Ground elevation model generation method based on satellites with different orbits

Description

A method for generating ground elevation models based on heterogeneous satellites Technical Field

[0001] This invention relates to the field of elevation model technology, specifically to a method for generating ground elevation models based on satellites with different orbits. Background Technology

[0002] A Digital Elevation Model (DEM) is a digital simulation of ground topography (i.e., a digital representation of the surface morphology of the terrain) achieved through limited terrain elevation data. It is a physical ground model that represents ground elevation using an ordered array of numerical values. It is a branch of Digital Terrain Model (DTM), from which various other terrain feature values ​​can be derived.

[0003] Currently, existing elevation models often acquire elevation values ​​for multiple observation points within an observation area using a single stereo mapping satellite. However, the acquisition of stereo images from stereo mapping satellites has stringent technical requirements regarding weather and satellite tilt, often resulting in highly unstable acquisition cycles due to weather and other factors. These cycles can last from one month to several months, and the uncertainty of the project schedule is fatal to engineering projects. This is a major reason why the application of satellite imagery stereo mapping in the engineering field is limited.

[0004] To provide rapid and low-cost topographic maps and other ancillary surveying and mapping geographic information products for emergency disaster relief, engineering projects, and other fields, a ground elevation model generation method based on heterogeneous satellites is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a method for generating ground elevation models based on heterogeneous satellites, thereby solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for generating a ground elevation model based on a heterodox satellite, comprising the following steps:

[0007] Data collection specifically includes:

[0008] The straight-line distances d1 and d2 from the two satellites Sa1 and Sa2 to the ground observation point Pi, as well as the orbital altitudes h1 and h2 of the satellites Sa1 and Sa2, are obtained from their orbital parameters.

[0009] The resolution P of remote sensing images is obtained from the remote sensing image acquisition module of a different orbital satellite. c and radar echo intensity R a ;

[0010] The latitude and longitude of multiple observation points Pi within the observation area, as well as the atmospheric refractive index A of the city, were obtained from data released by the meteorological bureaus of the cities in the observation area. t ;

[0011] Data preprocessing involves transmitting the collected data to the data processing and computing module for decoding and preprocessing to obtain the parameters that will be used in the calculations of the important data processing and computing modules.

[0012] The basic elevation value H1 and the corrected elevation value H2 of multiple observation points Pi are calculated using the basic elevation value algorithm unit and the corrected elevation value algorithm unit in the data processing calculation module.

[0013] The calculated basic elevation value H1 and correction elevation value of observation point Pi are substituted into the final elevation value algorithm unit in the data processing calculation module to calculate the final elevation value H of multiple observation points Pi. f ;

[0014] To optimize resource allocation, the data processing and calculation module records observation points Pi whose corrected elevation H2 is lower than 0.2 times the average value during the calculation process, and prioritizes the collection of satellite data from the remaining observation points Pi in that area.

[0015] Model generation, based on the final elevation values ​​H of different observation areas. f Depending on the characteristics of the data, an appropriate modeling method is selected. Using geographic information system software, a ground elevation model is established based on the final elevation values ​​of all observation points Pi within the observation area and the selected modeling method, thus completing the generation of the ground elevation model for the observation area.

[0016] Optionally, the ground elevation model generation method employs a data collection module, a data processing and calculation module, and a model generation module.

[0017] Optionally, the equipment used in the data collection module includes heterogeneous satellites Sa1 and Sa2, as well as satellite remote sensing equipment;

[0018] The equipment used in the model generation module includes Geographic Information System (GIS) software.

[0019] Optionally, the data processing and calculation module includes a basic elevation value algorithm unit, a corrected elevation value algorithm unit, and a final elevation value algorithm unit.

[0020] Optionally, the basic elevation value algorithm unit is as follows:

[0021] in:

[0022] H1 represents the basic elevation value;

[0023] d1 and d2 represent the hetero-orbiting satellite Sa1 and the straight-line distance from the hetero-orbiting satellite Sa1 to the ground observation point Pi, respectively;

[0024] h1 and h2 represent the orbital altitudes of the heterogeneous satellites Sa1 and Sa2, respectively.

[0025] θ1 and θ2 represent the observation angles of the different orbital satellites Sa1 and Sa2 to the ground observation point Pi, respectively, and are the angles between the satellite's line of sight and the normal to the Earth's surface.

[0026] Optionally, the elevation correction algorithm unit is as follows:

[0027] in:

[0028] H2 represents the corrected elevation value;

[0029] h1 represents the base elevation value;

[0030] R represents the Earth's radius;

[0031] α1 and α2 represent the orbital inclinations of the heterodox satellites Sa1 and Sa2, respectively.

[0032] Optionally, the final elevation value algorithm unit is as follows:

[0033] in:

[0034] H f Represents the final elevation value of observation point Pi;

[0035] H1 represents the basic elevation value of observation point Pi;

[0036] H2 represents the calibration elevation value of observation point Pi;

[0037] β represents the satellite data acquisition error rate.

[0038] Optionally, the formula for calculating the satellite data acquisition error rate β is as follows:

[0039] in:

[0040] P c Represents pixel resolution;

[0041] R a Represents radar echo intensity;

[0042] A t It represents atmospheric refractive index.

[0043] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0044] I. In this invention, two satellites Sa1 and Sa2 with approximately parallel orbital planes are selected instead of a single stereo mapping satellite to acquire observation point data. This allows observation point Pi on the ground to be observed from two different angles. Cross-observation can provide two independent distance and angle information, and the three-dimensional position of point Pi can be determined through geometric calculation.

[0045] Secondly, by obtaining the three-dimensional position and elevation value of observation point Pi through cross-observation and geometric calculation, compared with traditional single stereo mapping satellites, when extreme weather occurs over the city in the observation area that has a significant impact on satellite remote sensing data, it can bypass the observation area where extreme weather in the sky has a significant impact on the acquisition of satellite remote sensing data images. The three-dimensional position and elevation value of observation point Pi can be obtained during extreme weather, so as to avoid the time of elevation model generation in the observation area or project due to extreme weather. This enables the rapid generation of the required elevation model in emergency disaster relief or time-sensitive engineering projects.

[0046] II. This invention, through the cooperation of three sets of algorithm units, constitutes the core architecture of a ground elevation model generation method based on heterodox satellites. It comprehensively considers factors such as the satellite's observation angle, orbital inclination, the clarity of the satellite's remote sensing images, radar echo intensity, and atmospheric refractive index to calculate the final elevation value H of multiple observation points Pi. f This allows for more accurate elevation data, providing scientific and reliable data support for subsequent ground elevation modeling in Geographic Information System (GIS) software. Attached Figure Description

[0047] Figure 1 is a flowchart of a method for generating a ground elevation model based on a satellite with different orbits;

[0048] Figure 2 is a schematic diagram of the overall structure of a ground elevation model generation method based on heterogeneous satellites. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Example 1, please refer to Figures 1 and 2. This invention provides a method for generating a ground elevation model based on a satellite with different orbits, including the following steps:

[0051] Data collection specifically includes:

[0052] The straight-line distances d1 and d2 from the two heterodox satellites Sa1 and Sa2 to the ground observation point Pi, as well as the orbital altitudes h1 and h2 of the heterodox satellites Sa1 and Sa2, are obtained from their orbital parameters.

[0053] The resolution P of remote sensing images is obtained from the remote sensing image acquisition module of a different orbital satellite. c and radar echo intensity R a .

[0054] The latitude and longitude of multiple observation points Pi within the observation area, as well as the atmospheric refractive index A of the city, were obtained from data released by the meteorological bureaus of the cities in the observation area. t .

[0055] Data preprocessing involves transmitting the collected data to the data processing and computing module for decoding and preprocessing to obtain the parameters that will be used in the calculations of the important data processing and computing modules.

[0056] The basic elevation value H1 and the corrected elevation value H2 of multiple observation points Pi are calculated using the basic elevation value algorithm unit and the corrected elevation value algorithm unit in the data processing calculation module.

[0057] The calculated basic elevation value H1 and correction elevation value of observation point Pi are substituted into the final elevation value algorithm unit in the data processing calculation module to calculate the final elevation value H of multiple observation points Pi. f .

[0058] To optimize resource allocation, the data processing and calculation module records observation points Pi whose corrected elevation H2 is lower than 0.2 times the average value during the calculation process, and prioritizes the collection of satellite data from the remaining observation points Pi in that area.

[0059] Model generation, based on the final elevation values ​​H of different observation areas. f Depending on the characteristics of the data, an appropriate modeling method is selected. Using Geographic Information System (GIS) software, a ground elevation model is established based on the final elevation values ​​of all observation points Pi within the observation area and the selected modeling method, thus completing the generation of the ground elevation model for the observation area.

[0060] In this embodiment:

[0061] Two satellites, Sa1 and Sa2, with approximately parallel orbital planes, are selected to replace the traditional single stereo mapping satellite for acquiring observation point data. On the one hand, the two satellites, Sa1 and Sa2, can observe the observation point Pi on the ground from different angles. This cross-observation can provide two independent distance and angle information, and the three-dimensional position of point Pi can be determined through geometric calculation.

[0062] Secondly, the three-dimensional position and elevation value of observation point Pi obtained through cross-observation and geometric calculation, compared with traditional single stereo mapping satellites, can bypass the observation area where extreme weather in the sky has a significant impact on satellite remote sensing data acquisition when extreme weather occurs over the observed city. The three-dimensional position and elevation value of observation point Pi can be obtained during extreme weather, so as to avoid the time of elevation model generation in the observation area or project affected by extreme weather. In the fields of emergency rescue, engineering projects, etc., the required elevation model of the area can be generated quickly.

[0063] It is worth noting that by using two different orbital satellites, Sa1 and Sa2, two sets of independent observation data can be provided. When these data are used to calculate the elevation value of the observation point Pi, they can be mutually verified and complemented, thereby reducing the error that may be caused by a single data source. This redundancy helps to improve the accuracy of elevation calculation.

[0064] A complete elevation calculation process is constructed using three algorithm units in the data processing and calculation module. The calculated elevation values ​​of multiple observation points Pi are then used in conjunction with these three formulas to comprehensively consider factors such as the satellite's observation angle, orbital inclination, the clarity of the satellite's remote sensing image acquisition, radar echo intensity, and atmospheric refractive index, ultimately yielding the final elevation value H of the multiple observation points Pi. f This allows for more accurate elevation data, providing scientific and reliable data support for subsequent ground elevation modeling in Geographic Information System (GIS) software.

[0065] Please refer to Figures 1 and 2. The basic elevation value algorithm unit is as follows:

[0066] in:

[0067] H1 represents the base elevation value.

[0068] d1 and d2 represent the straight-line distances from the heterodox satellites Sa1 and Sa2 to the ground observation point Pi, respectively; they are calculated using the orbital parameters of the two heterodox satellites and the latitude and longitude of the observation point Pi.

[0069] h1 and h2 represent the orbital altitudes of the heterodox satellites Sa1 and Sa2, respectively, which are the distances of the heterodox satellites from the Earth's surface and are obtained through the satellite's orbital parameters.

[0070] θ1 and θ2 represent the observation angles of the different orbital satellites Sa1 and Sa2 to the ground observation point Pi, respectively, and are the angles between the satellite's line of sight and the normal to the Earth's surface.

[0071] The tangent function tan in a right triangle is defined as the length of the opposite side divided by the length of the adjacent side. Here, θ1 and θ2 represent the observation angles of the different orbital satellites Sa1 and Sa2 to the ground observation point Pi, respectively. Therefore, tanθ1 and tanθ2 represent the ratios of the opposite side length to the adjacent side length of the right triangle formed by the different orbital satellites Sa1 and Sa2 with the ground point P at the observation angle.

[0072] This part represents the elevation correction value observed after subtracting the orbital altitude from the hetero-orbiting satellite Sa1. It takes into account the distance between the satellite and the ground point, the observation angle, and the satellite's orbital altitude.

[0073] The same, This part represents the elevation correction value observed after subtracting the orbital altitude from the hetero-orbiting satellite Sa2.

[0074] Therefore, when and Subtracting these two parts actually calculates the difference between the elevation correction values ​​observed by the two satellites. That is, when two satellites with different orbits observe the same ground point Pi, the observation angles and distances are different because they are located in different orbits, resulting in the difference in elevation correction values.

[0075] Assuming the reference elevation of ground point Pi is known (which is what we want to solve in practical applications), the elevation correction values ​​observed by the two satellites with different orbits are equal to the actual elevation of ground point Pi minus the elevation of their respective orbital planes. Therefore, the difference between the two elevation correction values ​​is equal to the elevation difference between the two orbital planes plus the difference in elevation change of ground point Pi relative to these two orbital planes.

[0076] Since the two orbital planes of the two selected satellites Sa1 and Sa2 are approximately parallel, and any observation point Pi in the observation area lies between the two orbital planes, under this condition, by and The difference obtained by subtracting the two values ​​is the reference elevation of the ground point Pi.

[0077] This difference value is the calculated H1, which is the reference elevation of the ground observation point Pi.

[0078] In this embodiment:

[0079] The calculated H1 serves as the base elevation value, providing fundamental data for the subsequent generation of ground elevation models. It is directly calculated based on heterodox satellite observation data and reflects the height information of a ground point relative to a certain reference surface. The base elevation value H1 reflects the height variation information of the ground observation area and can be used to extract terrain features. For example, by comparing the base elevation values ​​H1 of different regions, terrain features such as mountains, rivers, and lakes can be identified. This information is of great significance for fields such as terrain analysis, environmental monitoring, and disaster early warning.

[0080] Please refer to Figures 1 and 2. The algorithm unit for correcting elevation values ​​is as follows:

[0081] in:

[0082] H2 represents the corrected elevation value.

[0083] h1 represents the base elevation value.

[0084] R represents the Earth's radius; in Formula 2, it is used to convert the initial elevation value h1 into a height relative to the Earth's surface.

[0085] α1 and α2 represent the orbital inclinations of the heterodox satellites Sa1 and Sa2, respectively.

[0086] The “R+H1” part represents the distance of the ground observation point Pi relative to the center of the Earth. This distance is the sum of the Earth’s radius R and the preliminary elevation H1.

[0087] This section describes the relationship between the distance of the ground detection point relative to the Earth's center and the Earth's radius, specifically as follows:

[0088] When the base elevation value H1 is large (i.e., the ground point is far from the Earth's surface), the value of this multiplication term will also increase accordingly, thus increasing the value of the correction elevation H2. Conversely, when H1 is small, the value of the multiplication term will decrease, resulting in a decrease in the value of the correction elevation H2.

[0089] This section represents the ratio of the difference in orbital inclination of two different orbital satellites, Sa1 and Sa2, to 180 degrees. This ratio reflects the degree of inclination of the orbits of the two different orbital satellites Sa1 and Sa2 relative to the Earth's equator. At α1-α2=90°, the maximum value of the difference in orbital inclination of the two different orbital satellites Sa1 and Sa2 is reached, meaning that the two orbital planes of Sa1 and Sa2 are nearly perpendicular. This indicates that the two orbital planes of the selected different orbital satellites Sa1 and Sa2 are not nearly parallel but have a large inclination angle, violating the selection requirements for different orbital satellites Sa1 and Sa2. Therefore, the multiplication term... The value of H1 will be the smallest, thus significantly reducing the value of the corrected elevation H2. When the value of the corrected elevation H2 is much lower than that of H1, it indicates that there is a problem with the selection of the positions of the two satellites Sa1 and Sa2, which need to be readjusted or selected.

[0090] Conversely, when the two orbital planes of the heterodox satellites Sa1 and Sa2 are nearly parallel, the value of α1-α2 will be smaller, and the multiplication term will be less significant. The value of will approach 1, and the impact on the calculation of the corrected elevation value H2 will be small, indicating that the selection of the hetero-orbit satellites Sa1 and Sa2 meets the requirements.

[0091] In this embodiment:

[0092] By combining the relationship between the distance of ground observation point Pi relative to the Earth's center and the Earth's radius, the orbital inclinations of two satellites Sa1 and Sa2, and the comprehensive influence of the basic elevation value H1 calculated by the basic elevation value algorithm unit, the corrected elevation value H2 is calculated. Compared with the basic elevation value H1, the corrected elevation value H2, which integrates factors such as the Earth's radius and satellite orbital inclination, has significantly improved accuracy. When monitoring more complex terrain areas, such as mountainous and hilly areas, the changes in ground elevation are more drastic. As a high-precision elevation value, the corrected elevation value H2 can better capture these terrain features, thereby supporting the generation of more refined ground elevation models and providing a scientific algorithmic basis for ground elevation model generation.

[0093] Furthermore, resource allocation is a crucial issue in the generation of the ground elevation model. The calculated corrected elevation value H2 has higher accuracy than the basic elevation value H1, but lower accuracy than the final elevation value H. f This allows for the assessment of elevation changes in different observation areas without wasting additional monitoring and computing resources, thereby optimizing resource allocation. In the field of disaster early warning, based on the calculation results of the corrected elevation H2, more resources can be invested in high-risk areas, such as areas within the disaster-stricken area where the corrected elevation H2 of some observation points Pi is much lower than the average (observation points Pi that are lower than 0.2 times the average corrected elevation, where the average corrected elevation = the sum of the corrected elevation values ​​of all observed observation points Pi / the number of observation points Pi). These areas represent areas with a large number of potholes or subsidence. Prioritizing satellite data collection for the remaining observation points Pi in these areas helps improve the accuracy and timeliness of early warning.

[0094] Please refer to Figures 1 and 2. The final elevation value algorithm unit is as follows:

[0095] in:

[0096] H fThis represents the final elevation value of the observation point Pi.

[0097] H1 represents the basic elevation value of observation point Pi.

[0098] H2 represents the calibrated elevation value of observation point Pi.

[0099] β represents the satellite data acquisition error rate.

[0100] This part represents the arithmetic mean of the squares of the sum of the basic elevation value H1 and the calibration elevation value H2 of the observation point Pi. The square root of the above arithmetic mean is performed to reflect the combined influence of the basic elevation value H1 and the calibration elevation value H2, resulting in a smoother and more stable value.

[0101] Multiplying this value by the weighting factor β in the formula means that β will adjust the result of this calculation on the final elevation value H according to the error rate of data acquisition. f The contribution of H, when β is close to 1, indicates a low data acquisition error. f It will be closer This part of the value; when β is close to 0, it indicates a high data acquisition error, H f The calculation results will be more suppressed.

[0102] The formula for calculating the satellite data acquisition error rate β is as follows:

[0103] in:

[0104] P c Represents pixel resolution; acquired from the remote sensing image acquisition module of a different orbital satellite.

[0105] R a Represents radar echo intensity; obtained from the remote sensing image acquisition module of a different orbital satellite.

[0106] A t Represents atmospheric refractive index, obtained from data released by meteorological bureaus in the cities within the observation area.

[0107] In this embodiment:

[0108] From calculating the initial elevation H1, to adjusting the corrected elevation H2, and finally to the final elevation H fThe determination of elevation data takes into account different sources of error and influencing factors at each step. Through gradual correction and adjustment, the accuracy of the elevation model can be significantly improved. In fields such as geological exploration, urban planning, and environmental monitoring, accurate elevation data is an important basis for evaluation and decision-making. The three algorithm formulas mentioned above constitute a complete elevation calculation process. By combining these three formulas, more accurate elevation data can be obtained, thereby providing more scientific and reliable data support for these fields.

[0109] In particular, the satellite data acquisition error rate β in Formula 3 represents the combined error of the heterodox satellites Sa1 and Sa2 in acquiring data from observation point Pi. By introducing this satellite data acquisition error rate β, the clarity of the satellite remote sensing image acquisition, the radar echo intensity, and the atmospheric refractive index can be comprehensively considered in relation to the final elevation value H. f The influence of these factors can be adjusted to further reduce errors and improve the accuracy of the generated elevation model.

[0110] In the generation of ground elevation models based on heterogeneous satellites, the accuracy and completeness of elevation data are crucial. By combining these three formulas, more accurate elevation data can be obtained, thus providing a more reliable numerical basis for the generation of ground elevation models. This not only helps to generate more accurate ground elevation models, but also improves the applicability of the models under different terrain and climate conditions.

[0111] The final elevation value H of all observation points Pi within this observation area f After all calculations are completed, the final elevation value H is determined based on the different observation areas. f Depending on the characteristics of the data, appropriate modeling methods should be selected. Common methods include triangular mesh (TIN) models, regular grid models, and contour line models.

[0112] The irregular triangular mesh model, which connects adjacent elevation points to form a triangular mesh, can more accurately represent complex terrain.

[0113] Regular grid models can divide a region into regular grids, with each grid point having a corresponding elevation value, making them suitable for representing terrain over a large area.

[0114] Contour models, on the other hand, draw contour lines based on elevation values, using the density and shape of these contour lines to represent the undulations of the terrain.

[0115] After selecting a suitable model, use Geographic Information System (GIS) software or other elevation model building tools to build a ground elevation model based on the final elevation values ​​of all observation points Pi in the observation area and the selected modeling method, thus completing the generation of the ground elevation model for the observation area.

[0116] The three modeling methods mentioned above are all relatively mature existing technologies in the field of modeling, and will not be described in detail here.

[0117] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for generating a ground elevation model based on a heterodox satellite, characterized in that, Includes the following steps: Step S1: Data collection, specifically including: The straight-line distances d1 and d2 from the two satellites Sa1 and Sa2 to the ground observation point Pi, as well as the orbital altitudes h1 and h2 of the satellites Sa1 and Sa2, are obtained from their orbital parameters. The resolution P of remote sensing images is obtained from the remote sensing image acquisition module of a different orbital satellite. c and radar echo intensity R a ; The latitude and longitude of multiple observation points Pi within the observation area, as well as the atmospheric refractive index A of the city, were obtained from data released by the meteorological bureaus of the cities in the observation area. t ; Step S2: Data preprocessing. The collected data information is transmitted to the data processing and calculation module for decoding and preprocessing to obtain the parameters that will be used in the calculations of the important data processing and calculation modules. Step S3: Calculate the basic elevation value H1 and the corrected elevation value H2 of multiple observation points Pi using the basic elevation value algorithm unit and the corrected elevation value algorithm unit in the data processing calculation module; Step S4: Substitute the calculated basic elevation value H1 and correction elevation value of observation point Pi into the final elevation value algorithm unit in the data processing calculation module to calculate the final elevation value H of multiple observation points Pi. f ; Step S5: Optimize resource allocation. During the calculation process, the data processing and calculation module records the observation points Pi whose corrected elevation H2 is lower than 0.2 times the average value, and prioritizes the collection of satellite data from the remaining observation points Pi in the area. Step S6: Model generation, based on the final elevation values ​​H of different observation areas. f Depending on the characteristics of the data, an appropriate modeling method is selected. Using geographic information system software, a ground elevation model is established based on the final elevation values ​​of all observation points Pi within the observation area and the selected modeling method, thus completing the generation of the ground elevation model for the observation area.

2. The method for generating a ground elevation model based on a heterodox satellite according to claim 1, characterized in that: The ground elevation model generation method employs a data collection module, a data processing and calculation module, and a model generation module.

3. The method for generating a ground elevation model based on a heterodox satellite according to claim 2, characterized in that: The data processing and calculation module includes a basic elevation value algorithm unit, a corrected elevation value algorithm unit, and a final elevation value algorithm unit.

4. The method for generating a ground elevation model based on a heterodox satellite according to claim 3, characterized in that: The basic elevation value algorithm unit is as follows: in: H1 represents the basic elevation value; d1 and d2 represent the hetero-orbiting satellite Sa1 and the straight-line distance from the hetero-orbiting satellite Sa1 to the ground observation point Pi, respectively; h1 and h2 represent the orbital altitudes of the heterogeneous satellites Sa1 and Sa2, respectively. θ1 and θ2 represent the observation angles of the different orbital satellites Sa1 and Sa2 to the ground observation point Pi, respectively, and are the angles between the satellite's line of sight and the normal to the Earth's surface.

5. The method for generating a ground elevation model based on a heterodox satellite according to claim 4, characterized in that: The elevation correction algorithm unit is as follows: in: H2 represents the corrected elevation value; h1 represents the base elevation value; R represents the Earth's radius; α1 and α2 represent the orbital inclinations of the heterodox satellites Sa1 and Sa2, respectively.

6. The method for generating a ground elevation model based on a heterodox satellite according to claim 5, characterized in that: The final elevation value algorithm unit is as follows: in: H f Represents the final elevation value of observation point Pi; H1 represents the basic elevation value of observation point Pi; H2 represents the calibration elevation value of observation point Pi; β represents the satellite data acquisition error rate.

7. The method for generating a ground elevation model based on a heterodox satellite according to claim 6, characterized in that: The formula for calculating the satellite data acquisition error rate β is as follows: in: P c Represents pixel resolution; R a Represents radar echo intensity; A t It represents atmospheric refractive index.

8. The method for generating a ground elevation model based on a heterodox satellite according to claim 7, characterized in that: The equipment used in the data collection module includes the hetero-orbiting satellites Sa1 and Sa2, as well as satellite remote sensing equipment; 9. The method for generating a ground elevation model based on a heterodox satellite according to claim 8, characterized in that: The equipment used in the model generation module includes geographic information system software.

10. A method for generating a ground elevation model based on a heterodox satellite according to claim 9, characterized in that: The core architecture of the ground elevation model generation method based on heterogeneous satellites is formed through the cooperation of three sets of algorithm units. It comprehensively considers factors such as the satellite's observation angle, orbital inclination, the clarity of the satellite's remote sensing image acquisition, radar echo intensity, and atmospheric refractive index to calculate the final elevation value H of multiple observation points Pi. f This allows for more accurate elevation data, providing scientific and reliable data support for subsequent ground elevation modeling in geographic information system software.

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