A method and device for positioning the geographic location of micro-nano satellite remote sensing data

Abstract

The application discloses a kind of micro-nano satellite remote sensing data geographical position positioning method and equipment, it is related to satellite positioning technical field, it aims at solving the technical problem that data loss caused when micro-nano satellite appears failure cannot be solved by prior art.The method comprises: obtaining the image information data of the image to be positioned based on the obtained image to be positioned;Based on the central point longitude value and the central point latitude value, the positioning angle value of the target four-corner point is obtained;Based on the pixel length value and the pixel width value, the relative distance value of the target four-corner point and the center point is obtained;Based on the positioning angle value of the target four-corner point and the relative distance value, the target longitude value of the target four-corner point and the target latitude value of the target four-corner point are obtained;Based on the target longitude value of the target four-corner point and the target latitude value of the target four-corner point, the image to be positioned is positioned.

Description

Technical Field

[0001] This application relates to the field of satellite positioning technology, and in particular to a method and device for geolocation based on micro-nano satellite remote sensing data. Background Technology

[0002] Driven by the development of advanced technologies and the demands of the market, microsatellites and nanosatellites offer advantages such as small size, low power consumption, short development cycles, and the ability to be networked, enabling them to complete many complex space missions at a lower cost. However, as microsatellites and nanosatellites age, their hardware gradually fails, leading to problems such as missing auxiliary data during data transmission. Currently, there is no method for geolocation of microsatellite remote sensing data that can be independently processed at the ground-based processing end to address these issues. Summary of the Invention

[0003] The main objective of this application is to provide a method and device for geolocation of micro-nano satellite remote sensing data, aiming to solve the technical problem that existing technologies cannot address the data loss caused by the failure of micro-nano satellites.

[0004] To address the aforementioned technical problems, this application proposes a method for geolocation based on micro / nano satellite remote sensing data, comprising the following steps: Based on the acquired image to be located, image information data of the image to be located is obtained; wherein, the image information data includes the longitude value of the center point of the image to be located, the latitude value of the center point of the image to be located, the pixel length value of the image to be located, and the pixel width value of the image to be located. Based on the longitude and latitude of the center point, the positioning angle values ​​of the four corner points of the target are obtained; Based on the pixel length value and the pixel width value, the relative distance values ​​between the four corner points of the target and the center point are obtained; Based on the positioning angle values ​​and relative distance values ​​of the four corner points of the target, the target longitude values ​​and target latitude values ​​of the four corner points of the target are obtained; The image to be located is located based on the longitude and latitude values ​​of the four corner points of the target.

[0005] As some optional embodiments of this application, obtaining the positioning angle values ​​of the four corner points of the target based on the longitude value and the latitude value of the center point includes: Based on the longitude and latitude values ​​of the center point, multiple registration points of the image to be located are obtained. Based on each of the registration points, the longitude value and latitude value of each registration corner point are obtained; Based on the longitude and latitude values ​​of each of the four registration points, the positioning angle values ​​of each of the four registration points are obtained. Based on the probability of occurrence of the positioning angle values ​​of each of the registered four corner points, the positioning angle values ​​of the target four corner points are obtained; wherein, the probability of occurrence of the positioning angle values ​​of the target four corner points meets a preset probability threshold.

[0006] As some optional embodiments of this application, obtaining multiple registration points of the image to be located based on the longitude and latitude values ​​of the center point; and obtaining the longitude and latitude values ​​of each registration corner point based on each registration point, includes: Based on the longitude and latitude of the center point, the actual geographical location corresponding to the center point is obtained; Based on the latitude and longitude values ​​of the center point of the image to be located and the actual geographical location corresponding to the center point, a plurality of registration points of the image to be located are selected. Based on each of the registration points, multiple registration and positioning images are obtained; Based on the registered positioning images, the longitude values ​​and latitude values ​​of each of the four registered corner points are obtained.

[0007] As some optional embodiments of this application, obtaining the positioning angle value of each of the registration four corner points based on the longitude value and the latitude value of each of the registration four corner points includes: Based on the longitude values ​​of each of the registration four corner points and the longitude value of the center point, the longitude difference between each of the registration four corner points and the center point is obtained; Based on the latitude values ​​of each of the registration four corner points and the latitude value of the center point, the latitude difference between each of the registration four corner points and the center point is obtained; Based on the longitude difference and the latitude difference, the positioning angle values ​​of the four registration points are obtained.

[0008] As some optional embodiments of this application, the positioning angle values ​​of the four registration corner points satisfy the following relationship: tan α = y / x Wherein, α is the positioning angle value of the four registered corner points, y is the latitude difference between the four registered corner points and the center point, and x is the longitude difference between the four registered corner points and the center point.

[0009] As some optional embodiments of this application, the latitude difference between the registration corner points and the center point satisfies the following relationship: y=y i -y0 Where y is the latitude difference between the four registered corner points and the center point, y iy0 is the latitude value of the four registered corner points, and y0 is the latitude value of the center point; The longitude difference between the registration corner points and the center point satisfies the following relationship: x=x i -x0 Where x is the longitude difference between the registration four corner points and the center point, x i x0 represents the longitude value of the four registered corner points, and x0 represents the longitude value of the center point.

[0010] As some optional embodiments of this application, the relative distances between the target four corner points and the center point satisfy the following relationship: W 2 =(M / 2) 2 +(N / 2) 2 Wherein, W is the relative distance between the four corner points of the target and the center point, M is the pixel length of the image to be located, and N is the pixel width of the image to be located.

[0011] As some optional embodiments of this application, the target latitude values ​​of the target four corner points satisfy the following relationship:

[0012] Wherein, YA is the target latitude value of the four corner points, α is the positioning angle value of the four corner points, W is the relative distance between the four corner points and the center point, γ is the latitude value of the latitude line where the center point is located, and y0 is the latitude value of the center point.

[0013] As some optional embodiments of this application, the target longitude values ​​of the four corner points satisfy the following relationship:

[0014] Wherein, XA is the target longitude value of the four corner points, α is the positioning angle value of the four corner points, W is the relative distance value between the four corner points and the center point, and x0 is the longitude value of the center point.

[0015] To address the shortcomings of existing technologies, this application also proposes an electronic device comprising a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the geographic location positioning method for micro-nano satellite remote sensing data as described above.

[0016] Currently, microsatellites and nanosatellites are prone to hardware failure due to their long service life, resulting in missing downlink data, specifically the latitude and longitude values ​​of the four corner points of the image. The current approach mainly involves reverse engineering the downlink data, but this is technically challenging and requires a long recovery period. Therefore, this application provides a method for geolocation based on micro-nano satellite remote sensing data. Based on the acquired image to be located, other image information data besides the latitude and longitude values ​​of the four corners are obtained, such as the longitude value of the center point of the image, the latitude value of the center point of the image, the pixel length value of the image, and the pixel width value of the image. Then, based on the acquired longitude and latitude values ​​of the center point, the positioning angle values ​​of the four corner points are calculated using mathematical trigonometric functions. Furthermore, based on the pixel length and pixel width values, the relative distance values ​​between the four corner points and the center point are calculated. Using the calculated positioning angle values ​​of the four corner points and the relative distance values ​​between the four corner points and the center point, the target longitude and target latitude values ​​of the four corner points are calculated in reverse. Finally, the obtained target longitude and target latitude values ​​are used as the latitude and longitude values ​​of the four corner points to locate the image to be located. As can be seen, the method described in this application uses existing downlinked images and included image data to calculate the accurate latitude and longitude of the four corner points using mathematical trigonometric function relationships, thereby accurately locating the acquired satellite images to ensure the integrity of the acquired satellite image data. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating the geographic location positioning method for micro-nano satellite remote sensing data described in the embodiments of this application; Figure 2 This is a schematic diagram of the satellite image described in the embodiments of this application; Figure 3 This is a statistical chart of the positioning angle α described in the embodiments of this application; Figure 4 This is a statistical graph of the positioning angle β described in the embodiments of this application; Figure 5 This is a schematic diagram of the functional modules of the geographic location positioning device for micro-nano satellite remote sensing data described in the embodiments of this application. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0019] Optical remote sensing imagery boasts advantages such as wide swath and high resolution, making it a crucial tool for Earth observation. Among these, microsatellites and nanosatellites are widely used due to their small size, low power consumption, short development cycles, and ability to be networked, enabling them to accomplish many complex space missions at a lower cost. However, as satellites age, or due to interference from atmospheric conditions and other practical operating factors, information loss often occurs in the images transmitted from satellites. For example, while microsatellites and nanosatellites are rapidly developed and low-cost, their hardware may fail over time, leading to issues such as missing or invalid auxiliary data in the transmitted data. Auxiliary data refers to the satellite orbital parameters, attitude parameters, sensor operating parameters, latitude and longitude, and other relevant orbital information acquired at the time of imaging when the ground point imagery acquired by the satellite camera is used in a ground system; or information loss may be caused by cloud cover.

[0020] However, currently there is no method for geolocation of micro- and nano-satellite remote sensing data that can be independently completed at the ground processing end to address the aforementioned problems. This directly leads to low utilization of acquired satellite imagery at the ground processing end, resulting in a certain waste of resources.

[0021] Currently, the main solution to the above technical problems is to reverse-recover the downlink data. However, reverse-recovery of downlink data is technically challenging and requires a long recovery period. Therefore, this application provides a method for geolocation based on micro-nano satellite remote sensing data. Based on the acquired image to be located, other image information data besides the latitude and longitude values ​​of the four corners are obtained, such as the longitude value of the center point of the image, the latitude value of the center point of the image, the pixel length value of the image, and the pixel width value of the image. Then, based on the acquired longitude and latitude values ​​of the center point, the positioning angle values ​​of the four corner points are calculated using mathematical trigonometric functions. Furthermore, based on the pixel length and pixel width values, the relative distance values ​​between the four corner points and the center point are calculated. Using the calculated positioning angle values ​​of the four corner points and the relative distance values ​​between the four corner points and the center point, the target longitude and target latitude values ​​of the four corner points are calculated in reverse. Finally, the obtained target longitude and target latitude values ​​are used as the latitude and longitude values ​​of the four corner points to locate the image to be located. As can be seen, the method described in this application uses existing downlinked images and included image data to calculate the accurate latitude and longitude of the four corner points using mathematical trigonometric function relationships, thereby accurately locating the acquired satellite images to ensure the integrity of the acquired satellite image data.

[0022] The method in this embodiment can be implemented as a program, based on an existing computer device. The computer device can be a mobile phone, tablet, desktop computer, etc. The computer device can include a processor, storage medium, etc. The storage medium is used to store the program for executing the method of this embodiment, and the processor is used to run the program to execute the method of this embodiment.

[0023] See attached document Figure 1 Based on the hardware device described in the foregoing embodiments, embodiments of this application provide a method for geolocation of micro-nano satellite remote sensing data, comprising the following steps: Step S10: Based on the acquired image to be located, obtain image information data of the image to be located; wherein, the image information data includes the longitude value of the center point of the image to be located, the latitude value of the center point of the image to be located, the pixel length value of the image to be located, and the pixel width value of the image to be located.

[0024] It should be noted that the latitude and longitude information of the image's center point is a crucial component of satellite imagery transmitted via satellite. This is because, given the lack of latitude and longitude information for the four corner points, obtaining the actual ground location using the center point's latitude and longitude is one of the few usable methods. Therefore, the method described in this application targets satellite imagery that includes both the center point's longitude and latitude values, ensuring accurate positioning even if the satellite image lacks the latitude and longitude information for the four corner points.

[0025] It should be noted that the pixel length and pixel width values ​​of the image to be located are dimensionless when there is no constraint from the latitude and longitude information of the four corner points. However, through the inventors' research, it has been discovered that the pixel length and pixel width values ​​of the image to be located, which are in a dimensionless state, can be calculated by combining them with the center latitude and longitude coordinates, so that the pixel length and pixel width values ​​of the image to be located can be applied to actual ground measurements instead of being simply units of length. Therefore, in practical applications, after acquiring the image to be located, the pixel length and pixel width values ​​of the image to be located can be obtained through machine measurement or manual measurement for subsequent use.

[0026] Step S20: Based on the longitude and latitude values ​​of the center point, obtain the positioning angle values ​​of the four corner points of the target.

[0027] It should be noted that the failure of auxiliary data in satellite imagery may be due to atmospheric or cloud cover obstruction, or it may be due to satellite hardware malfunction. Therefore, different calculation processes can be used to locate the satellite imagery for different reasons. Of course, different calculation processes may result in different positioning accuracy. For example, when using image information to perform inversion on the condition parameters at the time of capture, or to obtain Earth information and accurately identify ground features, it is necessary to use images that accurately reflect the radiation of sunlight, which requires atmospheric correction. As mentioned above, atmospheric correction includes absolute atmospheric correction methods and relative atmospheric correction methods. The former, in general, is a method of converting the DN (Digital Number) values ​​of remote sensing images into surface reflectance, surface radiance, surface temperature, etc.; the latter, in general, is the corrected image, where the same DN (Digital Number) value represents the same reflectance of ground features, and the result does not consider the actual reflectance of ground features. Both the above inversion and atmospheric correction require statistical models.

[0028] The method described in this application determines different search ranges based on the known latitude and longitude of the center point of the satellite image, according to different scaling ratios or rotation angles. Within different search ranges, registration points are selected based on objects or scenes in the image to obtain different registered images. Based on probability, the registered image with the highest or relatively high registration rate is selected, and its four corner points are used as target four corner points to obtain their corresponding latitude and longitude for positioning the satellite image.

[0029] In specific embodiments, the scaling ratio or rotation angle and the selection of registration points can be set in any order according to actual needs. For example, the scaling ratio can be set to 1:100 or 1:1000 first, then the search range can be determined, and registration points can be selected within the search range. Alternatively, a more significant registration point can be selected first. For example, if a point (point A) in a satellite image other than the center point is the Guangzhou Tower, then based on the actual geographical locations of the Guangzhou Tower and the center point, and the distance between the center point and point A on the image, the latitude and longitude of the four corner points corresponding to the image can be roughly determined. Alternatively, the rotation angle can be set first, then the search range can be determined, and then registration points can be selected within the search range. Again, a more significant registration point can be selected first. For example, if a point (point A) in a satellite image other than the center point is the Guangzhou Tower, then based on the actual geographical locations of the Guangzhou Tower and the center point, the positioning angle deviation value can be determined, and then based on the positioning angle deviation value, the latitude and longitude of the four corner points corresponding to the image can be determined.

[0030] However, in most cases, the satellite imagery lacks significant geographical landmarks. Therefore, in practical applications, the actual geographical location of the satellite image's center point can be determined based on the center point's latitude and longitude values. However, since the latitude and longitude information of the four corner points is not yet available, the image pixel length or width values ​​remain dimensionless. Therefore, different search ranges can be set based on the image pixel length and width values ​​and their multiples. Then, based on the objects or scenes captured in the image, similar objects or scenes can be searched within different search ranges to serve as registration points. Different registered images are generated based on different search ranges and different registration points. In some specific embodiments, to ensure the registration rate, multiple registration points should be selected. For example, each registered image should contain at least one registration point in addition to the center point. Registration points can be selected using ArcGIS, a commonly used processing software in remote sensing and geographic information systems, or through visual interpretation. Whether selecting registration points using ArcGIS, a common processing software in remote sensing and geospatial information fields, or through visual interpretation, image processing, such as binarization, can be performed on the satellite image before selection to improve selection efficiency and enhance the recognition of objects in the image.

[0031] In other embodiments, in order to improve the registration rate, this application does not use the latitude and longitude values ​​of the four corner points obtained after registration as the latitude and longitude values ​​of the target four corner points. Instead, it first calculates the positioning angle values ​​of each registered four corner point based on the latitude and longitude values ​​of the registered four corner points obtained after registration, and then selects the positioning angle value with the highest or relatively high probability of occurrence (i.e., a threshold for the probability of occurrence is preset, which can be set according to actual needs) as the positioning angle value of the target four corner points. Then, it uses the positioning angle value of the target four corner points to reverse calculate the latitude and longitude values ​​of the target four corner points, so as to reduce the error between the obtained latitude and longitude values ​​of the target four corner points and the latitude and longitude values ​​of the four corner points in the satellite image.

[0032] Specifically, obtaining the positioning angle values ​​of the four corner points of the target based on the longitude and latitude values ​​of the center point includes: Step S21: Based on the longitude and latitude values ​​of the center point, obtain multiple registration points of the image to be located; based on each registration point, obtain the longitude and latitude values ​​of each registration corner point.

[0033] In practical applications, the approximate location of the image on the ground can be determined by the longitude and latitude values ​​of the center point, i.e., the actual geographical location corresponding to the center point. After accurately locating the actual geographical location corresponding to the center point, image georegistration can be performed using ArcGIS, a commonly used processing software in remote sensing and GIS fields; or, unique features can be selected as registration points through visual interpretation to perform georegistration. During georegistration, multiple evenly distributed registration points can be selected from the entire image. Multiple registration schemes can be selected to choose the one with the highest fit during subsequent processing; each registration scheme should include at least one registration point to ensure that the image overlaps with the actual geographical location. That is: In practical applications, step S21, which involves obtaining multiple registration points of the image to be located based on the longitude and latitude values ​​of the center point, and obtaining the longitude and latitude values ​​of each registration corner point based on each registration point, includes: Based on the longitude and latitude values ​​of the center point, the actual geographical location corresponding to the center point is obtained; based on the longitude and latitude values ​​of the center point of the image to be positioned and the actual geographical location corresponding to the center point, multiple registration points of the image to be positioned are selected; based on each registration point, multiple registered positioning images are obtained; based on each registered positioning image, the longitude and latitude values ​​of each registration corner point are obtained.

[0034] It should be noted that multiple registration schemes can yield multiple corresponding registered images. Then, based on these multiple registered images, the latitude and longitude values ​​of the four corner points in each registered image are obtained. The latitude and longitude values ​​of the four corner points from multiple registration schemes are then filtered. Specifically, geographic registration tools such as GIS software are used to perform first-order polynomial overlay registration of corresponding points and features between microsatellite data and the base map data. Through a large amount of overlay registration data, the angles between the lines connecting the four corner points and the center point of the registered image and the horizontal axis at the image center point are calculated. All angle samples are then statistically analyzed, and the value with the highest probability is used as the angle for locating the latitude and longitude of the four corner points. That is: Step S22: Based on the longitude and latitude values ​​of each of the four registration points, obtain the positioning angle values ​​of each of the four registration points.

[0035] It should be noted that the positioning angle value refers to the angle between the line connecting the four corner points and the center point of the registered image and the horizontal axis at the center point of the image.

[0036] Specifically, step S22, which involves obtaining the positioning angle values ​​of each of the registered four corner points based on their longitude and latitude values, includes: Step S221: Based on the longitude values ​​of each of the registration four corner points and the longitude value of the center point, obtain the longitude difference between each of the registration four corner points and the center point. That is, the longitude difference between the registration four corner points and the center point satisfies the following relationship: x=x i -x0 Where x is the longitude difference between the registration four corner points and the center point, x i x0 represents the longitude value of the four registered corner points, and x0 represents the longitude value of the center point.

[0037] Step S222: Based on the latitude values ​​of each of the registration four corner points and the latitude value of the center point, obtain the latitude difference between each of the registration four corner points and the center point. That is, the latitude difference between the registration four corner points and the center point satisfies the following relationship: y=y i -y0 Where y is the latitude difference between the four registered corner points and the center point, y i y0 is the latitude value of the four registered corner points, and y0 is the latitude value of the center point.

[0038] Step S223: Based on the longitude differences and latitude differences, obtain the positioning angle values ​​of each of the four registration points. That is, the positioning angle values ​​of the four registration points satisfy the following relationship: tan α = y / x Wherein, α is the positioning angle value of the four registered corner points, y is the latitude difference between the four registered corner points and the center point, and x is the longitude difference between the four registered corner points and the center point.

[0039] Step S23: Based on the occurrence probability of the positioning angle values ​​of each of the registered four corner points, obtain the positioning angle values ​​of the target four corner points; wherein, the occurrence probability of the positioning angle values ​​of the target four corner points meets a preset probability threshold.

[0040] In practical applications, as mentioned above, due to the existence of multiple registration schemes and corresponding multiple registration images, the positioning angle values ​​of the four corner points in each registration image will inevitably be different. Therefore, it is necessary to select the scheme with the highest or relatively high registration rate from the multiple registration schemes as the target scheme, and then obtain the target image to obtain the target four corner points. Generally, when only one set of target four corner points needs to be determined, the registration four corner point with the highest probability of occurrence of the positioning angle value can be directly selected as the target four corner point. However, there is also a situation where several sets of target four corner points need to be determined simultaneously and then further filtered later. In this case, the registration four corner points with the highest probability of occurrence of the positioning angle value can be selected as different target four corner points. Therefore, in practical applications, the preset probability threshold can be set as the occurrence probability value, such as the registration four corner points with an occurrence probability exceeding 30% or 35% can be used as target four corner points; the preset probability threshold can also be set as the ranking value of the occurrence probability, such as selecting the registration four corner points with the first, second, or third highest probability of occurrence as target four corner points.

[0041] For example, if a registered image includes a center point H, a top-left corner point A, a top-right corner point B, a bottom-right corner point C, and a bottom-left corner point D, and a latitude and longitude coordinate system is established for this image, then the latitude and longitude of these five coordinate points are also known in the registered image; that is, the latitude and longitude coordinates of the center point H are... (x0, y0) The latitude and longitude coordinates of the top left corner point A are: (Xa, Ya) The latitude and longitude coordinates of point B in the upper right corner are: (Xb, Yb) The latitude and longitude coordinates of point C in the lower right corner are: (Xc, Yc) The latitude and longitude coordinates of the lower left corner point D are: (Xd, Yd) Given the above conditions, the angle between the lines connecting points A, B, C, and D to the center point and the horizontal line of the center point can be calculated using the above formula; this is the positioning angle value. The angle between the line connecting point A to the center point and the horizontal line of the center point: ; The angle between the line connecting point B to the center point and the horizontal line of the center point: ; The calculation method for points C and D is the same as that for points A and B. After calculation, the positioning angles of points C and D are almost the same as those of points A and B. Therefore, the calculation will not be repeated here, and the positioning angles of points A and B will be used directly.

[0042] Assuming there are multiple simulated registration images as described above, then there will also be multiple sets of α and β values. Therefore, it is necessary to statistically analyze the obtained α and β values ​​and select the α and β values ​​with the highest probability of occurrence as the positioning angle values ​​of the four corner points of the target.

[0043] Step S30: Based on the pixel length value and the pixel width value, obtain the relative distance values ​​between the four corner points of the target and the center point.

[0044] In practical applications, the relative distances between the four corner points of the target and the center point satisfy the following relationship: W 2 =(M / 2) 2 +(N / 2) 2 Wherein, W is the relative distance between the four corner points of the target and the center point, M is the pixel length of the image to be located, and N is the pixel width of the image to be located.

[0045] It should be noted that the relative distances between the four target corner points and the center point are the same, therefore W is the relative distance between any one of the target corner points and the center point.

[0046] like Figure 2 As shown, this is a schematic diagram of a satellite image. The center point H has the following latitude and longitude coordinates: (x0, y0) The latitude and longitude coordinates of the top left corner point A are: (Xa, Ya) The latitude and longitude coordinates of point B in the upper right corner are: (Xb, Yb) The latitude and longitude coordinates of point C in the lower right corner are: (Xc, Yc) The latitude and longitude coordinates of the lower left corner point D are: (Xd, Yd) The pixel length of the image to be located is M, and the pixel width of the image to be located is N. The positioning angle values ​​of the four corner points of the target and the relative distance values ​​between the four corner points and the center point are calculated through the above steps S20 and S30.

[0047] Assume that during the calculation process in step S20, the α and β values ​​in multiple registration schemes are obtained, such as... Figure 3 and Figure 4 As shown, then from Figure 3 and Figure 4 As can be seen, the α and β values ​​with the highest probability of occurrence are 34° and 54°, respectively. Therefore, the target positioning angle of point A is 34° and the target positioning angle of point B is 54°.

[0048] Step S40: Based on the positioning angle values ​​of the four corner points of the target and the relative distance values, obtain the target longitude values ​​and target latitude values ​​of the four corner points of the target; based on the target longitude values ​​and target latitude values ​​of the four corner points of the target, locate the image to be located.

[0049] Specifically, the target latitude values ​​of the four corner points satisfy the following relationship:

[0050] Wherein, YA is the target latitude value of the four corner points, α is the positioning angle value of the four corner points, W is the relative distance between the four corner points and the center point, γ is the latitude value of the latitude line where the center point is located, and y0 is the latitude value of the center point.

[0051] The longitude values ​​of the four corner points of the target satisfy the following relationship:

[0052] Wherein, XA is the target longitude value of the four corner points, α is the positioning angle value of the four corner points, W is the relative distance value between the four corner points and the center point, and x0 is the longitude value of the center point.

[0053] In practical applications, the following are known: the positioning angle values ​​of the four corner points of the target (i.e., α and β values), and the latitude and longitude coordinates of the center point H of the image (i.e., ... (x0, y0) The relative distance W between the four corner points of the target and the center point; and since 1 degree is 111 km on the Earth's meridian and 111 on the Earth's parallel (γ is the latitude of that parallel). Given the above parameters, taking points A and B as examples: Target latitude value YA at point A: ； Longitude value XA of point A: ； Target latitude value YB at point B: ； Target longitude value XB at point B: 。

[0054] The above method can be used to obtain the latitude and longitude values ​​of the four corner points after inversion. Based on the longitude and latitude values ​​of the four corner points, the image to be located can be positioned to ensure the integrity of the acquired satellite image data.

[0055] The above calculation process can be completed through a positioning template configuration. This involves using a positioning auxiliary file from commonly used optical remote sensing satellite data as a prototype, and retaining basic information labels such as latitude and longitude tags and reference coordinate systems required for micro- and nano-satellite positioning. This information is then stored to be recognizable by relevant geographic information software. The stored information is based on the coordinate system series labels under the metadata tag, and the starting and target labels of the spatial reference. These labels represent the most fundamental information in the positioning system. By inputting the image's coordinate system under the metadata tag, and the row and column values ​​of the four corner points of the image, along with their corresponding latitude and longitude values, under the spatial reference tag, the image can be recognized by relevant geographic information software. This serves as the basic positioning template for micro- and nano-satellite data in this emergency response plan.

[0056] It can be seen that the method described in this application has wide applicability; that is, as long as the transmitted image contains the center point latitude and longitude values, the method described in this application can be used to locate satellite images. Therefore, in practical applications, this application has also developed a corresponding positioning configuration program, namely: a batch program written using IDL language. Its principle is to automatically calculate the latitude and longitude coordinates of the four corner points of each image based on the provided center latitude and longitude information, and write the calculated latitude and longitude coordinates of the four corner points into the corresponding labels of the positioning configuration template for software recognition. The program flow is as follows: input the center latitude and longitude values ​​of the image to be located into a text file; match the latitude and longitude information of the four corner points with the data name number of the registration scheme; copy one positioning template file each time using a loop; record the calculated four corner point information under the start and target labels; and then filter the above-mentioned four corner point data according to the logic described in this application to obtain the final target latitude and longitude values ​​of the target four corner points. This method enables the data to obtain geographical location through auxiliary positioning file information. Based on the acquired satellite imagery, the program can automatically output the calculated latitude and longitude values ​​of the four corner points according to the logic of the method described in this application, so as to use the method described in this application in batches and improve the processing efficiency of satellite imagery data.

[0057] It should be noted that the geographic information configuration template mentioned above refers to the fact that the calculated results can be applied through a self-modified geographic correction file. This geographic correction file is modified from an XML file that uses other satellites to assist geographic information software in identification by including image encoding bits, image coordinate information, and geographic latitude and longitude labels. Only metadata (basic information labels and frameworks such as geographic reference labels and geographic latitude and longitude labels) is retained to form a self-modified new geographic information configuration template.

[0058] Reference Figure 5 Based on the same inventive concept as in the foregoing embodiments, this application also provides a geographic location positioning device for micro-nano satellite remote sensing data, comprising: The acquisition module is used to obtain image information data of the image to be located based on the acquired image to be located; wherein the image information data includes the longitude value of the center point of the image to be located, the latitude value of the center point of the image to be located, the pixel length value of the image to be located, and the pixel width value of the image to be located. The first calculation module is used to obtain the positioning angle values ​​of the four corner points of the target based on the longitude value and the latitude value of the center point; The second calculation module is used to obtain the relative distance values ​​between the four corner points of the target and the center point based on the pixel length value and the pixel width value; The third calculation module is used to obtain the target longitude value and the target latitude value of the target four corner points based on the positioning angle value and the relative distance value of the target four corner points; The positioning module is used to locate the image to be positioned based on the target longitude values ​​and target latitude values ​​of the four corner points of the target.

[0059] Those skilled in the art should understand that the division of the various modules in the embodiments is merely a logical functional division. In actual applications, they can be fully or partially integrated into one or more actual carriers. These modules can be implemented entirely in software through processing unit calls, entirely in hardware, or a combination of software and hardware. It should be noted that each module in the satellite image positioning device in this embodiment corresponds one-to-one with each step in the geographic location positioning method for micro-nano satellite remote sensing data in the aforementioned embodiments. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned geographic location positioning method for micro-nano satellite remote sensing data, which will not be repeated here.

[0060] Based on the same inventive concept as in the foregoing embodiments, embodiments of this application also provide a computer-readable storage medium storing a computer program. When the computer program is loaded and executed by a processor, it implements the geographic location positioning method for micro-nano satellite remote sensing data as provided in the embodiments of this application.

[0061] Furthermore, based on the same inventive concept as in the foregoing embodiments, embodiments of this application also provide an electronic device, comprising at least a processor and a memory, wherein, Memory is used to store computer programs; The processor is used to load and execute computer programs to enable electronic devices to perform geolocation methods based on micro-nano satellite remote sensing data, as provided in the embodiments of this application.

[0062] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a device including one or any combination of the above-mentioned memories. The computer may be a variety of computing devices, including smart terminals and servers.

[0063] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0064] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0065] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0066] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0067] The order of the embodiments described above is merely for illustrative purposes and does not represent the superiority or inferiority of the embodiments.

[0068] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a multimedia terminal device (which may be a mobile phone, computer, television receiver, or network device, etc.) to execute the methods of the various embodiments of this application.

[0069] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for geolocation based on micro / nano satellite remote sensing data, characterized in that, Includes the following steps: Based on the acquired image to be located, image information data of the image to be located is obtained; wherein, the image information data includes the longitude value of the center point of the image to be located, the latitude value of the center point of the image to be located, the pixel length value of the image to be located, and the pixel width value of the image to be located. Based on the longitude and latitude values ​​of the center point, the actual geographical location corresponding to the center point is obtained; based on the longitude and latitude values ​​of the center point of the image to be positioned and the actual geographical location corresponding to the center point, multiple registration points of the image to be positioned are selected; based on each registration point, multiple registered positioning images are obtained; based on each registered positioning image, the longitude and latitude values ​​of each registration four-corner point are obtained; based on the longitude values ​​of each registration four-corner point and the longitude value of the center point, the longitude difference between each registration four-corner point and the center point is obtained; based on the latitude values ​​of each registration four-corner point and the latitude value of the center point, the latitude difference between each registration four-corner point and the center point is obtained; based on the longitude difference and the latitude difference, the positioning angle value of each registration four-corner point is obtained; based on the occurrence probability of the positioning angle value of each registration four-corner point, the positioning angle value of the target four-corner point is obtained; wherein, the occurrence probability of the positioning angle value of the target four-corner point meets a preset probability threshold; Based on the pixel length value and the pixel width value, the relative distance values ​​between the four corner points of the target and the center point are obtained; Based on the positioning angle values ​​and relative distance values ​​of the four corner points of the target, the target longitude values ​​and target latitude values ​​of the four corner points of the target are obtained; The image to be located is located based on the longitude and latitude values ​​of the four corner points of the target.

2. The geographic location positioning method for micro / nano satellite remote sensing data according to claim 1, characterized in that, The positioning angle values ​​of the four registration corner points satisfy the following relationship: tan α = y / x Wherein, α is the positioning angle value of the four registered corner points, y is the latitude difference between the four registered corner points and the center point, and x is the longitude difference between the four registered corner points and the center point.

3. The geographic location positioning method for micro / nano satellite remote sensing data according to claim 2, characterized in that, The latitude difference between the registration corner points and the center point satisfies the following relationship: y=y i -y0 Where y is the latitude difference between the four registered corner points and the center point, y i y0 is the latitude value of the four registered corner points, and y0 is the latitude value of the center point; The longitude difference between the registration corner points and the center point satisfies the following relationship: x=x i -x0 Where x is the longitude difference between the registration four corner points and the center point, x i x0 represents the longitude value of the four registered corner points, and x0 represents the longitude value of the center point.

4. The geographic location positioning method for micro / nano satellite remote sensing data according to claim 1, characterized in that, The target latitude values ​​of the four corner points satisfy the following relationship: Wherein, YA is the target latitude value of the four corner points, θ is the positioning angle value of the four corner points, W is the relative distance between the four corner points and the center point, γ is the latitude value of the latitude line where the center point is located, and y0 is the latitude value of the center point.

5. The geographic location positioning method for micro / nano satellite remote sensing data according to claim 1, characterized in that, The longitude values ​​of the four corner points of the target satisfy the following relationship: Wherein, XA is the target longitude value of the four corner points, θ is the positioning angle value of the four corner points, W is the relative distance value between the four corner points and the center point, and x0 is the longitude value of the center point.

6. An electronic device, characterized in that, The electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the geographic location positioning method for micro-nano satellite remote sensing data as described in any one of claims 1-5.

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