Satellite image positioning method, device and equipment based on spatial observation configuration

Abstract

The application provides a satellite image positioning method based on a space observation configuration, which can be applied to the technical field of satellite image processing. The method comprises the following steps: acquiring multi-scene satellite images of a ground object target; converting image coordinates of each pixel in each satellite image into object coordinates at multiple different elevations to construct a space ray model of the pixel; determining a space observation position of a satellite based on the space ray model corresponding to at least two pixels in the satellite image; constructing a space observation configuration of the ground object target based on multiple space observation positions of the satellite relative to the ground object target; screening a set of effective observation images that meet a preset geometric condition from the multi-scene satellite images based on the space observation configuration; and solving three-dimensional object coordinates of the ground object target based on the space ray model corresponding to the ground object target in the effective observation images. The application also provides a satellite image positioning device based on a space observation configuration, equipment and a storage medium.

Description

Technical Field

[0001] This application relates to the field of satellite image processing technology, and specifically to a satellite image positioning method, apparatus, equipment and medium based on space observation configuration. Background Technology

[0002] With the rapid development of Synthetic Aperture Radar (SAR) and optical remote sensing technologies, the acquisition of high-frequency, multi-angle satellite observation data has become increasingly convenient. However, due to various factors such as satellite platform attitude control errors and the space environment, raw satellite images (especially SAR images) often have large positioning errors, making it difficult to directly meet the requirements of high-precision applications.

[0003] Existing fine calibration techniques mainly fall into two categories: one is based on Ground Control Points (GCPs), which involves manually selecting feature points and matching them with GCPs of known coordinates to calculate calibration parameters. This method heavily relies on control point data and is difficult to implement in uncontrolled areas such as border regions and oceans. The other is a relative calibration method based on reference images, which uses existing high-precision optical images as a reference for registration. Due to the significant differences in imaging mechanisms between different sensors (such as optical and SAR), geometric distortions and radiometric characteristics are inconsistent, resulting in low matching accuracy and limited applicability.

[0004] Furthermore, existing technologies typically employ simple overlay or averaging strategies when processing multiple images covering the same area, neglecting the crucial impact of satellite spatial observation geometry on positioning accuracy. This fails to effectively select the geometrically optimal image combination, limiting further improvements in positioning accuracy. Therefore, there is an urgent need for a high-precision positioning method that does not rely on ground control points and fully utilizes the spatial geometric distribution of multiple images. Summary of the Invention

[0005] In view of the above problems, this application provides a satellite image positioning method, apparatus, equipment and medium based on space observation configuration to improve positioning accuracy.

[0006] According to a first aspect of this application, a satellite image positioning method based on a spatial observation configuration is provided. The method includes: acquiring multiple satellite images of a ground feature; converting the image-side coordinates of each pixel in each satellite image into multiple object-side coordinates at different elevations, and constructing a spatial ray model for each pixel, wherein the spatial ray model represents the spatial line-of-sight relationship between the satellite and the ground feature when the satellite image was captured; determining the spatial observation position of the satellite based on the spatial ray model corresponding to at least two pixels in the satellite image; constructing a spatial observation configuration of the ground feature based on the multiple spatial observation positions of the satellite relative to the ground feature, wherein the spatial observation configuration represents the spatial geometric relationship between the ground feature and the multiple spatial observation positions; selecting a set of effective observation images that meet preset geometric conditions from the multiple satellite images based on the spatial observation configuration; and calculating the three-dimensional object-side coordinates of the ground feature based on the spatial ray model corresponding to the ground feature in the effective observation images.

[0007] According to an embodiment of this application, acquiring multiple satellite images of ground features includes: determining the latitude and longitude range of the target area where the ground features are located; calculating the coordinates of the four corner points of the object side of the candidate satellite images to obtain the latitude and longitude range covered by the candidate satellite images; and using the candidate satellite images whose latitude and longitude range overlaps with the latitude and longitude range of the target area as the acquired satellite images.

[0008] According to an embodiment of this application, the step of converting the image coordinates of each pixel in each satellite image into multiple object coordinates at different elevations and constructing a spatial ray model for the pixel includes: based on the positioning model of the satellite image, calculating the image coordinates of each pixel in the satellite image into object coordinates corresponding to different elevations, wherein the positioning model is a mathematical model representing the mapping relationship between the image coordinates and the object coordinates; fitting the object coordinates at different elevations into a spatial straight line and constructing a spatial ray model representing the spatial straight line.

[0009] According to an embodiment of this application, determining the spatial observation position of the satellite based on the spatial ray models corresponding to at least two pixels in the satellite image includes: selecting a first pixel and a second pixel located on the same scan line in the satellite image, obtaining the spatial ray models corresponding to the first pixel and the second pixel; solving the spatial coordinates of the intersection point of the spatial ray model of the first pixel and the spatial ray model of the second pixel, and using the spatial coordinates of the intersection point as the spatial observation position when the satellite captures the satellite image.

[0010] According to an embodiment of this application, the step of constructing a spatial observation configuration of the ground object based on multiple spatial observation positions of the satellite relative to the ground object includes: obtaining multiple spatial observation positions of the satellite relative to the ground object; projecting each of the satellite spatial observation positions onto the same plane to obtain a convex polygon formed by the projection points; and constructing a spatial observation configuration of the ground object with the ground object as the vertex and the convex polygon as the base.

[0011] According to an embodiment of this application, the preset geometric condition is to maximize the volume of the space observation configuration. The step of selecting a set of valid observation images from the multiple satellite images that satisfy the preset geometric condition based on the space observation configuration includes: randomly selecting three images from the multiple satellite images; calculating the current volume of the space observation configuration based on the satellite's spatial observation position; sequentially adding the spatial observation positions of the satellites corresponding to the remaining satellite images in the multiple satellite images to the space observation configuration, and calculating the new volume of the space observation configuration; if the new volume is greater than the current volume, then selecting the newly added satellite images as valid observation images, updating the space observation configuration and the current volume; and traversing the multiple satellite images to obtain the set of valid observation images.

[0012] According to an embodiment of this application, calculating the three-dimensional object coordinates of the ground target based on the spatial ray model corresponding to the ground target in the effective observation image includes: obtaining the spatial ray model corresponding to the ground target in each effective observation image; solving all the obtained spatial ray models simultaneously to obtain the target coordinate point, wherein the sum of the squared distances from the target coordinate point to the spatial ray models corresponding to all effective observation images is minimized; and using the target coordinate point as the three-dimensional object coordinates of the ground target.

[0013] According to a second aspect of this application, a satellite image positioning device based on a spatial observation configuration is provided. The device includes: an image acquisition module for acquiring multiple satellite images of a ground target; a ray model construction module for converting the image-side coordinates of each pixel in each of the satellite images into object-side coordinates at multiple different elevations, and constructing a spatial ray model of the pixel, wherein the spatial ray model represents the spatial line-of-sight relationship between the satellite and the ground target when the satellite image is captured; an observation position determination module for determining the spatial observation position of the satellite based on the spatial ray model corresponding to at least two pixels in the satellite image; a configuration construction module for constructing a spatial observation configuration of the ground target based on the multiple spatial observation positions of the satellite relative to the ground target, wherein the spatial observation configuration represents the spatial geometric relationship between the ground target and the multiple spatial observation positions; an image filtering module for filtering a set of valid observation images that meet preset geometric conditions from the multiple satellite images based on the spatial observation configuration; and a coordinate calculation module for calculating the three-dimensional object-side coordinates of the ground target based on the spatial ray model corresponding to the ground target in the valid observation images.

[0014] A third aspect of this application provides an electronic device comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method described above.

[0015] A fourth aspect of this application also provides a computer-readable storage medium having a computer program or instructions stored thereon, which, when executed by a processor, implement the steps of the above-described method.

[0016] Compared with existing technologies, this disclosure offers the following advantages: First, it proposes a positioning method that does not rely on ground control points. Positioning accuracy can be evaluated and improved solely by analyzing the "spatial observation configuration" of the satellite imagery itself, completely eliminating dependence on control points and making it suitable for uncontrolled areas such as border regions, oceans, and disaster areas. Second, it establishes for the first time a positive correlation model between satellite image positioning accuracy and spatial observation configuration (pyramidal volume or base area), quantifying geometric distribution characteristics into optimizable indicators. Based on this, a dynamic filtering mechanism based on maximizing the spatial configuration volume is designed, which can automatically eliminate redundant images with low geometric contribution and retain effective observations, thereby significantly improving the reliability of positioning results. Finally, it forms a complete uncontrolled processing flow from data extraction, observation position calculation, configuration construction, optimal filtering to high-precision positioning, achieving fully automated high-precision satellite image positioning. Attached Figure Description

[0017] The above-mentioned contents, other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0018] Figure 1 A flowchart illustrating a satellite imagery positioning method based on a space observation configuration according to an embodiment of this application is shown schematically.

[0019] Figure 2 This illustration schematically shows a satellite Earth observation diagram according to an embodiment of this application;

[0020] Figure 3 This illustration schematically shows a multi-satellite observation diagram of the same ground feature according to an embodiment of this application;

[0021] Figure 4 This schematically illustrates a structural block diagram of a satellite image positioning device based on a space observation configuration according to an embodiment of this application; and

[0022] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing a satellite imagery positioning method based on a space observation configuration, according to an embodiment of this application. Detailed Implementation

[0023] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0024] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0025] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0026] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0027] Figure 1 A flowchart illustrating a satellite imagery positioning method based on a space observation configuration according to an embodiment of this application is shown schematically.

[0028] like Figure 1 As shown, the satellite image positioning method based on space observation configuration in this embodiment includes operations S110 to S160, and the transaction processing method can be executed sequentially.

[0029] The S110 is used to acquire multiple satellite images of ground features.

[0030] Based on the target area, all images covering that area are extracted from the satellite imagery database to form a multi-view satellite imagery dataset.

[0031] In operation S120, the image coordinates of each pixel in each satellite image are converted into object coordinates at multiple different elevations, and a spatial ray model of the pixel is constructed.

[0032] A space ray model represents the spatial line-of-sight relationship between a satellite and a ground target when satellite imagery is captured. For a given pixel in a satellite image, since the accurate elevation of the ground point is unknown, the pixel may correspond to different locations on different elevation planes. Using a satellite positioning model, such as Rational Polynomial Coefficients (RPCs), the image-space coordinates of the same pixel are combined with multiple assumed elevation values ​​to calculate a series of object-space coordinates. These coordinates theoretically lie on the same spatial straight line. Fitting these points to a spatial straight line yields the space ray model of that pixel, which describes the observation direction from the satellite position, through the pixel, and extending to the ground. In practical positioning, this model simplifies the complex nonlinear positioning model into a straight line, facilitating subsequent intersection calculations: given any elevation value, the corresponding planar coordinates can be quickly calculated along the ray, and the intersection of multiple rays (from observations of the same target from different imagery) can calculate the target's three-dimensional coordinates.

[0033] In operation S130, the space observation position of the satellite is determined based on the space ray model corresponding to at least two pixels in the satellite image.

[0034] Each pixel's spatial ray model originates from the satellite projection center (i.e., the camera's optical center), passing through that pixel and pointing towards the ground. Therefore, theoretically, the spatial rays corresponding to any two different pixels in the same image intersect at the same point: the satellite projection center. By simultaneously solving the linear equations of these two spatial ray models and finding the intersection point, the satellite's three-dimensional spatial coordinates at the time of imaging can be obtained. If model errors cause the rays to not intersect, the least squares method can be used to find the approximate intersection point that minimizes the distance between the two rays. This method utilizes the image's own geometric constraints and can recover the satellite's spatial observation position without relying on external control points.

[0035] In operation S140, a spatial observation configuration of the ground target is constructed based on multiple spatial observation positions of the satellite relative to the ground target. The spatial observation configuration represents the spatial geometric relationship between the ground target and multiple spatial observation positions.

[0036] The space observation configuration is a spatial geometry formed by using the coordinates of the satellite projection centers calculated from different satellites or images from different time phases as observation nodes, together with the ground target points. Typically, it is assumed that the satellites are at similar orbital altitudes (i.e., approximately coplanar). These observation positions are projected onto the same plane, and their convex hull polygons are calculated. Then, with the ground target as the vertex and the convex hull polygon as the base, a polygonal pyramid is formed. This pyramid is the space observation configuration, which quantitatively characterizes the distribution range and geometric intensity of satellite observation directions: the larger the base (the more dispersed the satellite distribution), the larger the pyramid volume, indicating better stereo intersection conditions for satellites observing targets from different angles, thus resulting in higher positioning accuracy. This configuration provides an intuitive geometric metric for subsequent selection of the optimal observation subset and evaluation of positioning accuracy.

[0037] When operating the S150, based on the space observation configuration, a set of effective observation images that meet the preset geometric conditions are selected from multiple satellite images.

[0038] The preset geometric condition is usually to maximize the configuration volume (or maximize the area of ​​the convex hull of the base), because a larger volume means a more dispersed distribution of satellite observations and a stronger intersection geometry. By gradually adding satellite observation positions from multiple images, only images that can increase the configuration volume are retained, and redundant observations with low geometric contribution are removed, ultimately obtaining the optimal subset of observations.

[0039] In operation S160, the three-dimensional object coordinates of the ground objects are calculated based on the spatial ray model corresponding to the ground objects in the effective observation images.

[0040] Theoretically, the spatial ray models of all valid observation images should intersect at the same ground point. In practice, a spatial point is solved using the least squares method to minimize the sum of the squared weighted distances to all rays. This point represents the high-precision three-dimensional coordinates of the ground target. This enables reliable positioning based on optimal geometry under uncontrolled conditions.

[0041] To make the objectives, technical solutions, and advantages of this disclosure clearer, the disclosure 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 for illustrative purposes only and are not intended to limit the scope of this disclosure.

[0042] S110 acquires multiple satellite images of ground features, including S111 to S113.

[0043] In operation S111, determine the latitude and longitude range of the target area where the ground features are located.

[0044] In operation S112, the coordinates of the four corner points of the candidate satellite image are calculated to obtain the latitude and longitude range of the candidate satellite image coverage.

[0045] In operation S113, candidate satellite images covering areas where the latitude and longitude range overlaps with the target area are used as acquired satellite images.

[0046] In the embodiments of this application, it is assumed that the latitude and longitude range of the target area for positioning is [missing information]. The database contains Remote sensing images of the landscape.

[0047] For the For remote sensing images, their object space parameters are: Based on this object space parameter information, a specific image space point in the remote sensing image can be calculated. The corresponding object coordinate value :

[0048]

[0049] The four corner points of the remote sensing image Substituting these values ​​into the above equation, we obtain the coordinates of the four corner points of the object. By comparing the coordinates of the four corner points of the object, the coverage area of ​​the remote sensing image can be obtained. :

[0050]

[0051] Compare the latitude and longitude range of the remote sensing image with the latitude and longitude range of the target area to be located. The remote sensing image and the target area are considered to overlap when the following conditions are met:

[0052]

[0053] In operation S120, the image coordinates of each pixel in each satellite image are converted into object coordinates at multiple different elevations, and a spatial ray model of the pixel is constructed, including operations S121~S122.

[0054] In operation S121, based on the positioning model of satellite imagery, the image coordinates of each pixel in the satellite imagery are solved into object coordinates corresponding to different elevations. The positioning model is a mathematical model that represents the mapping relationship between image coordinates and object coordinates.

[0055] In operation S122, the object coordinates at different elevations are fitted to spatial straight lines to construct a spatial ray model representing the spatial straight lines.

[0056] Assume that in the target region image dataset S, the first... If the localization model for the landscape image is the RPC model, then the image-side coordinates in the image... With object coordinates The relationship can be represented by the following equation:

[0057]

[0058] in,

[0059]

[0060] in, These are the coefficients of the RFM model.

[0061] Figure 2 A schematic diagram of satellite Earth observation according to an embodiment of this application is shown.

[0062] like Figure 2 As shown, for a single pixel in the image By setting different elevation Z values, different object coordinates can be obtained.

[0063] For a single pixel in the image By setting different elevation Z values, different object coordinates can be obtained.

[0064] Assume that N elevation surfaces are taken respectively. Based on the above equation, we can obtain the N sets of object coordinates corresponding to this pixel, as shown below:

[0065]

[0066]

[0067] in, These are the coefficients of the current ray.

[0068] The actual values ​​of the above coefficients can be obtained by using the least squares method, so as to construct a space ray model.

[0069] In operation S130, the space observation position of the satellite is determined based on the space ray model corresponding to at least two pixels in the satellite image, including S131~S132.

[0070] In operation S131, select the first pixel and the second pixel located on the same scan line in the satellite image, and obtain the space ray model corresponding to the first pixel and the second pixel.

[0071] In operation S132, the spatial coordinates of the intersection point of the spatial ray model of the first pixel and the spatial ray model of the second pixel are solved, and the spatial coordinates of the intersection point are used as the spatial observation position when the satellite takes satellite images.

[0072] Suppose that in the j-th image, there are two independent pixels located in the same row. Take N elevation surfaces respectively As described in step S2, three sets of object coordinates corresponding to two independent pixels can be obtained, as shown below:

[0073]

[0074] Based on the acquired N sets of object coordinates, in pixels For example, we can construct an equation for the ray originating from the satellite observation position, as shown in the following formula:

[0075]

[0076] in, These are the coefficients of the current ray.

[0077] The actual values ​​of the above coefficients can be obtained by using the least squares method.

[0078] Similarly, we can obtain the pixel The coefficients corresponding to the constructed ray equations .

[0079] Based on the two obtained ray equations, The solution is shown in the following formula:

[0080]

[0081] The satellite's spatial observation position for the j-th image can be obtained using the least squares method. .

[0082] In operation S140, a spatial observation configuration of the ground target is constructed based on multiple spatial observation positions of the satellite relative to the ground target, including S141~S143.

[0083] In operation S141, multiple space observation positions corresponding to the satellite relative to ground targets are obtained.

[0084] In operation S142, the spatial observation positions of each satellite are projected onto the same plane, resulting in a convex polygon formed by the projection points.

[0085] In operation S143, a spatial observation configuration of the ground object is constructed with the ground object as the vertex and the convex polygon as the base.

[0086] Figure 3 The illustration shows a schematic diagram of multi-satellite observation of the same ground feature according to an embodiment of this application.

[0087] like Figure 3 As shown, assuming there are 5 satellite observations (Sat1 to Sat5) for the same ground target T0, the spatial coordinates of these 5 observations can be obtained through steps S1 to S3. .

[0088] By connecting the spatial locations of different satellite observation times and selecting the largest circumscribed polygon, a spatial polyhedron composed of Sat1-Sat2-Sat3-Sat4-Sat5-T0 can be constructed.

[0089] Based on the analysis of the image pairs between satellite orbits and target ground positions, it can be concluded that for satellite images in the same low / medium / high orbit, the altitude difference between different satellite observation positions is much smaller than the altitude difference between each satellite observation position and the observed target. Therefore, it can be considered that when each satellite observes the same ground target from different spatial positions, they are basically located on the same plane, that is:

[0090]

[0091] Therefore, multiple satellite observations of the same ground feature can yield results such as Figure 3 The spatial geometry shown is the spatial observation configuration.

[0092] In operation S150, the preset geometric condition is to maximize the volume of the space observation configuration. Based on the space observation configuration, a set of effective observation images that meet the preset geometric condition are selected from multiple satellite images, including S151 to S154.

[0093] In operation S151, three images are randomly selected from multiple satellite images, and the current volume of the space observation configuration is calculated based on the satellite's space observation position.

[0094] by Figure 3 Taking the spatial configuration shown as an example, calculate the volume of the pyramid under this configuration. As shown in the formula below:

[0095]

[0096] in, The area of ​​the plane where the satellite's space observation location is located. This represents the distance from the ground target to the plane where the satellite space observation location is located.

[0097] for Figure 3 The satellite space observation position relationships shown are such that, since the Z-coordinates of all points are equal, the area is calculated based on their planar coordinates in sequence. Then the area of ​​the plane is

[0098]

[0099] Assuming the satellite imagery positioning accuracy is The correlation model between satellite image positioning accuracy and space observation configuration is as follows:

[0100]

[0101] According to the above correlation model, the positioning accuracy of satellite imagery is directly proportional to its spatial observation configuration.

[0102] As the volume of space observation configurations continues to increase, the positioning accuracy of satellite imagery becomes higher.

[0103] Based on the above analysis, for the same target, the spatial configuration that yields the largest volume of the pyramid obtained by the satellite space observation configuration is the optimal spatial configuration.

[0104] In operation S152, the spatial observation positions of the satellites corresponding to the other satellite images in the multi-view satellite imagery are added to the spatial observation configuration in turn, and the new volume of the spatial observation configuration is calculated.

[0105] Assuming there are N satellite observations (Sat1 to SatN) for the same observation target T0, the volume of the spatial pyramid under these N observation conditions can be obtained as follows:

[0106]

[0107] Since all N observations were at similar orbital altitudes, therefore, when the number of observations is increased, Unchanged; that is, the volume of the spatial pyramid is only related to the area of ​​the planar polygon formed by the satellite's spatial observation position. related.

[0108] Three locations are randomly selected from N observation positions to form an initial planar polygon, the area of ​​which is... for:

[0109]

[0110] The remaining N-3 observations are added to the initial planar polygon in sequence. If the area of ​​the newly obtained planar polygon is larger than that before it was added, then the observation is recorded as a valid observation; otherwise, the observation is recorded as an invalid observation.

[0111] In operation S153, if the new volume is larger than the current volume, the newly added satellite imagery will be selected as a valid observation imagery, and the space observation configuration and the current volume will be updated.

[0112] As effective observations are added, the area of ​​the planar polygon continuously increases. The area of ​​the planar polygon reaches its maximum when the last effective observation is added; at this point, the spatial configuration is optimal, resulting in the highest image positioning accuracy. All effective observations then constitute the selection result for the remote sensing image.

[0113] By operating S154, multiple satellite images are traversed to obtain a set of effective observation images.

[0114] Assuming that M valid observations are selected from N observations, then the corresponding optimal spatial configuration volume is... for

[0115]

[0116] The high-precision positioning result of the remote sensing image at this time is:

[0117]

[0118] In operation S160, based on the spatial ray model corresponding to the ground targets in the effective observation image, the three-dimensional object coordinates of the ground targets are calculated, including S161~S163.

[0119] In operation S161, the spatial ray model corresponding to the ground targets in each valid observation image is obtained.

[0120] Assuming that after the aforementioned screening, a total of M valid observation images are obtained, and the corresponding image points of ground objects in each image have been determined, and the spatial ray model of the image point has been constructed according to the aforementioned method.

[0121] In operation S162, solve all the acquired space ray models simultaneously to obtain the target coordinate point. The sum of the squared distances from the target coordinate point to the corresponding space ray models of all valid observation images is minimized.

[0122] Ideally, the spatial ray models corresponding to the same ground feature in all valid observation images should intersect precisely at the target's true spatial location. However, due to unavoidable factors such as positioning model errors, pixel measurement errors, and satellite attitude errors, the rays often cannot intersect precisely at a single point. In this case, it is necessary to find an optimal estimation point that minimizes the overall geometric deviation between that point and all rays. The perpendicular distance from a point to each ray is defined as the observation residual corresponding to that ray. The sum of the squares of all residuals constitutes a total error function. Solving for the minimum point of this function using the least squares method yields the statistically optimal 3D coordinate solution—this point balances the constraints of all rays, exhibits good robustness to random errors, and is equivalent to maximum likelihood estimation when the errors follow a normal distribution. Therefore, the point with the minimum sum of squared distances is the optimal 3D object space coordinate of the ground feature.

[0123] In operation S163, the target coordinate point is used as the three-dimensional object coordinate of the ground object.

[0124] This application achieves multi-view rendezvous positioning by constructing a space ray model, calculating satellite observation positions, establishing a space observation configuration, and filtering effective observation images based on volume maximization. This method is completely independent of ground control points, utilizing only the geometric distribution characteristics of multiple satellite images to automatically eliminate redundant observations with low geometric contribution, significantly improving positioning accuracy under uncontrolled conditions. The entire process is highly automated and widely applicable, providing an effective solution for high-precision uncontrolled positioning of high-resolution remote sensing imagery.

[0125] Based on the above method, this application also provides a satellite image positioning device based on a space observation configuration. The following will combine... Figure 4 The device is described in detail.

[0126] Figure 4 A schematic diagram of a satellite image positioning device based on a space observation configuration according to an embodiment of this application is shown.

[0127] like Figure 4 As shown, the device 400 in this embodiment includes: an image acquisition module 410, a ray model construction module 420, an observation position determination module 430, a configuration construction module 440, an image filtering module 450, and a coordinate calculation module 460.

[0128] The image acquisition module 410 is used to acquire multiple satellite images of ground features. In one embodiment, the image acquisition module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0129] The ray model construction module 420 is used to convert the image-side coordinates of each pixel in each satellite image into object-side coordinates at multiple different elevations, and construct a spatial ray model for the pixel. The spatial ray model represents the spatial line-of-sight relationship between the satellite and ground targets when the satellite image was captured. In one embodiment, the ray model construction module 420 can be used to perform the operation S220 described above, which will not be repeated here.

[0130] The observation position determination module 430 is used to determine the satellite's spatial observation position based on a spatial ray model corresponding to at least two pixels in the satellite image. In one embodiment, the observation position determination module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0131] The configuration construction module 440 is used to construct a spatial observation configuration of a ground target based on multiple spatial observation positions of the satellite relative to the ground target. The spatial observation configuration represents the spatial geometric relationship between the ground target and the multiple spatial observation positions. In one embodiment, the configuration construction module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0132] The image filtering module 450 is used to filter a set of valid observation images that meet preset geometric conditions from multiple satellite images based on the space observation configuration. In one embodiment, the image filtering module 450 can be used to perform the operation S250 described above, which will not be repeated here.

[0133] The coordinate calculation module 460 is used to calculate the three-dimensional object coordinates of ground targets based on the spatial ray model corresponding to the ground targets in the effective observation image. In one embodiment, the coordinate calculation module 460 can be used to perform the operation S260 described above, which will not be repeated here.

[0134] According to embodiments of this application, any multiple modules among the image acquisition module 410, ray model construction module 420, observation position determination module 430, configuration construction module 440, image screening module 450, and coordinate calculation module 460 can be combined into one module, or any one of these modules can be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules can be combined with at least part of the functionality of other modules and implemented in one module. According to embodiments of this application, at least one of the above six modules can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or any other reasonable means of integrating or packaging circuits, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the above modules can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0135] Figure 5 A block diagram schematically illustrates an electronic device suitable for implementing a satellite imagery positioning method based on a space observation configuration, according to an embodiment of this application.

[0136] like Figure 5 As shown, an electronic device 500 according to an embodiment of this application includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0137] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 502 and / or RAM 503. It should be noted that the programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0138] According to embodiments of this application, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to a bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0139] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0140] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this application, the computer-readable storage medium may include ROM 502 and / or RAM 503 and / or one or more memories other than ROM 502 and RAM 503 described above.

[0141] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code enables the computer system to implement the satellite imagery positioning method based on space observation configuration provided in the embodiments of this application.

[0142] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0143] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0144] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of this application embodiment. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0145] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0146] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0147] Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application.

[0148] The embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Without departing from the scope of this application, those skilled in the art can make various substitutions and modifications, all of which should fall within the scope of this application.

Claims

1. A satellite image positioning method based on space observation configuration, characterized in that, The method includes: Acquire multiple satellite images of ground features; The image coordinates of each pixel in each satellite image are converted into object coordinates at multiple different elevations, and a spatial ray model of the pixel is constructed. The spatial ray model represents the spatial line-of-sight relationship between the satellite and the ground target when the satellite image is captured. The spatial observation position of the satellite is determined based on the spatial ray model corresponding to at least two pixels in the satellite image. Based on multiple spatial observation positions of the satellite relative to the ground target, a spatial observation configuration of the ground target is constructed, wherein the spatial observation configuration represents the spatial geometric relationship between the ground target and the multiple spatial observation positions; Based on the aforementioned space observation configuration, a set of valid observation images that meet preset geometric conditions are selected from the multiple satellite images. Based on the spatial ray model corresponding to the ground target in the effective observation image, the three-dimensional object coordinates of the ground target are calculated.

2. The method according to claim 1, characterized in that, The acquired multi-scene satellite imagery of ground features includes: Determine the latitude and longitude range of the target area where the ground features are located; Calculate the coordinates of the four corner points of the candidate satellite image to obtain the latitude and longitude range of the candidate satellite image coverage; Candidate satellite images covering areas whose latitude and longitude ranges overlap with those of the target area are used as the acquired satellite images.

3. The method according to claim 1, characterized in that, The step of converting the image coordinates of each pixel in each of the satellite images into object coordinates at multiple different elevations, and constructing the spatial ray model of the pixel, includes: Based on the positioning model of the satellite image, the image coordinates of each pixel in the satellite image are calculated into object coordinates corresponding to different elevations. The positioning model is a mathematical model that represents the mapping relationship between the image coordinates and the object coordinates. The object coordinates at different elevations are fitted to spatial straight lines to construct a spatial ray model representing the spatial straight lines.

4. The method according to claim 1, characterized in that, Determining the space observation position of the satellite based on a space ray model corresponding to at least two pixels in the satellite imagery includes: In the satellite image, select the first pixel and the second pixel located on the same scan line, and obtain the space ray model corresponding to the first pixel and the second pixel; Solve for the spatial coordinates of the intersection point of the spatial ray model of the first pixel and the spatial ray model of the second pixel, and use the spatial coordinates of the intersection point as the spatial observation position when the satellite takes the satellite image.

5. The method according to claim 1, characterized in that, The construction of the spatial observation configuration of the ground object based on multiple spatial observation positions of the satellite relative to the ground object includes: Obtain multiple spatial observation positions of the satellite relative to the ground target; Projecting each of the aforementioned spatial observation positions onto the same plane yields a convex polygon formed by the projection points; Using the ground target as the vertex and the convex polygon as the base, a spatial observation configuration of the ground target is constructed.

6. The method according to claim 1, characterized in that, The preset geometric condition is to maximize the volume of the space observation configuration. The step of selecting a set of effective observation images that satisfy the preset geometric condition from the multiple satellite images based on the space observation configuration includes: Three images are randomly selected from the multiple satellite images, and the current volume of the space observation configuration is calculated based on the satellite's space observation position. The spatial observation positions of the satellites corresponding to the remaining satellite images in the multi-view satellite imagery are sequentially added to the spatial observation configuration, and the new volume of the spatial observation configuration is calculated. If the new volume is larger than the current volume, the newly added satellite imagery will be selected as a valid observation imagery, and the space observation configuration and the current volume will be updated. By traversing the multiple satellite images, a set of valid observation images is obtained.

7. The method according to claim 1, characterized in that, Based on the spatial ray model corresponding to the ground features in the effective observation image, the calculation of the three-dimensional object coordinates of the ground features includes: Obtain the spatial ray model corresponding to the ground features in each valid observation image; Solve all the acquired space ray models simultaneously to obtain the target coordinate point, where the sum of the squared distances from the target coordinate point to the space ray models corresponding to all valid observation images is minimized; The target coordinate point is used as the three-dimensional object coordinate of the ground object.

8. A satellite image positioning device based on a space observation configuration, characterized in that, The device includes: The image acquisition module is used to acquire multiple satellite images of ground features; The ray model construction module is used to convert the image coordinates of each pixel in each satellite image into object coordinates at multiple different elevations, and construct a spatial ray model of the pixel. The spatial ray model represents the spatial line-of-sight relationship between the satellite and the ground target when the satellite image was captured. The observation location determination module is used to determine the spatial observation location of the satellite based on the spatial ray model corresponding to at least two pixels in the satellite image. The configuration construction module is used to construct a spatial observation configuration of the ground target based on multiple spatial observation positions of the satellite relative to the ground target, wherein the spatial observation configuration represents the spatial geometric relationship between the ground target and the multiple spatial observation positions; The image filtering module is used to filter a set of valid observation images that meet preset geometric conditions from the multiple satellite images based on the space observation configuration. The coordinate calculation module is used to calculate the three-dimensional object coordinates of the ground target based on the spatial ray model corresponding to the ground target in the effective observation image.

9. An electronic device, comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 7.

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