has a cursor and an anchor point, each column has a cursor and an anchor point, each cursor and anchor point has a corresponding number, and then they are sorted in rows and columns to construct a first reference benchmark table corresponding to the reference points arranged in rows and a second reference benchmark table corresponding to the reference points arranged in columns.

[0065] Step a53: construct a preset reference reference table based on the first reference reference table and the second reference reference table.

[0066] Then, the first reference benchmark table and the second reference benchmark table are integrated to construct a preset reference benchmark table.

[0067] The method for determining the solar position provided in this embodiment can further divide the reference points by dividing them into row reference points and column reference points, so that the imaging points corresponding to the reference points can be determined more accurately by using a preset reference datum table.

[0068] In an optional embodiment, the imaging feature includes: centroid coordinates; wherein the above step S102 includes:

[0069] Step b1, determining the distance between each imaging point based on the centroid coordinates of each imaging point.

[0070] The target distance is used to characterize the minimum distance between each imaging point. For example: the distance between imaging point A and imaging point B is 5, and the distance between imaging point A and imaging point C is 3, then the target distance can be 3. Specifically, the distance between each imaging point can be determined by the centroid coordinates of each imaging point. Specifically, the centroid coordinates of each imaging point in the image are first calculated, and then the distance between the imaging points is calculated based on these coordinates. The centroid coordinates usually represent the geometric center of the brightness or grayscale value in the image, and are an important parameter in image analysis. The imaging point can be a light spot, a feature point, or other identifiable mark in the image. For example: two imaging points, whose centroid coordinates are (x1, y1) and (x2, y2) respectively. Using the Euclidean distance formula, the distance d between the imaging points can be calculated as:

[0071] Step b2, comparing the distances between the various imaging points to determine the target distance.

[0072] The calculated distances between all imaging points are compared to determine the minimum distance between the imaging points, and the minimum distance is taken as the target distance.

[0073] In the method for determining the sun's position provided in this embodiment, the centroid coordinates are obtained by calculating the weighted center of the grayscale value or brightness value of all pixels in the imaging point. This process fully considers the overall distribution characteristics of the imaging point. Therefore, the distance calculated based on the centroid coordinates is more accurate and can reduce the error caused by the irregular shape of the imaging point or the uneven brightness distribution. In addition, by determining the distance between every two imaging points and then determining the target distance from all the distances, the accuracy of the target distance determination can be improved.

[0074] In an optional implementation, the imaging feature at least includes: image point area; wherein the above step S103 includes:

[0075] Step c1, based on the image point area, determine the first imaging point corresponding to the anchor point and the second imaging point corresponding to the cursor in the imaging point; wherein the area of ​​the first imaging point is greater than the area of ​​the second imaging point.

[0076] From the above content, it can be seen that the anchor point is composed of M closely arranged apertures, and the cursor is composed of a single aperture, so the area of ​​the anchor point must be larger than the area of ​​the cursor. For the imaging plane, the area of ​​the first imaging point corresponding to the anchor point is larger than the area of ​​the second imaging point corresponding to the cursor. Then, according to the size of the area, the reference point that matches the imaging point is determined from the preset reference datum table.

[0077] Step c2: Taking the target distance as the second minimum base number, determining the ratio between the imaging points arranged in rows and the ratio between the imaging points arranged in columns.

[0078] The second minimum cardinality can be used to characterize the minimum distance, and then the ratio between the imaging points arranged in adjacent rows and the ratio between the imaging points arranged in columns are determined according to the second minimum cardinality. For example, if the minimum distance between the target distance F1 and the target distance F2 is known to be d, and the distance between the adjacent target distances F2 and F3 is 2d through measurement, then the ratio between them is 2:1.

[0079] Step c3, determining a first target ratio from a preset reference benchmark table based on the ratios among the first imaging point, the second imaging point and the imaging points arranged in a row.

[0080] After determining the ratio between the first imaging point and the second imaging point, a matching first target ratio is determined from a preset reference table; for example: first imaging points L1, L2, second imaging points K1, K2, wherein the order of row arrangement between the first imaging point and the second imaging point is: L1, K1, K2 and L2, and there are three distances between the four, namely, distance O1 between L1 and K1, distance O2 between K1 and K2, and distance O3 between K2 and L2, then O1:O2:O3 can be 1:3:2, and the first target ratio can be determined to be 1:3:2.

[0081] Step c4: determining a second target ratio from a preset reference standard table based on the ratio among the first imaging point, the second imaging point and the imaging point arranged based on the column.

[0082] The first imaging points are L1 and L2, and the second imaging points are K1 and K2. The order of the first imaging points and the second imaging points is L1, K1, K2 and L2. There are three distances between the four points, namely, the distance O1 between L1 and K1, the distance O2 between K1 and K2, and the distance O3 between K2 and L2. Then, O1:O2:O3 can be 1:3:2. Then, the first target ratio can be determined to be 1:3:2.

[0083] Step c5, determining each first reference point of the row arrangement based on the first target ratio.

[0084] Step c6, determining each second reference point of the column arrangement based on the second target ratio.

[0085] Step c7, taking the first reference point and the second reference point as target reference points.

[0086] After determining the first target ratio and the second target ratio, the ratio formed by the matching multiple reference points can be found from the preset reference datum table to determine the first reference point and the second reference point, and the first reference point and the second reference point are integrated to obtain the target reference point.

[0087] The method for determining the sun's position provided in this embodiment can effectively distinguish the imaging points corresponding to the anchor point and the cursor by the difference in the image point area. The anchor point usually corresponds to a larger imaging area, while the cursor corresponds to a smaller imaging area. This distinction enables the system to more accurately identify different types of imaging points, thereby improving the accuracy of subsequent processing.

[0088] In addition, by using the target distance as the second minimum base number to determine the proportional relationship between the imaging points arranged in rows and columns, the proportional relationship can be flexibly adjusted according to different imaging conditions, thereby corresponding to the preset reference benchmark table, and then accurately determining the reference point corresponding to the imaging point.

[0089] In addition, the target reference point can be more accurately located from the preset reference table by combining the target distance and the pixel area. This not only improves the response speed of the system, but also reduces the error introduced by wrong matching.

[0090] In an optional embodiment, the above method further includes:

[0091] Step d1, obtaining the minimum distance between multiple apertures in the anchor point and the distance between the mask and the imaging plane.

[0092] It can be seen from the above that the anchor point is composed of M closely arranged apertures, and there is an aperture with the smallest distance among the M closely arranged apertures. The mask of the sun sensor is a special optical element, usually designed to have a pattern or hole with a specific shape and structure, and these patterns or holes are precisely etched on the mask. Imaging plane: During the photolithography process, the plane on which the pattern is formed on the silicon wafer, that is, the position where the pattern is projected and solidified. The distance between the mask and the imaging plane refers to the distance from the mask to the solidified position. Specifically, a high-precision measuring tool (such as a laser rangefinder, a ruler under a microscope, etc.) can be used to directly measure the actual distance between each aperture in the anchor point. It is also possible to analyze the microscopic image of the anchor point through image processing technology, automatically calculate the minimum distance between the apertures, etc., which is not specifically limited here and can be implemented by those skilled in the art.

[0093] Step d2, detect whether the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, whether the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet the second preset condition, and whether the distance between the mask and the imaging plane meets the third preset condition.

[0094] The first preset condition can be to check whether the minimum distance between multiple apertures in the anchor point meets a specific threshold requirement, and whether the minimum distance between the anchor point and the cursor also meets the corresponding standard. The second preset condition can be to verify whether the relationship between the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meets a preset ratio or range. The third preset condition can be to separately check whether the distance between the mask and the imaging plane falls within the allowable error range. For example: the first preset condition: the minimum distance between apertures ≥ 0.4 microns, the minimum distance between the anchor point and the cursor ≥ 1 mm. The second preset condition: the distance from the mask to the imaging plane / the minimum distance between the apertures ≤ 20000 (i.e., a 20-fold relationship). The third preset condition: the distance from the mask to the imaging plane is between 9.9 mm and 10.1 mm, etc., which is not specifically limited here.

[0095] Step d3, if the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, the distance between the mask and the imaging plane and the minimum distance between the multiple apertures in the anchor point meet the second preset condition, and the distance between the mask and the imaging plane meets the third preset condition, then the preset reference benchmark table is determined to be qualified.

[0096] If all the test conditions meet the preset conditions, the preset reference table (or photolithography process parameters) is judged to be qualified. If any condition is not met, it is judged to be unqualified, and the photolithography process parameters may need to be adjusted or the measurement equipment may need to be recalibrated.

[0097] Preferably, whether the minimum distance between multiple apertures in the detection anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition can be used as the first condition, that is, whether the first condition is met is detected first. When the first condition is not met, there is no need to detect other conditions, and the preset reference benchmark table can also be determined to be unqualified.

[0098] The method for determining the sun's position provided in this embodiment performs multiple checks on multiple key parameters by setting the first, second and third preset conditions. This multiple check mechanism can significantly improve the reliability of the system and ensure that the target reference point corresponding to the imaging point can still be accurately determined under complex and changeable observation conditions.

[0099] In an alternative embodiment, in combination Figure 2 , Figure 3 and Figure 4 As shown, in a specific application scenario, the method may include:

[0100] The reference points on the MEMS mask are divided into two categories: anchor points and verniers. The vernier is composed of a single aperture, while the anchor point is equivalently formed by the centers of M closely arranged apertures, and M=4 in the embodiment. The geometric center of the vernier is the center of a single aperture, while the geometric center of the anchor point is the joint center of the average of the geometric centers of M closely arranged apertures. Relative to the geometric center of the anchor point, the M closely arranged apertures need to be axisymmetric or centrosymmetric. In this embodiment, they are both axisymmetric and centrosymmetric.

[0101] The shortest distance between the geometric centers of the reference points is d 参考点最短间距 , the shortest distance between the geometric centers of M closely spaced apertures at a single anchor point is d 孔径最短间距 , the shortest distance between the MEMS mask plane and the imaging plane is h. In the embodiment, d 孔径最短间距 =30μm, d 参考点最短间距 =160μm, h=0.015m, satisfying d 参考点最短间距 ≥2×d 孔径最短间距 (the first precondition mentioned above), d 孔径最短间距 ≤0.0045×h (the second preset condition above), and d 孔径最短间距 Not less than 10 μm (the third preset condition mentioned above).

[0102] The reference points are arranged in rows and columns. For each row, the reference points are arranged in a consistent row pattern; for each column, the reference points are arranged in a consistent column pattern. In the embodiment, there are 2 cursors between every two sequential anchor points, whether in the row direction or the column direction, and there are 4 reference points in total, including the 2 anchor points as endpoints, forming 3 spacings as a set of spacing groups. The minimum value d between the geometric centers of the reference points is taken as 参考点最短间距 = 160 μm is the scale reference 1, and the reference point distance is calculated as the corresponding scale, such as Figure 1 As shown, the row mode design in the embodiment is that the spacing arrangement ratio of the sequential reference points between every two sequential anchor points is 1:2:3, 1:3:2 and 3:2:1 from left to right, which are different from each other; the column mode design is that the spacing arrangement ratio of the sequential reference points between every two sequential anchor points is 1:2:3, 2:1:3 and 3:1:2 from top to bottom, which are also different from each other.

[0103] Construct a reference reference table corresponding to the reference point array layout, specifically: the contents recorded in the reference table include the ratio of the spacing between the row mode arrangement layout numbers and the sequential adjacent numbers, and the ratio of the spacing between the column mode arrangement layout numbers and the sequential adjacent numbers; the ratio basis is d 参考点最短间距 , that is, d 参考点最短间距The ratio reference 1 is used as the ratio reference, and the spacings of other reference points are calculated according to the ratio reference. In the embodiment, for the row mode, the reference points of a row are numbered 0, 1, 2, ..., 9 from left to right, and the ratios of numbers 0 to 3 are 1:2:3, the ratios of numbers 3 to 6 are 1:3:2, and the ratios of numbers 6 to 9 are 3:2:1; for the column mode, the reference points of a column are numbered 0, 1, 2, ..., 9 from top to bottom, and the ratios of numbers 0 to 3 are 1:2:3, the ratios of numbers 3 to 6 are 2:1:3, and the ratios of numbers 6 to 9 are 3:1:2.

[0104] Extract the imaging features of the imaging points in the actual measured image, specifically: extract the imaging features of each imaging point in turn, including the centroid coordinates, grayscale value and image point area. Figure 3 As shown, there are 28 imaging points in the embodiment, and the features of these imaging points are actually extracted, and the features of 28 imaging points are extracted in total.

[0105] Establish the relationship between "imaging point-reference point" and calculate the shortest distance H between the actual reference points in the row direction according to the imaging characteristics. 参考点最短间距 The shortest distance V between the reference points in the column direction 参考点最短间距 , respectively as the basis for calculating the proportionality of the imaging point spacing in the row direction and the column direction, respectively calculate the reference point spacing ratio in the row direction and the column direction, then match according to the row mode and column mode in the reference reference table, identify the row mode number and column mode number of the imaging point in the reference reference table, and establish the "imaging point-reference point" association relationship. In the embodiment, in the row direction, the shortest distance between reference points is 40.0 pixels wide, so H 参考点最短间距 =40.0×pixel horizontal side length. In the column direction, the shortest distance between reference points is 38.0 pixel widths, so V 参考点最短间距 =38.0×pixel horizontal side length. When identifying and matching, first identify the anchor points in the image points according to the size of the image point area, with the larger area being the anchor point, and identify a total of 4 anchor points. Then calculate the ratio of the sequential reference point spacing between two sequential anchor points in the row direction and column direction respectively. Combined with Figure 4 As shown, in this embodiment, the ratio of calculating two sequential anchor points in the row direction is equal to 1:3:2, and the ratio of calculating two sequential anchor points in the column direction is equal to 2:1:3. By comparing the reference reference table, the reference point numbers and identities corresponding to these image points can be uniquely determined. Figure 3 The anchor point in the upper left corner of the four anchor points corresponds to the reference point in the 4th row and 4th column on the mask, and the other points can also be numbered one by one.

[0106] According to each pair of associations, the relative orientation information between the corresponding sun vector and the sun sensor is calculated respectively. Specifically, the calculated relative orientation information is a vector information, not a scalar. In the embodiment, 28 relative orientation information vectors are calculated for 28 "imaging point-reference point" associations in turn.

[0107] According to the branch setting, the arithmetic mean or intensity weighted average of multiple relative orientation information is calculated as the final output, specifically: the branch setting parameter is a preset value or a dynamic setting value, and the arithmetic mean or intensity weighted average of multiple relative orientations is calculated according to the different settings of the parameter value, and the way to calculate the vector average is to perform the calculation one by one according to the element position. In the embodiment, the branch setting parameter is "arithmetic mean", so the arithmetic mean calculation is performed on the 28 relative orientation information vectors one by one according to the vector element position, and finally the arithmetic mean relative orientation information vector is obtained as the final output result.

[0108] In this embodiment, a device for determining the position of the sun is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made are omitted. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0109] This embodiment provides a device for determining the sun's position. Figure 5 As shown, it includes: an acquisition module 501, which is used to acquire the imaging characteristics of the imaging point of the sun's rays; a first determination module 502, which is used to determine the target distance between each imaging point based on the imaging characteristics; wherein the target distance is used to characterize the minimum distance between each imaging point; a second determination module 503, which is used to determine the target reference point corresponding to the imaging point from a preset reference benchmark table based on the target distance; and a third determination module 504, which is used to determine the sun's position based on the target reference point and the imaging point.

[0110] In an optional embodiment, the above-mentioned device also includes: a number acquisition module, which is used to acquire the reference points of the mask and the numbers of the reference points; wherein the reference points include: an anchor point and a cursor, the cursor is used to indicate a point of a single aperture, and the anchor point is used to indicate a point of a combination of multiple apertures; a fourth determination module, which is used to determine the aperture center of the anchor point and the aperture center of the cursor respectively; a fifth determination module, which is used to determine the minimum distance between the anchor point and the cursor based on the aperture center of the anchor point and the aperture center of the cursor; a sixth determination module, which is used to determine the ratio between adjacent reference points with the minimum distance between the anchor point and the cursor as the first minimum base; a construction module, which is used to construct a preset reference benchmark table based on the numbers of the reference points and the ratios between adjacent reference points.

[0111] In an optional embodiment, the reference point numbering includes: row reference point numbering and column reference point numbering; wherein the construction module includes: a first determination unit, used to determine a first reference benchmark table corresponding to the reference points arranged in a row based on the row reference point numbering and the ratio between adjacent reference points; a second determination unit, used to determine a second reference benchmark table corresponding to the reference points arranged in a column based on the column reference point numbering and the ratio between adjacent reference points; a construction unit, used to construct a preset reference benchmark table based on the first reference benchmark table and the second reference benchmark table.

[0112] In an optional embodiment, the imaging features include: centroid coordinates; wherein the first determination module 502 includes: a second determination unit, used to determine the distance between each imaging point based on the centroid coordinates of each imaging point; and a third determination unit, used to compare the distances between each imaging point to determine the target distance.

[0113] In an optional embodiment, the imaging feature at least includes: an image point area; wherein the second determination module 503 includes: a fourth determination unit, which is used to determine, based on the image point area, a first imaging point corresponding to an anchor point in the imaging point and a second imaging point corresponding to a cursor; wherein the area of ​​the first imaging point is greater than the area of ​​the second imaging point; a fifth determination unit, which is used to determine the ratio between the imaging points arranged in rows and the ratio between the imaging points arranged in columns with the target distance as the second minimum cardinality; a sixth determination unit, which is used to determine a first target ratio from a preset reference reference table based on the ratio between the first imaging point, the second imaging point and the imaging points arranged in rows; a seventh determination unit, which is used to determine a second target ratio from a preset reference reference table based on the ratio between the first imaging point, the second imaging point and the imaging points arranged in columns; an eighth determination unit, which is used to determine each first reference point arranged in rows based on the first target ratio; a ninth determination unit, which is used to determine each second reference point arranged in columns based on the second target ratio; and a tenth determination unit, which is used to use the first reference point and the second reference point as target reference points.

[0114] In an optional embodiment, the above-mentioned device also includes: a condition acquisition module, which is used to acquire the minimum distance between multiple apertures in the anchor point and the distance between the mask and the imaging plane; a detection module, which is used to detect whether the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, whether the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet the second preset condition, and whether the distance between the mask and the imaging plane meets the third preset condition; a judgment module, which is used to judge that the preset reference benchmark table is qualified if the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet the second preset condition, and the distance between the mask and the imaging plane meets the third preset condition.

[0115] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0116] The solar position determination device in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0117] The embodiment of the present invention also provides a computer device having the above Figure 5 The solar position determination device shown.

[0118] See also Figure 6 , Figure 6 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 6 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 6 A processor 10 is taken as an example.

[0119] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0120] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0121] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0122] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0123] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0124] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0125] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0126] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for determining the solar position, It is characterized in that The method comprises: Obtain imaging features of imaging points of sunlight; Based on the imaging feature, determining the target distance between each imaging point; wherein the target distance is used to characterize the minimum distance between each imaging point; Based on the target distance, determining a target reference point corresponding to the imaging point from a preset reference reference table; Based on the target reference point and the imaging point, the sun position is determined.

2. The method for determining the solar position according to claim 1, It is characterized in that The process of building a preset reference datum table includes: Obtaining reference points and reference point numbers of the mask; wherein the reference points include: anchor points and cursors, the cursors are used to indicate points of a single aperture, and the anchor points are used to indicate points of a combination of multiple apertures; Determining the aperture center of the anchor point and the aperture center of the cursor respectively; Determining a minimum distance between an anchor point and a cursor based on an aperture center of the anchor point and an aperture center of the cursor; Taking the minimum distance between the anchor point and the cursor as the first minimum base, determine the ratio between adjacent reference points; A preset reference datum table is constructed based on the numbers of the reference points and the ratios between adjacent reference points.

3. The method for determining the solar position according to claim 2, It is characterized in that The reference point numbers include: row reference point numbers and column reference point numbers; wherein, based on the reference point numbers and the ratios between adjacent reference points, a preset reference datum table is constructed, including: Determine a first reference datum table corresponding to the reference points arranged in the row based on the row reference point numbers and the ratios between adjacent reference points; Determine a second reference datum table corresponding to the reference points arranged in the column based on the column reference point numbers and the ratios between adjacent reference points; Based on the first reference reference table and the second reference reference table, a preset reference reference table is constructed.

4. The method for determining the solar position according to claim 1, It is characterized in that The imaging feature includes: centroid coordinates; wherein, based on the imaging feature, determining the target distance between each imaging point includes: Determine the distance between each imaging point based on the centroid coordinates of each imaging point; The distances between the various imaging points are compared to determine the target distance.

5. The method for determining the solar position according to claim 2, It is characterized in that The imaging feature at least includes: an image point area; wherein, based on the target distance, determining the target reference point corresponding to the imaging point from a preset reference reference table includes: Based on the image point area, determining a first imaging point corresponding to the anchor point and a second imaging point corresponding to the cursor in the imaging point; wherein the area of ​​the first imaging point is greater than the area of ​​the second imaging point; Taking the target distance as the second minimum base number, determining the ratio between the imaging points arranged in rows and the ratio between the imaging points arranged in columns; Determining a first target ratio from a preset reference reference table based on a ratio between the first imaging point, the second imaging point, and the imaging points arranged in a row; Determining a second target ratio from a preset reference reference table based on a ratio among the first imaging point, the second imaging point, and the imaging point arranged based on the column; Based on the first target ratio, determining each first reference point of the row arrangement; Based on the second target ratio, determining each second reference point of the column arrangement; The first reference point and the second reference point are used as target reference points.

6. The method for determining the solar position according to claim 2, It is characterized in that The method further comprises: Obtaining the minimum distance between multiple apertures in the anchor point, and the distance between the mask and the imaging plane; Detecting whether the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet a first preset condition, whether the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet a second preset condition, and whether the distance between the mask and the imaging plane meets a third preset condition; If the minimum distance between multiple apertures in the anchor point and the minimum distance between the anchor point and the cursor meet the first preset condition, the distance between the mask and the imaging plane and the minimum distance between multiple apertures in the anchor point meet the second preset condition, and the distance between the mask and the imaging plane meets the third preset condition, then the preset reference benchmark table is determined to be qualified.

7. A device for determining the position of the sun, It is characterized in that The device comprises: An acquisition module, used to acquire imaging features of imaging points of sunlight; A first determination module is used to determine a target distance between each imaging point based on the imaging feature; wherein the target distance is used to characterize a minimum distance between each imaging point; A second determination module, configured to determine a target reference point corresponding to the imaging point from a preset reference table based on the target distance; The third determination module is used to determine the sun's position based on the target reference point and the imaging point.

8. A computer device, It is characterized in that include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for determining the sun position according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for determining the sun position according to any one of claims 1 to 6.

10. A computer program product, It is characterized in that The method comprises computer instructions for causing a computer to execute the method for determining the sun position according to any one of claims 1 to 6.

Images