Satellite constellation based deformation monitoring method, apparatus, medium and program product

Abstract

This application provides a deformation monitoring method, device, medium, and program product based on satellite constellations, belonging to the field of Internet technology. The method includes: acquiring observation data of the monitored object from each satellite constellation in a satellite constellation platform based on the object's location information; correcting the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain corrected coordinate data; fusing the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain target coordinate data; analyzing the reference coordinate data and target coordinate data to obtain analysis results; and if the analysis results determine that the target coordinate data is abnormal, then the monitoring result is determined to be abnormal deformation of the monitored object. Using the method provided in this application, multiple satellite constellations can be used to monitor the deformation of the monitored object, effectively improving the accuracy of deformation monitoring.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to a deformation monitoring method, device, medium and program product based on a satellite constellation. Background Technology

[0002] With the development of technology, people's construction skills for bridges, dams, and other structures have greatly improved, bringing great convenience to people's lives. However, during the construction, operation, and management of these structures, if deformation occurs or geological disasters (such as landslides or subsidence) occur, it may cause damage to the surrounding ecological environment and affect the lives of nearby residents.

[0003] Currently, detection equipment can be used to monitor buildings and geological conditions in real time, obtaining deformation values ​​to detect the risk of building collapse or geological disasters. However, traditional monitoring equipment and detection methods have significant errors in obtaining deformation values ​​for buildings and mountains. Therefore, improving the accuracy of deformation monitoring is an urgent problem to be solved. Summary of the Invention

[0004] This application provides a deformation monitoring method, device, medium, and program product based on satellite constellations. It can utilize multiple satellite constellations to obtain the coordinate data of the monitored object and monitor the deformation of the monitored object, effectively improving the accuracy of deformation monitoring.

[0005] On the one hand, this application provides a deformation monitoring method based on a satellite constellation, wherein the method includes:

[0006] Based on the location information of the monitored object, the observation data of each satellite constellation in the satellite constellation platform for the monitored object are obtained; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system;

[0007] The coordinate data of the corresponding satellite constellation are corrected according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; the target correction parameters are obtained based on the meteorological data of the location of the monitored object.

[0008] The corrected coordinate data of the corresponding satellite constellation are fused according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation.

[0009] The baseline coordinate data and the target coordinate data are analyzed and processed to obtain the analysis results.

[0010] If the analysis results indicate that the target coordinate data is abnormal, then the monitoring result is determined to be that the monitored object has abnormal deformation.

[0011] On one hand, this application provides a deformation monitoring device, wherein the device includes:

[0012] The acquisition unit is used to acquire observation data of the monitored object from each satellite constellation in the satellite constellation platform based on the location information of the monitored object; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system;

[0013] The processing unit is used to perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; the target correction parameters are obtained based on the meteorological data of the location of the monitored object;

[0014] The processing unit is further configured to perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; the fusion weight parameters are determined based on the satellite orbit parameters of each satellite constellation and signal evaluation data;

[0015] The processing unit is also used to analyze and process the reference coordinate data and the target coordinate data to obtain analysis results;

[0016] The determining unit is used to determine that the monitoring object has abnormal deformation if the target coordinate data is determined to be abnormal based on the analysis results.

[0017] On one hand, this application provides a server, which includes a processor, a communication interface, and a memory. The processor, the communication interface, and the memory are interconnected. The memory stores executable program code, and the processor is used to call the executable program code to implement the deformation monitoring method based on satellite constellation provided in the embodiments of this application.

[0018] Accordingly, this application also provides a computer-readable storage medium storing a computer program adapted to be loaded by a processor and to implement the satellite constellation-based deformation monitoring method provided in the embodiments of this application.

[0019] Accordingly, this application also provides a computer program product, wherein the computer program product includes a computer program that, when executed by a processor, implements the deformation monitoring method based on a satellite constellation provided in the embodiments of this application.

[0020] In this application, the server can obtain observation data of the monitored object from each satellite constellation in the satellite constellation platform based on the location information of the monitored object; perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; analyze and process the reference coordinate data and the target coordinate data to obtain the analysis results; if the analysis results determine that there is an anomaly in the target coordinate data, the monitoring result is determined to be that there is an abnormal deformation of the monitored object. The satellite constellation platform includes at least two satellite constellations; the observation data includes meteorological data of the monitored object's location and the coordinate data of the monitored object in a preset coordinate system; the target correction parameters are obtained based on the meteorological data of the monitored object's location; and the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation. The method provided in this application embodiment can be used to observe the monitored object using various satellite constellations in a satellite constellation platform to obtain observation data. Target correction parameters are determined using meteorological data of the monitored object's location from the observation data. These target correction parameters are then used to correct the coordinate data of the monitored object in the observation data, resulting in corrected coordinate data. Furthermore, fusion weight parameters for each satellite constellation are determined using satellite orbit parameters and signal evaluation data. The corrected coordinate data is then weighted and fused using these fusion weight parameters to obtain the target coordinate data of the monitored object. Finally, the reference coordinate data and target coordinate data are used to determine whether the monitored object exhibits abnormal deformation, effectively improving the accuracy of deformation monitoring. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0022] Figure 1 This is a schematic diagram of the structure of a deformation monitoring system based on a satellite constellation provided in an embodiment of this application;

[0023] Figure 2This is a schematic flowchart of a deformation monitoring method based on a satellite constellation provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of a process for generating a fusion weight matrix, using three satellite constellations as an example, provided in an embodiment of this application.

[0025] Figure 4 This is a schematic diagram of the structure of a deformation monitoring device provided in an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Detailed Implementation

[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0028] 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 apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment.

[0029] It should be understood that although the terms first, second, third, etc., may be used herein to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this document, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if," as used herein, may be interpreted as "when," "when," or "in response to determination." Furthermore, as used herein, the singular forms "a," "an," and "the" are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms "comprising," "including," indicate the presence of the stated feature, step, operation, element, component, item, kind, and / or group, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups. The terms "or," "and / or," "including at least one of the following," etc., as used in this application, may be interpreted as inclusive, or mean any one or any combination thereof. For example, "including at least one of the following: A, B, C" means "any one of the following: A; B; C; A and B; A and C; B and C; A and B and C." Similarly, "A, B, or C" or "A, B, and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A and B and C." Exceptions to this definition only occur when the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0030] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0031] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0032] To better understand the embodiments of this application, some related technical terms will be introduced below:

[0033] Global Navigation Satellite System (GNSS): Also known as a global satellite navigation system, it is a space-based radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates, velocity, and time information at any location on the Earth's surface or in near-Earth space. It is a general term for satellite navigation systems that can achieve global coverage.

[0034] The WGS-84 coordinate system (World Geodetic System-1984 Coordinate System) is a geocentric coordinate system established in 1984. It provides a spatial reference for the Global Positioning System (GPS) and is consistent with the International Earth Reference System (ITRS). This coordinate system was established based on satellite radar altimetry and Earth's gravity field data, forming a new three-dimensional spatial reference system by correcting the reference origin and scale datum. In practical applications, it needs to be transformed into regional coordinate systems such as the 1980 Xi'an Coordinate System through parametric models to meet different surveying and mapping needs.

[0035] The following describes a deformation monitoring system based on a satellite constellation provided by an embodiment of this application.

[0036] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of a deformation monitoring system based on a satellite constellation provided in an embodiment of this application. Figure 1As shown, the deformation monitoring system based on satellite constellations includes a first satellite constellation 101, an Nth satellite constellation 102, a satellite constellation platform 103, and a server 104. The first satellite constellation 101 and the Nth satellite constellation 102 each contain at least one satellite, and the total number of satellite constellations is at least two. The first satellite constellation 101, the Nth satellite constellation 102, and the server 104 communicate with the satellite constellation platform 103. The satellite constellation platform 103 may include GNSS, and the first satellite constellation 101 and the Nth satellite constellation 102 may include satellite navigation systems included in GNSS (such as BeiDou Navigation Satellite System (BDS), Global Positioning System (GPS), and GLONASS). The server 104 may include cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. It should be noted that the above-mentioned communication methods, servers, satellite constellations, and satellite constellation platforms are merely examples, not an exhaustive list, and include, but are not limited to, the above-mentioned communication methods, servers, satellite constellations, and satellite constellation platforms.

[0037] In this embodiment, server 104 can obtain observation data of the monitored object from each satellite constellation in satellite constellation platform 103 based on the location information of the monitored object; perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; analyze and process the reference coordinate data and the target coordinate data to obtain the analysis result; if it is determined from the analysis result that the target coordinate data is abnormal, then the monitoring result is determined to be that the monitored object has abnormal deformation. The satellite constellation platform 103 includes at least two satellite constellations; the observation data includes meteorological data of the monitored object's location and the coordinate data of the monitored object in a preset coordinate system; the target correction parameters are obtained based on the meteorological data of the monitored object's location; and the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation. The method provided in this application embodiment can be used to observe the monitored object using various satellite constellations in a satellite constellation platform to obtain observation data. Target correction parameters are determined using meteorological data of the monitored object's location from the observation data. These target correction parameters are then used to correct the coordinate data of the monitored object in the observation data, resulting in corrected coordinate data. Furthermore, fusion weight parameters for each satellite constellation are determined using satellite orbit parameters and signal evaluation data. The corrected coordinate data is then weighted and fused using these fusion weight parameters to obtain the target coordinate data of the monitored object. Finally, the reference coordinate data and target coordinate data are used to determine whether the monitored object exhibits abnormal deformation, effectively improving the accuracy of deformation monitoring.

[0038] The following describes a deformation monitoring method based on a satellite constellation provided by an embodiment of this application.

[0039] Please see Figure 2 , Figure 2 This is a schematic flowchart illustrating a deformation monitoring method based on a satellite constellation provided in this application. The deformation monitoring method based on a satellite constellation provided in this application can be applied to the above-mentioned... Figure 1 The deformation monitoring system based on a satellite constellation shown below will be illustrated using the application of this deformation monitoring method to the server within the system as an example. Figure 2 As shown, this satellite constellation-based deformation monitoring method includes:

[0040] S201. Based on the location information of the monitored object, obtain the observation data of each satellite constellation in the satellite constellation platform for the monitored object; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system.

[0041] In this embodiment, the monitoring object can refer to structures such as bridges and dams, or places such as slopes and mountains that are prone to geological disasters such as landslides and subsidence. The location information of the monitoring object can include the latitude and longitude information and altitude of the monitoring object. The satellite constellation platform can include a global satellite navigation system (e.g., GNSS). The satellite constellation can include satellite navigation systems within the global satellite navigation system (e.g., BeiDou Navigation Satellite System, Global Positioning System, and GLONASS). Meteorological data can include parameters reflecting atmospheric conditions such as atmospheric pressure, temperature, and water vapor pressure. These parameters affect the propagation speed and path of GNSS signals in the troposphere. The preset coordinate system can include the WGS-84 coordinate system. The observation data can include meteorological data of the location of the monitoring object and the coordinate data of the monitoring object in the preset coordinate system.

[0042] The server can send the location information of the monitored object to the satellite constellation platform. The satellite constellation platform then sends the location information of the monitored object to each satellite constellation. Once the satellite constellation receives the location information of the monitored object, it can observe the monitored object based on the latitude, longitude, and altitude information included in the location information, and obtain the observation data of the monitored object.

[0043] It should be noted that the number of satellite constellations used for monitoring in the satellite constellation platform is two or more. The specific number of satellite constellations can be adjusted according to the actual situation. This application embodiment does not limit the number of satellite constellations.

[0044] S202. Based on the target correction parameters of each satellite constellation, perform data correction processing on the coordinate data of the corresponding satellite constellation to obtain the corrected coordinate data of the monitored object; the target correction parameters are obtained based on the meteorological data of the location of the monitored object.

[0045] In this embodiment, the server can use the target correction parameters of each satellite constellation to correct the coordinate data of the monitored object observed by its own satellite constellation, thereby obtaining corrected coordinate data and effectively improving the accuracy of the coordinate data of the monitored object. The target correction parameters of each satellite constellation are determined by the server based on meteorological data of the location of the monitored object.

[0046] Among them, the target correction parameter is used to correct the tropospheric delay of the Earth. The tropospheric delay is the positioning error caused by the longer propagation path and slower speed of GNSS satellite signals when passing through the Earth's troposphere due to the influence of the atmospheric medium. It is the main source of error in the plateau environment. This embodiment can correct this error and effectively improve the accuracy of the coordinate data of the monitored object.

[0047] In one feasible embodiment, each satellite constellation determines its own target correction parameters, which may include: acquiring meteorological data of the location of the monitored object observed by each satellite constellation in the satellite constellation platform; determining the correction parameters of each satellite constellation in the satellite constellation platform based on the meteorological data of the location of the monitored object; and determining the correction parameters of each satellite constellation as the target correction parameters of the corresponding satellite constellation.

[0048] Specifically, the Saastamoinen model can be used to calculate the basic tropospheric delay, which is the correction parameter for each satellite constellation. The calculation formula is as follows:

[0049] Δd_Saa=(0.002277 / sin(E))×[P+(1255 / T+0.05)×e]

[0050] In the formula, E is the satellite elevation angle, P is the atmospheric pressure, T is the absolute temperature, and its unit is Kelvin (K); e is the water vapor pressure.

[0051] Specifically, the server determines the correction parameters of each satellite constellation as the target correction parameters for that constellation. This can include: determining the station elevation parameters of each satellite constellation in the satellite constellation platform based on the location information of the monitored object; determining the compensation data for each satellite constellation based on meteorological data and the station elevation parameters; and performing data compensation processing on the correction parameters of the corresponding satellite constellation based on the compensation data to obtain the target correction parameters for each satellite constellation. The station elevation parameters are used to indicate the actual altitude of the monitored object's location.

[0052] In one feasible embodiment, the aforementioned compensation data may include altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters. The aforementioned meteorological data may include atmospheric pressure data and temperature data. The server determines the compensation data for each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation. This may include: the server determining the altitude compensation parameters for each satellite constellation based on atmospheric pressure data and the station elevation parameters of each satellite constellation; the server acquiring the annual cumulative day data of the monitored object and determining the seasonal compensation parameters for each satellite constellation based on the annual cumulative day data of the monitored object; and the server determining the temperature compensation parameters for each satellite constellation based on temperature data. The altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters of each satellite constellation are then used as the compensation data for the corresponding satellite constellation. In this embodiment, due to the characteristics of the plateau environment, such as high altitude and low air pressure, large seasonal water vapor variations, and significant diurnal temperature differences, the compensation data can be adapted to the characteristics of the plateau, effectively improving the monitoring accuracy of the coordinate data of the monitored object.

[0053] In one feasible embodiment, the altitude compensation parameter can be an altitude adaptive factor, which can be a correction coefficient used to compensate for the decrease in atmospheric pressure caused by the increase in altitude, thereby reducing the tropospheric delay; the seasonal compensation parameter can be a seasonal variation factor, which can be a correction coefficient used to compensate for the influence of the seasonal periodic change in atmospheric water vapor content on the tropospheric delay; and the temperature compensation parameter can be a temperature response factor, which can be a correction coefficient used to compensate for the influence of the change in atmospheric refractive index caused by temperature changes on the signal propagation speed.

[0054] In a feasible embodiment, the altitude adaptation factor K_altitude is calculated as follows:

[0055] K_altitude=(P / P0)α×exp((h-h0) / H_scale)

[0056] In the formula, P0 is the standard sea-level pressure, h is the station elevation, h0 is the reference elevation, and H_scale is the atmospheric elevation; α is the pressure-altitude attenuation exponent, an empirical constant used to characterize the nonlinear attenuation characteristics of atmospheric pressure with changes in station elevation; the standard sea-level pressure can be taken as 1013.25 hPa, the reference elevation as 500 m, and the atmospheric elevation as 8000 m. The altitude adaptive factor is calculated using a power-law and exponential composite model, where the standard sea-level pressure represents the ideal atmospheric state, the station elevation reflects the actual altitude, the reference elevation is set at 500 meters as the correction benchmark, and the atmospheric elevation controls the pressure attenuation law. This factor effectively characterizes the acceleration effect of the low-pressure environment at high altitudes on signal propagation speed.

[0057] In a feasible embodiment, the formula for calculating the seasonal variation factor K_season is:

[0058] K_season=1+A_season×cos(2π×(DOY-φ_season) / 365.25)

[0059] In the formula, A_season represents the seasonal variation amplitude, DOY represents the accumulated days of the year, and φ_season represents the phase shift. 365.25 represents the average number of days in a tropical year, taking into account leap years. The Earth's revolution around the Sun takes approximately 365 days, 5 hours, 48 ​​minutes, and 46 seconds. A common year is calculated as 365 days, and there is a leap year every four years with 366 days, averaging approximately 365.25 days in a year. The seasonal variation factor constructs a periodic adjustment function. The seasonal variation amplitude is determined based on long-term meteorological statistics from the plateau, the accumulated days of the year represent the time sequence within the year, and the phase shift corresponds to the point of transition between seasonal extremes in the Northern Hemisphere. This factor accurately reflects the periodic fluctuations in atmospheric water vapor content brought about by monsoon circulation.

[0060] In a feasible embodiment, the temperature response factor K_temperature is calculated using the following formula:

[0061] K_temperature=1+β_T×(T-T_ref) / T_ref

[0062] In the formula, β_T is the temperature sensitivity coefficient, and T_ref is the reference temperature. The temperature response factor adopts a linear sensitivity model, the temperature sensitivity coefficient characterizes the correlation strength between temperature and delay changes, and the reference temperature is the international standard atmospheric temperature value. This factor effectively compensates for the changes in signal propagation path caused by the drastic diurnal temperature range in plateau regions.

[0063] In a feasible embodiment, the basic tropospheric delay value can be multiplied and fused with three compensation parameters to obtain the target correction data. The formula for calculating the target correction data Δd_trop is as follows:

[0064] Δd_trop=Δd_Saa×K_altitude×K_season×K_temperature

[0065] In this embodiment, three compensation parameters work together to achieve full-dimensional compensation of environmental parameters, ultimately outputting a precise delay correction amount that conforms to the actual atmospheric conditions at high altitudes. The final tropospheric delay is used to offset errors in the original GNSS observation data, completing the tropospheric delay correction of the observation data. An environmentally adaptive compensation process specifically addresses the challenge of tropospheric delay correction in high-altitude environments. A baseline is established through basic value calculations, and multiple compensation parameters are adapted to characteristics such as seasonal temperature differences at high altitudes, achieving precise correction of delay errors. This can improve monitoring accuracy by 35%, effectively offsetting the interference of the high-altitude environment on signal propagation, providing high-quality observation data for subsequent multi-constellation fusion positioning, and effectively improving the accuracy of deformation monitoring.

[0066] S203. Perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation.

[0067] In this embodiment, the server can obtain the fusion weight parameters of the satellite constellation based on its satellite orbit parameters and signal evaluation data. Then, it uses these fusion weight parameters to perform data fusion processing on the corrected coordinate data of each satellite constellation to obtain the target coordinate data of the monitored object. When the monitored object changes or different objects are monitored, the monitoring performance of the satellite constellation will change. By rationally allocating the weights of each satellite constellation to the monitored object, the monitoring advantages of different satellite constellations for different monitored objects can be fully utilized, effectively improving the accuracy of the target coordinate data.

[0068] In one feasible embodiment, the server determines the fusion weight parameters of each satellite constellation, which may include: the server obtaining the satellite orbit parameters and signal evaluation data of each satellite constellation for the monitored object from the satellite constellation platform based on the location information of the monitored object; and determining the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation.

[0069] The signal evaluation data may include signal strength data and signal fluctuation data. Based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation, the fusion weight parameters of each satellite constellation are determined. This may include: obtaining the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation; and determining the fusion weight parameters of each satellite constellation based on the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation.

[0070] In one feasible embodiment, determining the fusion weight parameters for each satellite constellation based on its satellite orbit parameters, signal strength data, and signal fluctuation data may include: the server determining the positioning error parameters for each satellite constellation based on its satellite orbit parameters; determining the number of observable satellites for each satellite constellation based on its signal strength data; determining the operational status parameters for each satellite constellation based on its signal fluctuation data; and determining the fusion weight parameters for each satellite constellation based on its positioning error parameters, the number of observable satellites, and the operational status parameters.

[0071] Specifically, the server can extract satellite orbit parameters, signal strength data, and signal fluctuation data from the observation data of each satellite constellation. Among them, satellite orbit parameters are an indicator of the impact of the geometric layout of each constellation's satellites in the sky above the monitored object on positioning accuracy: by using the satellite orbit parameters in the observation data, a positioning error parameter (Position Accuracy Attenuation Factor, PDOP) reflecting the geometric distribution characteristics of the satellite constellation is calculated. The smaller the PDOP value, the more dispersed the satellites are in space, the better their geometric configuration, the stronger their ability to suppress errors in the positioning results, and the better the satellite spatial distribution quality; conversely, the larger the PDOP value, the worse the distribution quality.

[0072] Satellite orbital parameters can include the satellite's azimuth (az). i ), elevation angle (el) i The satellite geometry matrix H can be constructed based on the azimuth and elevation angles, along with the receiver clock error correction term (usually set to 1). i Taking a configuration with 4 satellites as an example, a 4×4 covariance matrix Q can be obtained using the geometric matrices of the four satellites. The positioning error parameter can be the square root of the sum of the variance terms of the first three main diagonals of the covariance matrix. Here, PDOP < 3 is considered an excellent configuration, 3 ≤ PDOP < 6 is a good configuration, and PDOP ≥ 6 is a poor configuration. The azimuth angle is the horizontal angle measured clockwise from true north of the receiving point to the satellite direction, and the elevation angle is the angle between the antenna centerline and the horizontal plane. The elevation angle can eliminate the cutoff elevation angle, effectively reducing atmospheric refraction and multipath interference.

[0073] It should be noted that the range of the cutoff elevation angle can be 5°-15°, and the specific value can be set according to the specific situation. This application embodiment does not limit it.

[0074] Wherein, geometric matrix H i The formula is shown below:

[0075]

[0076] The formula for the covariance matrix Q is shown below:

[0077]

[0078] In the formula, Q xx Q yx Q zx Q tx It can correspond to H i -cosel i cosaz i Q xy Q yy Q zy Q ty It can correspond to H i -cosel i sinaz i Q xz Q yz Q zz Q tz It can correspond to H i -sinel i Q xt Q yt Q zt Q tt This is the receiver clock error correction term.

[0079] The formula for calculating the Positioning Error Parameter (PDOP) is as follows:

[0080]

[0081] The number of observable satellites refers to the total number of satellites in each constellation that the server can stably receive signals from at the current observation time, and whose signal strength meets the positioning calculation requirements. Based on the signal strength data in the observation data, satellites with signal strength reaching a preset threshold are selected, and the number of selected satellites is counted. The more observable satellites there are, the richer the positioning reference information that the server can obtain, and the stronger the reliability and anti-interference capability of the positioning results.

[0082] It is possible to obtain the signal strength data of each satellite in a satellite constellation, determine the number of satellites whose signal strength data is greater than or equal to a set signal strength, and determine the number of satellites as the number of observable satellites in that satellite constellation.

[0083] Operating status parameters can refer to system operational stability, which is an indicator for evaluating whether the current operating status of each satellite constellation is stable and whether signal transmission is continuous. By analyzing signal strength data and signal fluctuation data in the observation data, the continuity of satellite signal transmission (whether there are signal interruptions or jumps) and the magnitude of error fluctuations (whether they are within the normal operating range) are determined. If the satellite signal is continuous and uninterrupted, and the error fluctuation amplitude is small, it indicates that the satellite's operating status is stable and the system's operational stability is good. If there are frequent signal interruptions or large signal fluctuations, it is determined that the system's operational stability is poor.

[0084] The system can statistically analyze whether satellite signals experience interruptions or jumps, calculating the ratio of uninterrupted time to total observation time, which is determined as the continuity rate. A higher continuity rate indicates better stability. Furthermore, the variance and / or standard deviation of signal transmission errors are calculated to determine if they are within the error threshold range for normal satellite operation; smaller fluctuations indicate better stability. Combining the quantified results of signal transmission continuity and error fluctuation amplitude with the set standard continuity rate, variance, and / or standard deviation, a normalized operating state parameter between 0 and 1 is obtained (if the operating state parameter exceeds 1, it is set to 1). Here, 1 represents optimal satellite operating state with no signal interruption and minimal error fluctuation, while 0 represents complete signal interruption or error exceeding the threshold.

[0085] By combining the PDOP values ​​of the satellite spatial distribution quality, the statistical results of the number of observable satellites, and the judgment results of the system operation stability, the real-time positioning performance of each satellite constellation can be comprehensively calculated, thereby providing a data basis for the fusion weight of each satellite constellation, effectively improving the accuracy of the fusion weight parameters, and thus improving the accuracy of the coordinate data of the monitored objects.

[0086] In a feasible embodiment, taking a satellite constellation including GPS, BeiDou, and GLONASS as an example, the formula for calculating the fusion weight of the GPS system is as follows:

[0087] W_GPS=(C_GPS / PDOP_GPS)×min(N_GPS / K_GPS, 1.0)×Health_GPS

[0088] In the formula, W_GPS represents the weight of the GPS system; PDOP_GPS is the GPS constellation position accuracy attenuation factor; N_GPS is the number of visible GPS satellites; Health_GPS is the health status factor of the GPS system; C_GPS represents the GPS system accuracy attenuation coefficient, used to adjust the influence of PDOP on the weight; K_GPS represents the ideal satellite reference number of the GPS system, indicating the number of GPS satellites required to achieve ideal positioning performance, with 8 satellites as the ideal reference value; min(N_GPS / K_GPS, 1.0) refers to converting the current absolute number of visible satellites N_GPS into a relative ratio related to the ideal reference number K_GPS. This min function can eliminate the unfairness caused by the difference in scale between different constellations. For example, the BeiDou system has K_BDS=12, and the GPS system has K_GPS=8. This means that when BeiDou has 12 satellites and GPS has 8 satellites, they both achieve a perfect score (1.0) in this aspect, even though their absolute numbers are different. Here, 1.0 is the upper limit of saturation. When the calculated ratio of N_GPS / K_GPS is greater than or equal to 1.0, the min function will output 1.0, thereby maximizing the contribution of this term and effectively improving the accuracy of the fusion weights.

[0089] The weight calculation formula for the BeiDou system is as follows:

[0090] W_BDS=W_base_BDS×GEO_enhance×Constellation_mature

[0091] W_base_BDS=(C_BDS / PDOP_BDS)×min(N_BDS / K_BDS, 1.0)×Health_BDS

[0092] In the formula, W_BDS represents the weight of the BeiDou system, GEO_enhance is the geographic enhancement factor, which is dynamically adjusted based on the geographic coordinates of the station; Constellation_mature is the constellation completeness factor; W_base_BDS is the basic weight of the BeiDou system, PDOP_BDS is the position accuracy attenuation factor of the BeiDou constellation, N_BDS is the number of visible BeiDou satellites, Health_BDS is the health status factor of the BeiDou system; C_BDS is the accuracy attenuation coefficient of the BeiDou system, used to adjust the influence of PDOP on the weight; K_BDS is the ideal satellite reference number of the BeiDou satellite navigation system, representing the number of BeiDou satellites required to achieve ideal positioning performance, with 12 satellites as the ideal reference value.

[0093] First, the base weight W_base_BDS is calculated, then multiplied by the geographic enhancement factor GEO_enhance and the constellation perfection factor Constellation_mature to obtain the weights of the BeiDou system. The geographic enhancement factor GEO_enhance quantifies the improvement effect of GEO satellites on the positioning performance of the BeiDou Navigation Satellite System in the Asia-Pacific region. Since the positions of GEO satellites over the Asia-Pacific region are relatively fixed, their signal propagation paths are stable and less affected by atmospheric factors. By analyzing indicators such as the signal-to-noise ratio and carrier phase observation stability of GEO satellite signals at stations in the Asia-Pacific region, and combining this with positioning calculation results, the degree of improvement in positioning accuracy by GEO satellites is calculated.

[0094] The Constellation_mature factor reflects the completeness of the BeiDou constellation in the Asia-Pacific region. It considers factors such as the number of visible BeiDou satellites in the Asia-Pacific region, the uniformity of their spatial distribution, and their health status. The total number of BeiDou satellites visible from stations in the Asia-Pacific region over a certain period is statistically analyzed, along with the proportion of satellites in different orbital types (GEO, IGSO, MEO). Simultaneously, satellite signal quality, orbital accuracy, and other health indicators are monitored. By establishing a comprehensive evaluation model, these factors are quantitatively analyzed to derive the Constellation_mature factor. For example, when the number of visible satellites in the Asia-Pacific region is sufficient, the distribution of satellites in different orbital types is reasonable, and the satellites are in good health, the Constellation_mature factor value is higher, indicating a higher degree of completeness of the BeiDou constellation in the region, enabling it to provide more reliable and accurate positioning services.

[0095] The weight calculation formula for the GLONASS system is as follows:

[0096] W_GLO=W_base_GLO×FDMA_advantage×Latitude_factor

[0097] In the formula, W_GLO is the weight of the GLONASS system, W_base_GLO is the base weight of the GLONASS system, FDMA_advantage is the FDMA advantage factor of the GLONASS system, and Latitude_factor is the latitude factor of the GLONASS system.

[0098] The FDMA advantage factor (FDMA_advantage) measures the improvement of GLONASS system's positioning performance in mid-to-high latitude regions by FDMA technology. By comparing the positioning results of GLONASS system with other GNSS systems employing Code Division Multiple Access (CDMA) technology (such as GPS) in mid-to-high latitude regions, the effectiveness of FDMA technology in reducing signal interference and improving signal quality is analyzed.

[0099] The latitude factor reflects the impact of mid-to-high latitude characteristics on the positioning performance of the GLONASS system. The atmospheric environment and ionospheric activity in mid-to-high latitude regions differ from those in low latitude regions, and these factors affect the propagation of GNSS signals. By analyzing observation data from stations at different latitudes in mid-to-high latitude regions, this study investigates the impact of latitude variations on the positioning accuracy, convergence time, and other performance indicators of the GLONASS system.

[0100] Based on the corrected fusion weight parameters of the three satellite constellations, the weighted least squares method is used for fusion calculation. The calculation formula is as follows:

[0101]

[0102] In the formula, P_fusion is the position solution vector (target coordinate data) representing the three-dimensional coordinates of the station after multi-constellation fusion, i is the constellation index, i takes the values ​​1, 2, and 3 to correspond to the GPS system, BeiDou system, and GLONASS system, respectively; Pi represents the position solution vector of the i-th constellation; Qi represents the covariance matrix calculated by the i-th satellite constellation, and W_norm_i is the fusion weight parameter of the i-th satellite constellation.

[0103] In this embodiment, the weighted least squares method is used to quantify and integrate the performance advantages and positioning reliability of each satellite constellation into the fusion process, avoiding the limitations of simple data superposition. This improves the accuracy of coordinate data to the millimeter level, enabling precise capture of minute deformations in different environments. This provides high-quality positioning results for deformation monitoring, effectively improving the accuracy of monitoring in complex environments, and thus improving the accuracy of deformation monitoring.

[0104] After fusion calculation using the weighted least squares method, the fusion weight parameters for each satellite constellation are obtained: the fusion weight parameter for the GPS system is 0.274 (i.e., 27.4%), the fusion weight parameter for the BeiDou system is 0.508 (i.e., 50.8%), and the fusion weight parameter for the GPS system is 0.218 (i.e., 21.8%). It should be noted that the fusion weight parameters for each satellite constellation mentioned above are merely examples. The actual fusion weight can be determined based on the monitored object. The detection performance of satellite constellations for the same monitored object varies at different times or in different seasons, and their fusion weight parameters will also change accordingly. The value of the fusion weight parameter needs to be determined according to the actual situation, and this application embodiment does not impose any limitations.

[0105] In one feasible embodiment, the server can determine the satellite orbit configuration and satellite coverage data of each satellite constellation based on the location information of the monitored object; analyze and process the satellite orbit configuration and satellite coverage data of each satellite constellation to obtain the monitoring performance parameters of each satellite constellation for the monitored object; and adjust the fusion weight parameters of each satellite constellation based on the monitoring performance parameters.

[0106] Among them, the monitoring performance parameters refer to the regional performance characteristics of each satellite constellation. The regional performance characteristics refer to the positioning performance advantages of different constellations based on their satellite orbit design in different geographical locations. The regional performance characteristics are obtained by analyzing the satellite orbit configuration and satellite coverage data of each constellation.

[0107] Taking GPS as an example, its satellite orbit configuration and satellite coverage data indicate that GPS is a globally covering constellation. Its weighting formula does not include a separate parameter to characterize regional performance; it is typically a constant. Differences in the regional performance characteristics of the GPS system can be reflected through real-time calculated PDOP values ​​and N_GPS. If the PDOP value of a region's GPS increases and the number of visible satellites decreases, its weight decreases accordingly. For example, if the baseline regional performance characteristic of GPS is 1, the baseline PDOP value is 2, and the baseline number of visible satellites is 10, and a region's PDOP value is measured to be 4 and the number of visible satellites to be 8, then the regional performance characteristic of GPS in that region can be determined as 1 × (2 / 4) × (8 / 10) = 0.4. This 0.4 can be multiplied by the GPS fusion weighting parameter to obtain a new fusion weighting parameter, thereby adjusting the fusion weighting parameters of each satellite constellation.

[0108] S204. Analyze and process the reference coordinate data and the target coordinate data to obtain the analysis results.

[0109] In this embodiment, the reference coordinate data can be the average value of the target coordinate data within a set time period, or it can be the target coordinate data from the previous time. The reference coordinate data can be determined as the standard normal coordinates of the monitored object. The coordinate data can be the three-dimensional coordinates of the monitored object. The server can calculate the Euclidean distance difference between the reference coordinate data and the target coordinate data in three-dimensional space, which can include displacement on the horizontal plane and vertical displacement (settlement). The reference coordinate data can utilize a sliding time window, adjusting the reference coordinate data according to changes in the time window, so that the reference coordinate data can adapt to long-term, slow deformation.

[0110] In one feasible embodiment, the server analyzes and processes the reference coordinate data and the target coordinate data to obtain the analysis result, which may include: the server determining the deformation of the monitored object based on the reference coordinate data and the target coordinate data; when the deformation of the monitored object is greater than or equal to a preset threshold, the analysis result is determined to be that the target coordinate data is abnormal; when the deformation of the monitored object is less than the preset threshold, the analysis result is determined to be that the target coordinate data is not abnormal.

[0111] The server can calculate the difference between the baseline coordinate data and the target coordinate data to obtain the difference between the baseline coordinate data and the target coordinate data, and determine the deformation of the monitored object. For example, if the baseline coordinate data is P1=(-1.8, 5.9, 2.7) and the target coordinate data is P1=(-1.81, 5.86, 2.73), the deformation of the monitored object can be obtained as -0.01, -0.04, and 0.03, respectively. The sign of the data can indicate the direction of deformation of the monitored object. -0.01 can indicate that the monitored object has shifted by 0.01 basic units (meters) in the first direction (e.g., south), -0.04 can indicate that the monitored object has shifted by 0.04 basic units (meters) in the second direction (e.g., west), and 0.03 can indicate that the monitored object has shifted by 0.03 basic units (meters) in the third direction (e.g., vertical).

[0112] S205. If the analysis results indicate that the target coordinate data is abnormal, then the monitoring result is determined to be that the monitored object has abnormal deformation.

[0113] In this embodiment, if the analysis results determine that the target coordinate data is abnormal, the server can determine that the detection result of the monitored object is that there is abnormal deformation.

[0114] In one feasible embodiment, when the detection result of the monitored object is determined to be abnormal deformation, an alarm message can be generated and sent to the relevant operation and maintenance personnel. The operation and maintenance personnel can then perform timely maintenance on the monitored object, effectively improving the geological disaster early warning capability and the engineering safety monitoring level.

[0115] Please see Figure 3 , Figure 3 This is a schematic diagram illustrating a process for generating a fusion weight matrix, using three satellite constellations as an example, as provided in an embodiment of this application. Figure 3As shown, this method of generating a fusion weight matrix, taking three satellite constellations as an example, can include: acquiring observation data from each satellite constellation; calculating positioning error parameters, the number of observable satellites, and operational status parameters; calculating the weight parameters of the first satellite constellation; calculating the weight parameters of the second satellite constellation; adjusting the weight parameters of the second satellite constellation using a geographic augmentation factor and a constellation completeness factor; calculating the weight parameters of the third satellite constellation; adjusting the weight parameters of the second satellite constellation using a frequency division multiple access factor and a latitude factor; performing weight normalization processing to obtain the fusion weight parameters of each satellite constellation; and outputting the fusion weight matrix of each satellite constellation.

[0116] It should be noted that, Figure 3 For a specific implementation of generating a fusion weight matrix using three satellite constellations as an example, please refer to the description in steps S201-S205, which will not be repeated here.

[0117] In this embodiment, the server can obtain observation data of each satellite constellation on the monitored object from the satellite constellation platform based on the location information of the monitored object; perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; analyze and process the reference coordinate data and the target coordinate data to obtain the analysis result; if it is determined from the analysis result that there is an anomaly in the target coordinate data, then the monitoring result is determined to be that there is an abnormal deformation of the monitored object. The satellite constellation platform includes at least two satellite constellations; the observation data includes meteorological data of the location of the monitored object and the coordinate data of the monitored object in a preset coordinate system; the target correction parameters are obtained based on the meteorological data of the location of the monitored object; and the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation. The method provided in this application embodiment can be used to observe the monitored object using various satellite constellations in a satellite constellation platform to obtain observation data. Target correction parameters are determined using meteorological data of the monitored object's location from the observation data. These target correction parameters are then used to correct the coordinate data of the monitored object in the observation data, resulting in corrected coordinate data. Furthermore, fusion weight parameters for each satellite constellation are determined using satellite orbit parameters and signal evaluation data. The corrected coordinate data is then weighted and fused using these fusion weight parameters to obtain the target coordinate data of the monitored object. Finally, the reference coordinate data and target coordinate data are used to determine whether the monitored object exhibits abnormal deformation, effectively improving the accuracy of deformation monitoring.

[0118] The following describes a deformation monitoring device provided in an embodiment of this application.

[0119] Please seeFigure 4 , Figure 4 This is a structural schematic diagram of a deformation monitoring device provided in an embodiment of this application. Figure 4 As shown, the deformation monitoring device includes:

[0120] The acquisition unit 401 is used to acquire observation data of the monitored object from each satellite constellation in the satellite constellation platform based on the location information of the monitored object; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system;

[0121] The processing unit 402 is used to perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; the target correction parameters are obtained based on the meteorological data of the location of the monitored object;

[0122] The processing unit 402 is further configured to perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; the fusion weight parameters are determined based on the satellite orbit parameters of each satellite constellation and the signal evaluation data.

[0123] The processing unit 402 is also used to analyze and process the reference coordinate data and the target coordinate data to obtain analysis results;

[0124] The determining unit 403 is used to determine that the monitoring result is that the monitored object has abnormal deformation if the target coordinate data is determined to be abnormal based on the analysis result.

[0125] In a feasible embodiment, the acquisition unit 401 is further configured to: acquire meteorological data of the location of the monitored object observed by each satellite constellation in the satellite constellation platform; the determination unit 403 is further configured to: determine the correction parameters of each satellite constellation in the satellite constellation platform based on the meteorological data of the location of the monitored object; and determine the correction parameters of each satellite constellation as the target correction parameters of the corresponding satellite constellation.

[0126] In a feasible embodiment, the determining unit 403 determines the correction parameters of each satellite constellation as the target correction parameters for the corresponding satellite constellation by: determining the station elevation parameters of each satellite constellation in the satellite constellation platform based on the location information of the monitored object; determining the compensation data of each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation; and performing data compensation processing on the correction parameters of the corresponding satellite constellation based on the compensation data of each satellite constellation to obtain the target correction parameters of each satellite constellation.

[0127] In one feasible embodiment, the compensation data includes altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters, and the meteorological data includes atmospheric pressure data and temperature data. When the determining unit 403 determines the compensation data for each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation, it is specifically used to: determine the altitude compensation parameters for each satellite constellation based on the atmospheric pressure data and the station elevation parameters of each satellite constellation; acquire the annual cumulative day data of the monitored object, and determine the seasonal compensation parameters for each satellite constellation based on the annual cumulative day data of the monitored object; determine the temperature compensation parameters for each satellite constellation based on the temperature data; and determine the altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters of each satellite constellation as the compensation data for the corresponding satellite constellation.

[0128] In a feasible embodiment, the acquisition unit 401 is further configured to: acquire satellite orbit parameters and signal evaluation data of each satellite constellation for the monitored object from the satellite constellation platform based on the location information of the monitored object; the determination unit 403 is further configured to: determine the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation.

[0129] In one feasible embodiment, the signal evaluation data includes signal strength data and signal fluctuation data; when the determining unit 403 determines the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation, it is specifically used to: acquire the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation; and determine the fusion weight parameters of each satellite constellation based on the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation.

[0130] In a feasible embodiment, when the determining unit 403 determines the fusion weight parameters of each satellite constellation based on the satellite orbit parameters, signal strength data, and signal fluctuation data of each satellite constellation, it is specifically used to: determine the positioning error parameters of each satellite constellation based on the satellite orbit parameters of each satellite constellation; determine the number of observable satellites of each satellite constellation based on the signal strength data of each satellite constellation; determine the operating status parameters of each satellite constellation based on the signal fluctuation data of each satellite constellation; and determine the fusion weight parameters of each satellite constellation based on the positioning error parameters, the number of observable satellites, and the operating status parameters of each satellite constellation.

[0131] In a feasible embodiment, the determining unit 403 is further configured to: determine the satellite orbit configuration and satellite coverage data of each satellite constellation based on the location information of the monitored object; the processing unit 402 is further configured to: analyze and process the satellite orbit configuration and satellite coverage data of each satellite constellation to obtain the monitoring performance parameters of each satellite constellation for the monitored object; and adjust the fusion weight parameters of each satellite constellation based on the monitoring performance parameters.

[0132] In a feasible embodiment, the processing unit 402 analyzes and processes the reference coordinate data and the target coordinate data to obtain the analysis result, specifically for: determining the deformation of the monitored object based on the reference coordinate data and the target coordinate data; generating an analysis result if the deformation of the monitored object is greater than or equal to a preset threshold; the analysis result is used to indicate that the target coordinate data is abnormal; generating an analysis result if the deformation of the monitored object is less than the preset threshold; the analysis result is used to indicate that the target coordinate data is not abnormal.

[0133] In a feasible embodiment, the deformation monitoring device provided in this application can be implemented in software. The deformation monitoring device can be stored in a memory and can be software in the form of programs and plug-ins, and includes a series of units, including an acquisition unit, a processing unit, and a determination unit; wherein, the acquisition unit, processing unit, and determination unit are used to implement the satellite constellation-based deformation monitoring method provided in this application.

[0134] In other feasible embodiments, the deformation monitoring device provided in this application can also be implemented in a combination of hardware and software. As an example, the deformation monitoring device provided in this application can be a processor in the form of a hardware decoding processor, which is programmed to execute the deformation monitoring method based on satellite constellation provided in this application. For example, the processor in the form of a hardware decoding processor can be one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0135] The following describes a server provided by an embodiment of this application.

[0136] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a server provided in an embodiment of this application. Figure 5 The server in this embodiment may include one or more processors 501, one or more communication interfaces 502, and a memory 503. The processors 501, communication interfaces 502, and memory 503 are connected via a bus 504. The memory 503 stores computer programs, including program instructions, and the processors 501 execute the program instructions stored in the memory 503. By running the executable program code in the memory 503, the processors 501 perform the following operations:

[0137] Based on the location information of the monitored object, the observation data of each satellite constellation in the satellite constellation platform for the monitored object are obtained; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system;

[0138] The coordinate data of the corresponding satellite constellation are corrected according to the target correction parameters of each satellite constellation to obtain the corrected coordinate data of the monitored object; the target correction parameters are obtained based on the meteorological data of the location of the monitored object.

[0139] The corrected coordinate data of the corresponding satellite constellation are fused according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object; the fusion weight parameters are determined based on the satellite orbit parameters and signal evaluation data of each satellite constellation.

[0140] The baseline coordinate data and the target coordinate data are analyzed and processed to obtain the analysis results.

[0141] If the analysis results indicate that the target coordinate data is abnormal, then the monitoring result is determined to be that the monitored object has abnormal deformation.

[0142] In a feasible embodiment, the processor 501 is further configured to: acquire meteorological data of the location of the monitored object observed by each satellite constellation in the satellite constellation platform; determine the correction parameters of each satellite constellation in the satellite constellation platform based on the meteorological data of the location of the monitored object; and determine the correction parameters of each satellite constellation as the target correction parameters of the corresponding satellite constellation.

[0143] In a feasible embodiment, when the processor 501 determines the correction parameters of each satellite constellation as the target correction parameters of the corresponding satellite constellation, it is specifically used to: determine the station elevation parameters of each satellite constellation in the satellite constellation platform based on the location information of the monitored object; determine the compensation data of each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation; and perform data compensation processing on the correction parameters of the corresponding satellite constellation based on the compensation data of each satellite constellation to obtain the target correction parameters of each satellite constellation.

[0144] In one feasible embodiment, the compensation data includes altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters, and the meteorological data includes atmospheric pressure data and temperature data. When the processor 501 determines the compensation data for each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation, it specifically performs the following: determining the altitude compensation parameters for each satellite constellation based on the atmospheric pressure data and the station elevation parameters of each satellite constellation; acquiring the annual cumulative day data of the monitored object and determining the seasonal compensation parameters for each satellite constellation based on the annual cumulative day data of the monitored object; determining the temperature compensation parameters for each satellite constellation based on the temperature data; and determining the altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters of each satellite constellation as the compensation data for the corresponding satellite constellation.

[0145] In a feasible embodiment, the processor 501 is further configured to: obtain satellite orbit parameters and signal evaluation data of each satellite constellation for the monitored object from the satellite constellation platform based on the location information of the monitored object; and determine the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation.

[0146] In one feasible embodiment, the signal evaluation data includes signal strength data and signal fluctuation data; when the processor 501 determines the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation, it is specifically used to: acquire the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation; and determine the fusion weight parameters of each satellite constellation based on the satellite orbit parameters, signal strength data and signal fluctuation data of each satellite constellation.

[0147] In one feasible embodiment, when the processor 501 determines the fusion weight parameters of each satellite constellation based on the satellite orbit parameters, signal strength data, and signal fluctuation data of each satellite constellation, it is specifically used to: determine the positioning error parameters of each satellite constellation based on the satellite orbit parameters of each satellite constellation; determine the number of observable satellites of each satellite constellation based on the signal strength data of each satellite constellation; determine the operating status parameters of each satellite constellation based on the signal fluctuation data of each satellite constellation; and determine the fusion weight parameters of each satellite constellation based on the positioning error parameters, the number of observable satellites, and the operating status parameters of each satellite constellation.

[0148] In a feasible embodiment, the processor 501 is further configured to: determine the satellite orbit configuration and satellite coverage data of each satellite constellation based on the location information of the monitored object; analyze and process the satellite orbit configuration and satellite coverage data of each satellite constellation to obtain the monitoring performance parameters of each satellite constellation for the monitored object; and adjust the fusion weight parameters of each satellite constellation based on the monitoring performance parameters.

[0149] In a feasible embodiment, when the processor 501 analyzes and processes the reference coordinate data and the target coordinate data to obtain the analysis result, it is specifically used to: determine the deformation of the monitored object based on the reference coordinate data and the target coordinate data; if the deformation of the monitored object is greater than or equal to a preset threshold, then generate an analysis result; the analysis result is used to indicate that the target coordinate data is abnormal; if the deformation of the monitored object is less than the preset threshold, then generate an analysis result; the analysis result is used to indicate that the target coordinate data is not abnormal.

[0150] The method steps in the embodiments of this application can be adjusted, combined, or deleted according to actual needs.

[0151] The units in the embodiments of this application can be merged, divided, and deleted according to actual needs.

[0152] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0153] In this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions are generally described in detail only when they appear for the first time. When they appear again, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions that are not described in detail later can be referred to their previous relevant detailed descriptions.

[0154] In this application, the descriptions of the various embodiments have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0155] The technical features of the present application can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present application.

[0156] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, storage disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0157] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A deformation monitoring method based on a satellite constellation, characterized in that, The method includes: Based on the location information of the monitored object, the observation data of each satellite constellation in the satellite constellation platform for the monitored object are obtained; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system; Based on the location information of the monitored object, determine the station elevation parameters of each satellite constellation in the satellite constellation platform; Based on the meteorological data and the station elevation parameters of each satellite constellation, the compensation data for each satellite constellation is determined. Based on the compensation data of each satellite constellation, the correction parameters of the corresponding satellite constellation are processed to obtain the target correction parameters of each satellite constellation. Based on the target correction parameters of each satellite constellation, the coordinate data of the corresponding satellite constellation is corrected to obtain the corrected coordinate data of the monitored object. Based on the location information of the monitored object, the satellite orbit parameters and signal evaluation data of each satellite constellation for the monitored object are obtained from the satellite constellation platform; Based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation, the fusion weight parameters of each satellite constellation are determined. The corrected coordinate data of the corresponding satellite constellation are fused according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object. The baseline coordinate data and the target coordinate data are analyzed and processed to obtain the analysis results. If the analysis results indicate that the target coordinate data is abnormal, then the monitoring result is determined to be that the monitored object has abnormal deformation.

2. The method according to claim 1, characterized in that, The compensation data includes altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters; the meteorological data includes atmospheric pressure data and temperature data; determining the compensation data for each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation includes: Based on the atmospheric pressure data and the station elevation parameters of each satellite constellation, the altitude compensation parameters of each satellite constellation are determined. Acquire the annual cumulative day data of the monitored object, and determine the seasonal compensation parameters of each satellite constellation based on the annual cumulative day data of the monitored object; Based on the temperature data, the temperature compensation parameters for each satellite constellation are determined; The altitude compensation parameters, seasonal compensation parameters, and temperature compensation parameters of each satellite constellation are determined as the compensation data for the corresponding satellite constellation.

3. The method according to claim 1, characterized in that, The signal evaluation data includes signal strength data and signal fluctuation data; the determination of the fusion weight parameters for each satellite constellation based on the satellite orbit parameters obtained from each satellite constellation and the signal evaluation data includes: Obtain the satellite orbit parameters, signal strength data, and signal fluctuation data for each satellite constellation; The fusion weight parameters for each satellite constellation are determined based on the satellite orbit parameters, signal strength data, and signal fluctuation data of each satellite constellation.

4. The method according to claim 3, characterized in that, The step of determining the fusion weight parameters for each satellite constellation based on its satellite orbit parameters, signal strength data, and signal fluctuation data includes: Based on the satellite orbit parameters of each satellite constellation, determine the positioning error parameters of each satellite constellation; Based on the signal strength data of each satellite constellation, determine the number of observable satellites in each satellite constellation; Based on the signal fluctuation data of each satellite constellation, the operating status parameters of each satellite constellation are determined; The fusion weight parameters for each satellite constellation are determined based on the positioning error parameters, the number of observable satellites, and the operational status parameters of each constellation.

5. The method according to claim 4, characterized in that, The method further includes: Based on the location information of the monitored objects, determine the satellite orbit configuration and satellite coverage data of each satellite constellation; The satellite orbit configuration and satellite coverage data of each satellite constellation are analyzed and processed to obtain the monitoring performance parameters of each satellite constellation for the monitored object; The fusion weight parameters of each satellite constellation are adjusted based on the monitoring performance parameters.

6. The method according to any one of claims 1-5, characterized in that, The analysis and processing of the reference coordinate data and the target coordinate data to obtain the analysis results include: The deformation of the monitored object is determined based on the reference coordinate data and the target coordinate data; If the deformation of the monitored object is greater than or equal to a preset threshold, an analysis result is generated; the analysis result is used to indicate that there is an anomaly in the target coordinate data; If the deformation of the monitored object is less than the preset threshold, an analysis result is generated; the analysis result is used to indicate that there are no abnormalities in the target coordinate data.

7. A deformation monitoring device, characterized in that, The device includes: The acquisition unit is used to acquire observation data of the monitored object from each satellite constellation in the satellite constellation platform based on the location information of the monitored object; the satellite constellation platform includes at least two satellite constellations, and the observation data includes meteorological data of the location of the monitored object and coordinate data of the monitored object in a preset coordinate system; The determining unit is used to determine the station elevation parameters of each satellite constellation in the satellite constellation platform based on the location information of the monitored object. The determining unit is further configured to determine the compensation data for each satellite constellation based on the meteorological data and the station elevation parameters of each satellite constellation. The processing unit is used to perform data compensation processing on the correction parameters of the corresponding satellite constellation based on the compensation data of each satellite constellation, so as to obtain the target correction parameters of each satellite constellation. The processing unit is further configured to perform data correction processing on the coordinate data of the corresponding satellite constellation according to the target correction parameters of each satellite constellation, so as to obtain the corrected coordinate data of the monitored object; The acquisition unit is also used to acquire satellite orbit parameters and signal evaluation data of each satellite constellation for the monitored object from the satellite constellation platform based on the location information of the monitored object; The determining unit is further configured to determine the fusion weight parameters of each satellite constellation based on the satellite orbit parameters and signal evaluation data obtained from each satellite constellation. The processing unit is also used to perform data fusion processing on the corrected coordinate data of the corresponding satellite constellation according to the fusion weight parameters of each satellite constellation to obtain the target coordinate data of the monitored object. The processing unit is also used to analyze and process the reference coordinate data and the target coordinate data to obtain analysis results; The determining unit is further configured to determine that the monitoring result indicates abnormal deformation of the monitored object if the target coordinate data is determined to be abnormal based on the analysis result.

8. A server, characterized in that, include: The system includes a processor, a communication interface, and a memory, which are interconnected. The memory stores executable program code, and the processor is used to call the executable program code to implement the deformation monitoring method based on a satellite constellation as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed on a computer, cause the computer to implement the deformation monitoring method based on a satellite constellation as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the deformation monitoring method based on a satellite constellation as described in any one of claims 1-6.

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