Data fusion method and device, electronic equipment and storage medium

Abstract

The invention relates to a data fusion method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a plurality of measurement points around a request point of which the wave height is to be determined; under the condition that the plurality of measurement points comprise a plurality of first measurement points, obtaining a plurality of first measurement data obtained by respectively measuring wave heights at the plurality of first measurement points, and obtaining a plurality of first simulation data obtained by carrying out wave height numerical simulation on grids where the plurality of first measurement points are located, the distance between the first measurement point and the request point is not greater than a first distance threshold value; based on the first measurement data and the first simulation data, determining first correction data representing the difference between the simulation data and the measurement data; and correcting the wave height simulation data of the request point by using the first correction data to obtain target wave height data of the request point. Therefore, accurate and accurate wave height data can be obtained in a sea area which is not covered by equipment.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a data fusion method and device, an electronic device, and a storage medium. Background Art

[0002] Wave height data provides important reference for human maritime activities, disaster warning, etc., and is of great significance in many fields.

[0003] At present, although wave height data can be collected through equipment, the coverage of the equipment is limited, so wave height data in some sea areas cannot be obtained.

[0004] In addition, historical observation data can also be numerically simulated to obtain wave height simulation data. However, the spatial resolution of the data obtained by this method is low, so the precision and accuracy of the simulated wave height data are low. Summary of the invention

[0005] In view of this, the present disclosure proposes a data fusion solution.

[0006] According to one aspect of the present disclosure, a data fusion method is provided, including: obtaining multiple measurement points around a request point for determining a wave height; when the multiple measurement points include multiple first measurement points, obtaining multiple first measurement data obtained by measuring the wave height at each of the multiple first measurement points, and performing numerical simulation of the wave height on the grids where the multiple first measurement points are located to obtain multiple first simulation data, wherein the first measurement point is a measurement point that is no more than a first distance threshold from the request point; determining first correction data characterizing the difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data; and using the first correction data to correct the wave height simulation data of the request point to obtain target wave height data of the request point.

[0007] In a possible implementation, the method further includes: when the multiple measurement points include at least one second measurement point, obtaining a historical measurement time series obtained by measuring the wave height at the second measurement point, and performing wave height numerical simulation on multiple surrounding grids around the second measurement point to obtain multiple historical simulation time series, the second measurement point is farther from the request point than the first measurement point; based on the historical measurement time series and the multiple historical simulation time series, determining the spatial correlation of the wave data in the spatial dimension; based on the spatial correlation, determining multiple target grids corresponding to the request point; obtaining the wave height simulation data, and performing wave height numerical simulation on the multiple target grids to obtain multiple second simulation data; based on the wave height simulation data and the multiple second simulation data, determining second correction data characterizing the error between the simulation data related in the spatial dimension; using the second correction data, correcting the wave height simulation data to obtain the target wave height data.

[0008] In a possible implementation, the determining of first correction data characterizing the difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data includes: determining an importance index of each of the multiple first measurement points based on multiple paths from the request point to each of the first measurement points; determining a first difference between each of the first measurement data and its corresponding first simulation data; and determining the first correction data based on each of the first differences and each of the importance indexes.

[0009] In a possible implementation, the first measuring point includes a first buoy point, and the importance index of each of the multiple first measuring points is determined based on multiple paths from the request point to each of the first measuring points, including: determining the first shortest path from the request point to each of the first buoy points to obtain multiple first shortest paths; for each of the first buoy points, performing the following steps to obtain each of the importance indexes: determining the importance index of the single first buoy point based on the multiple first shortest paths and the first shortest path of the single first buoy point.

[0010] In a possible implementation, the first measurement point includes: a target reflection point at which the sea surface effectively reflects the microwave signal, the first measurement data includes: target remote sensing inversion data obtained by inverting the wave height of the target reflection point based on the reflection of the microwave signal, and determining the importance index of each of the multiple first measurement points based on the multiple paths from the request point to each of the first measurement points, including: screening the reflection points that reflect the microwave signal according to spatial conditions to obtain multiple first reflection points; screening the remote sensing inversion data corresponding to the multiple first reflection points according to numerical conditions to obtain multiple target remote sensing inversion data and the target reflection point corresponding to each of the target remote sensing inversion data; determining the second shortest path from the request point to each of the target reflection points to obtain multiple second shortest paths; performing the following steps for each of the target reflection points to obtain each of the importance indexes: determining the importance index of the single target reflection point based on the multiple second shortest paths and the second shortest path of the single target reflection point.

[0011] In a possible implementation, determining the spatial correlation of the wave data in the spatial dimension based on the historical measurement time series and the multiple historical simulation time series includes:

[0012] According to the wave level, the data in the historical measurement time series are screened to obtain the first sub-time series corresponding to each wave level; step 1, for each moment in a single first sub-time series, the simulation data at each moment and the simulation data at each moment are extracted from each historical simulation time series to obtain multiple second sub-time series; step 2, the single first sub-time series is subjected to correlation detection with each second sub-time series to obtain multiple correlation indicators; step 3, based on each correlation indicator, a strongly correlated second sub-time series that is mutually associated with the second measurement point is determined, and the grid corresponding to the strongly correlated second sub-time series is used as the selected grid of the wave level corresponding to the single first sub-time series; for each first sub-time series, the steps 1 to 3 are executed to obtain the selected grid of each wave level, and the spatial position relationship between the second measurement point and the selected grid of each wave level is used as the spatial correlation relationship.

[0013] In a possible implementation, the determining of multiple target grids corresponding to the request point based on the spatial correlation includes: determining a first wave height level corresponding to the wave height simulation data; determining the multiple target grids based on the first wave height level and the spatial correlation; the determining of second correction data characterizing the error between simulation data related in the spatial dimension based on the wave height simulation data and the multiple second simulation data includes: determining a second difference between the wave height simulation data and each of the second simulation data; and determining the second correction data based on each of the second differences.

[0014] According to another aspect of the present disclosure, there is provided a data fusion device, comprising:

[0015] A measuring point acquisition unit, used to acquire a plurality of measuring points around a request point for determining a wave height;

[0016] A first measurement data and first simulation data acquisition unit, configured to acquire, when the plurality of measurement points include a plurality of first measurement points, a plurality of first measurement data obtained by measuring the wave height at each of the plurality of first measurement points, and a plurality of first simulation data obtained by numerically simulating the wave height for each of the grids where the plurality of first measurement points are located, wherein the first measurement point is a measurement point that is not more than a first distance threshold from the request point;

[0017] A first correction data determination unit, configured to determine first correction data representing a difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data;

[0018] The target wave height data determining unit is used to correct the wave height simulation data of the request point using the first correction data to obtain the target wave height data of the request point.

[0019] In a possible implementation manner, the device further includes:

[0020] a second measurement point time series acquisition unit, configured to acquire, when the plurality of measurement points include at least one second measurement point, a historical measurement time series obtained by measuring wave heights at the second measurement point, and a plurality of historical simulation time series obtained by numerically simulating wave heights for a plurality of surrounding grids around the second measurement point, wherein the second measurement point is farther from the request point than the first measurement point;

[0021] A spatial correlation determination unit, configured to determine the spatial correlation of the wave data in a spatial dimension based on the historical measurement time series and the plurality of historical simulation time series;

[0022] A target grid determination unit, configured to determine a plurality of target grids corresponding to the request point based on the spatial correlation relationship;

[0023] A second simulation data determining unit, configured to obtain the wave height simulation data, and perform wave height numerical simulation on the plurality of target grids to obtain a plurality of second simulation data;

[0024] A second correction data determination unit, configured to determine, based on the wave height simulation data and the plurality of second simulation data, second correction data representing errors between simulation data related in a spatial dimension;

[0025] The second target wave height data determining unit is used to correct the wave height simulation data using the second correction data to obtain the target wave height data.

[0026] In a possible implementation manner, the first correction data determining unit is further configured to:

[0027] Determining, based on a plurality of paths from the request point to each of the first measurement points, an importance index of each of the plurality of first measurement points;

[0028] Determine a first difference between each of the first measurement data and the first simulation data corresponding to each of the first measurement data;

[0029] The first correction data is determined based on each of the first differences and each of the importance indicators.

[0030] In a possible implementation, the first measurement point includes a first buoy point, and determining the importance index of each of the plurality of first measurement points based on the plurality of paths from the request point to each of the first measurement points includes:

[0031] Determine the first shortest path from the request point to each of the first buoy points, and obtain multiple first shortest paths;

[0032] For each of the first buoy points, the following steps are performed to obtain each of the importance indicators:

[0033] Based on the multiple first shortest paths and the first shortest path of a single first buoy point, an importance index of the single first buoy point is determined.

[0034] In a possible implementation, the first measurement point includes: a target reflection point where the sea surface effectively reflects the microwave signal, the first measurement data includes: target remote sensing inversion data obtained by inverting the wave height of the target reflection point based on the microwave signal reflection, and the importance index of each of the multiple first measurement points based on the multiple paths from the request point to each of the first measurement points includes:

[0035] According to the spatial conditions, the reflection points reflecting the microwave signal are screened to obtain a plurality of first reflection points;

[0036] According to the numerical conditions, the remote sensing inversion data corresponding to the plurality of first reflection points are screened to obtain the plurality of target remote sensing inversion data and the target reflection points corresponding to the respective target remote sensing inversion data;

[0037] Determine the second shortest path from the request point to each of the target reflection points to obtain multiple second shortest paths;

[0038] The following steps are performed for each target reflection point to obtain each importance index:

[0039] Based on the multiple second shortest paths and the second shortest path of a single target reflection point, an importance index of the single target reflection point is determined.

[0040] In a possible implementation manner, the spatial correlation relationship determining unit is further configured to:

[0041] According to the wave level, the data in the historical measurement time series are screened to obtain a first sub-time series corresponding to each wave level;

[0042] Step 1, for each moment in a single first sub-time series, extract each moment and the simulation data at each moment from each of the historical simulation time series to obtain multiple second sub-time series;

[0043] Step 2, performing correlation detection on the single first sub-time series and each of the second sub-time series to obtain multiple correlation indicators;

[0044] Step 3: Based on each of the correlation indicators, determine a strongly correlated second sub-time series that is mutually associated with the second measurement point, and use the grid corresponding to the strongly correlated second sub-time series as the selected grid for the wave level corresponding to the single first sub-time series;

[0045] For each of the first sub-time series, execute steps 1 to 3 to obtain the selected grid for each of the wave levels, and use the spatial position relationship between the second measurement point and the selected grid for each of the wave levels as the spatial correlation relationship.

[0046] In a possible implementation manner, the target grid determination unit is further configured to:

[0047] Determining a first wave height level corresponding to the wave height simulation data;

[0048] Determining the plurality of target grids based on the first wave height level and the spatial correlation relationship;

[0049] The second correction data determination unit is further used to:

[0050] determining a second difference between the wave height simulation data and each of the second simulation data;

[0051] Based on each of the second differences, the second correction data are determined.

[0052] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0053] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0054] According to another aspect of the present disclosure, a computer program product is provided, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0055] In the disclosed embodiment, although there is no equipment deployed at the request point, only wave height simulation data can be obtained. However, using the disclosed method, the first measurement data measured at multiple first measurement points around the request point, and the first simulation data obtained by numerically simulating the wave height of the grid where the first measurement point is located, are used to jointly determine the first correction data, and the first correction data is used to correct the wave height simulation data of the request point. And the first correction data characterizes the difference between the measurement data and the simulation data, so that the wave height simulation data is corrected to make it closer to the measurement data obtained by the measurement equipment. Therefore, the accuracy of the target wave height data is improved. In this way, accurate and precise wave height data can be obtained in sea areas not covered by the equipment.

[0056] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0058] Figure 1 A flowchart of a data fusion method provided in an embodiment of the present disclosure.

[0059] Figure 2 A schematic diagram of a perimeter grid provided for an embodiment of the present disclosure.

[0060] Figure 3 A schematic diagram of the structure of a data fusion device provided in an embodiment of the present disclosure.

[0061] Figure 4 A schematic diagram of the structure of an electronic device for English data fusion provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0062] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0063] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0064] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the subject matter of the present disclosure.

[0065] Figure 1 The following is a flow chart of the data fusion method provided by the embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0066] S11, obtaining a plurality of measurement points around a request point for determining a wave height.

[0067] The request point may be a geographical location in the sea area where the wave height data is to be obtained. The request point may represent a point in the sea area corresponding to a geographical coordinate, and the obtained wave height data may represent the wave height of the point. The request point may represent an area, and the obtained wave height data may represent the wave height of the area. The above is only an example, and the present disclosure does not limit the physical range represented by the request point.

[0068] In the present disclosure, it is not necessary to deploy equipment for measuring wave height data at the request point. The equipment here can be equipment that is set in the seawater to directly measure the wave height data; or it can be equipment that is not set in the seawater and indirectly measures the wave height data. Equipment for measuring sea wave data can be deployed at the measurement point. The multiple measurement points in the embodiment of the present disclosure can be all or part of the measurement points in the first area including the request point. Alternatively, the multiple measurement points can be all or part of the measurement points whose distance from the request point does not exceed a preset distance. The present disclosure does not limit the specific value of the preset distance and the number of measurement points.

[0069] S12, when the multiple measurement points include multiple first measurement points, obtain multiple first measurement data obtained by measuring the wave height at each of the multiple first measurement points, and obtain multiple first simulation data by numerically simulating the wave height for the grids where each of the multiple first measurement points is located, wherein the first measurement point is a measurement point that is no more than a first distance threshold from the request point.

[0070] The multiple measurement points obtained in S11 may all be first measurement points, or some of them may be first measurement points. The first distance threshold may be determined according to the accuracy of the device for measuring the wave height. In one example, the first distance threshold may be selected between 30 kilometers and 80 kilometers, preferably 50 kilometers. Of course, for different devices, the value range of the first distance threshold and the value of the preferred value may be different. In the embodiment of the present disclosure, the multiple first measurement points may be all the first measurement points around the request point, or some of the first measurement points.

[0071] The first measurement data may represent the wave height data obtained by measuring the wave height at the first measurement point through the device. The sea area may be divided into grids, each grid representing a sea area. The first simulation data represents the wave height data obtained by numerically simulating the wave height of the grid (sea area) where the first measurement point is located using historical observation data. A single first measurement point may correspond to at least one first measurement data and one first simulation data.

[0072] S13: Determine first correction data representing the difference between the simulation data and the measurement data based on each of the first measurement data and each of the first simulation data.

[0073] Exemplarily, an average value A of the plurality of first measurement data and an average value B of the plurality of first simulation data may be determined, and then a difference between the average value A and the average value B may be determined, and the difference may be used as the first correction data. The above is only an example, and the first correction data may also be determined using the method described below. The embodiment of the present disclosure does not limit the method for determining the first correction data.

[0074] S14, using the first correction data, correcting the wave height simulation data of the request point to obtain the target wave height data of the request point.

[0075] The wave height simulation data may be wave height data obtained by numerically simulating the waves in the grid (sea area) where the request point is located. The wave height simulation data may be added to the first correction data to complete the correction of the wave height simulation data. Alternatively, the first correction data may be multiplied by a fixed constant to obtain a product, and then the wave height simulation data may be added to the product; or, other operations may be performed on the wave height simulation data and the first correction data to complete the correction of the wave height simulation data. The above is only an example, and the disclosed embodiment does not limit the method of using the first correction data to correct the wave height simulation data.

[0076] After correction, the target wave height data can be obtained. The target wave height data can be the wave height data of the sea area corresponding to the request point. The accuracy and precision of the target wave height data are higher than the wave height simulation data, and are close to the measurement data obtained by measuring using the equipment.

[0077] In the disclosed embodiment, although there is no equipment deployed at the request point, only wave height simulation data can be obtained. However, using the disclosed method, the first measurement data measured at multiple first measurement points around the request point, and the first simulation data obtained by numerically simulating the wave height of the grid where the first measurement point is located, are used to jointly determine the first correction data, and the first correction data is used to correct the wave height simulation data of the request point. And the first correction data characterizes the difference between the measurement data and the simulation data, so that the wave height simulation data is corrected to make it closer to the measurement data obtained by the measurement equipment. Therefore, the accuracy of the target wave height data is improved. In this way, accurate and precise wave height data can be obtained in sea areas not covered by the equipment.

[0078] In a possible implementation, the method further includes: when the multiple measurement points include at least one second measurement point, obtaining a historical measurement time series obtained by measuring the wave height at the second measurement point, and performing wave height numerical simulation on multiple surrounding grids around the second measurement point to obtain multiple historical simulation time series, the second measurement point is farther from the request point than the first measurement point; based on the historical measurement time series and the multiple historical simulation time series, determining the spatial correlation of the wave data in the spatial dimension; based on the spatial correlation, determining multiple target grids corresponding to the request point; obtaining the wave height simulation data, and performing wave height numerical simulation on the multiple target grids to obtain multiple second simulation data; based on the wave height simulation data and the multiple second simulation data, determining second correction data characterizing the error between the simulation data related in the spatial dimension; using the second correction data, correcting the wave height simulation data to obtain the target wave height data.

[0079] The multiple measurement points obtained in S11 may all be second measurement points, or some of them may be second measurement points. The second measurement point may be a measurement point that is greater than the first distance threshold and less than the second distance threshold from the request point. The second distance threshold may be determined based on the accuracy of the device for measuring the wave height. In one example, the second distance threshold may be selected between 60 km and 210 km, preferably 200 km. Of course, the value range of the second distance threshold and the value of the preferred value may be different for different devices.

[0080] The historical measurement time series may be a series of measurement data measured by the device at the second measurement point, and a single measurement data corresponds to a measurement moment. The measurement data here is wave height data obtained by measuring the sea waves.

[0081] There may be a plurality of peripheral grids around the grid where the second measuring point is located, and these peripheral grids may be adjacent to or not adjacent to the grid where the second measuring point is located. The peripheral grids may be symmetrically distributed around the second measuring point. Figure 2 A schematic diagram of a perimeter grid provided in an embodiment of the present disclosure. Figure 2 For example, the grid (unfilled) where the second measurement point is located is taken as the center, and the surrounding 24 grids (filled) can be used as peripheral grids. Alternatively, the grid (unfilled) where the second measurement point is located can be taken as the center, and the adjacent 9 grids (filled) can be used as peripheral grids. The above is only an example, and the embodiment of the present disclosure does not limit the number of peripheral grids.

[0082] A single historical simulation time series can be a series of simulated data obtained by numerically simulating the ocean waves for a surrounding grid based on historical observation data, and a single simulated data corresponds to a simulated moment. The simulated data here refers to the ocean wave height simulated by the ocean wave numerical value. A single measurement moment can correspond to a single simulated moment.

[0083] For example, the historical measurement time series and the historical simulation time series can be aligned in the time dimension; or there is a time difference between the two, that is, each measurement moment can be adjusted by the time difference to obtain each simulated moment. A single peripheral grid can correspond to a historical simulation time series.

[0084] Since the seawater is flowing, the waves at the measurement point can be associated with the waves on at least part of the surrounding grid, so the measurement data at the second measurement point can be associated with the simulation data on part of the surrounding grid.

[0085] In an embodiment of the present disclosure, the spatial correlation of the wave data in the spatial dimension can be determined based on the historical measurement time series and multiple historical simulation time series. For example, a visualization method can be used to draw a graph of the historical measurement time series and multiple historical simulation time series; the horizontal axis is the time (measurement time, simulated time); the vertical axis is the wave height value. The spatial correlation is determined by observation. For another example, regression analysis can be performed by taking the historical measurement time series as the dependent variable and the multiple historical simulation time series as the independent variable to perform a multivariate linear regression analysis to determine the spatial correlation. The above is only an example, and the embodiment of the present disclosure does not limit the method for determining the spatial correlation. The spatial correlation can characterize which historical measurement time series are interrelated with which historical simulation time series. As mentioned above, a single surrounding grid can correspond to a historical simulation time series. Thus, the spatial correlation can characterize which surrounding grids the second measurement point (or the grid where the second measurement point is located) is interrelated with. That is, in an embodiment of the present disclosure, the spatial correlation can characterize the spatial position relationship between a specified grid and the surrounding grids that are interrelated with the specified grid. Based on this spatial correlation, the demand point can be used as a specified grid to determine the target grid associated with the grid where the demand point is located. That is, multiple target grids corresponding to the demand point can be obtained.

[0086] The second simulation data may be wave height data obtained by numerically simulating the wave height of the target grid. For example, the median of the plurality of second simulation data obtained may be determined, and then the difference between the median and the wave height simulation data may be determined. The difference is used as the second correction data. The above is only an example, and the second correction data may also be determined using the method described below. The disclosed embodiment does not limit the method for determining the second correction data.

[0087] In the embodiment of the present disclosure, the wave height simulation data may be added to the second correction data to complete the correction of the wave height simulation data. Alternatively, the second correction data may be multiplied by a fixed constant to obtain a product, and then the wave height simulation data may be added to the product; or, other operations may be performed on the wave height simulation data and the second correction data to complete the correction of the wave height simulation data. The above is only an example, and the embodiment of the present disclosure does not limit the method of using the second correction data to correct the wave height simulation data.

[0088] After correction, the target wave height data can be obtained. The target wave height data can be the wave height data of the sea area corresponding to the request point. The accuracy and precision of the target wave height data are higher than the wave height simulation data, and are close to the measurement data obtained by measuring using the equipment.

[0089] In the disclosed embodiment, when there is no equipment deployed at the request point and there is no available measurement data within the range of the first distance threshold from the request point, the target grid corresponding to the request point is determined using the historical measurement time series measured at the second measurement point and the historical simulation time series corresponding to the multiple surrounding grids. The wave height simulation data of the request point and the second simulation data corresponding to each of the multiple target grids are used to jointly determine the second correction data that characterizes the error between the simulation data related in the spatial dimension. The second correction data is used to correct the wave height simulation data of the request point. The wave height simulation data is corrected. In this way, the accuracy of the wave height simulation data obtained by numerical simulation is improved, and accurate and precise wave height data can be obtained in sea areas not covered by the equipment.

[0090] In one example, for a single first simulation data, the first measurement point can be determined first, and the first correction data can be determined using the above method to obtain the target wave height data. If the first measurement point is not determined, the second measurement point can be determined, and the second correction data can be determined using the above method, and the wave height simulation data can be corrected using the second correction data to obtain the target wave height data.

[0091] In this way, the target wave height data can be made as close as possible to the measurement data measured by the equipment. Even if the first measurement point cannot be obtained, the wave height simulation data can still be corrected. The accuracy and precision of the target wave height data are improved. In addition, when there are multiple first simulation data (for example: first simulation data time series) that need to be corrected, a single first simulation data can be the wave height data at a moment. Each first simulation data can correspond to a moment. Among them, a part of the moment can be the same as the measurement moment of the first measurement point, then the first measurement point can be determined for the first simulation data at this part of the moment, and the above method can be used to correct this part of the first simulation data. If a part of the moment is not the same as the measurement moment of the first measurement point, then for this part of the moment, it is possible to determine to extract the available second measurement point, and continue to correct this part of the first simulation data. Improve the correctability rate of multiple first simulation data.

[0092] In a possible implementation, the determining of first correction data characterizing the difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data includes: determining an importance index of each of the multiple first measurement points based on multiple paths from the request point to each of the first measurement points; determining a first difference between each of the first measurement data and its corresponding first simulation data; and determining the first correction data based on each of the first differences and each of the importance indexes.

[0093] There may be one or more paths from the request point to a single first measurement point. Thus, there may be multiple paths between the request point and each first measurement point. The path here may be a waterway path from the request point to a single first measurement point. The importance index may characterize the importance of the first measurement point. The importance index may characterize the importance of the difference between the measured data and the simulated data at the first measurement point.

[0094] Exemplarily, a first mapping relationship between each numerical interval and each importance index can be preset. Determine the first numerical interval in which the average value of the lengths of multiple paths from the request point to the single first measurement point falls, determine the importance index corresponding to the first numerical interval according to the first mapping relationship, and use the importance index as the importance index corresponding to the single first measurement point. This is only an example, and the method described below can also be used to determine the importance index, which is not limited in the embodiments of the present disclosure.

[0095] In the disclosed embodiment, the first measurement data and the first simulation data corresponding to a single first measurement point can be used to perform a difference operation, and the obtained difference is used as the first difference corresponding to the single first measurement point. The first difference corresponding to the first measurement data is weighted using the importance index corresponding to the first measurement data to obtain a weighted difference. The weighted differences corresponding to each first measurement data are added together, or screened, and the screened weighted differences are added together to obtain the first corrected data.

[0096] In the disclosed embodiment, the seawater between the request point and the first measurement point affects each other, and the seawater may flow between the request point and the first measurement point through different paths. The flow path has a direct impact on the wave data. Therefore, the disclosed embodiment can accurately represent the index characterizing the importance of the first difference of each first measurement point, that is, the importance index, based on the multiple paths from the request point to each of the first measurement points. The interpretability and accuracy of the importance index are improved. Moreover, the first correction data is determined jointly using each first difference and each importance index, which can more accurately represent the difference between the simulation data and the measurement data, and improve the rationality and accuracy of the first correction data.

[0097] In a possible implementation, the first measuring point includes a first buoy point, and the importance index of each of the multiple first measuring points is determined based on multiple paths from the request point to each of the first measuring points, including: determining the first shortest path from the request point to each of the first buoy points to obtain multiple first shortest paths; for each of the first buoy points, performing the following steps to obtain each of the importance indexes: determining the importance index of the single first buoy point based on the multiple first shortest paths and the first shortest path of the single first buoy point.

[0098] The device for measuring wave height data may include a buoy. Thus, the first measurement point may include a first buoy point. The first shortest path may be the shortest path among one or more paths from the request point to a single first buoy point. The degree of mutual influence of waves at two locations in the sea area is negatively correlated with the length of the path between the two locations. Thus, the first shortest path may be used to determine the importance index.

[0099] For ease of understanding, formula (1) is used to represent a method for determining the importance index of a single first buoy point.

[0100]

[0101] Among them, W i Characterizes the importance index corresponding to the i-th first buoy point. i Characterizes the length of the first shortest path from the request point to the i-th first buoy point. ∑1 / Path k In this example, there are k first shortest paths in total. The lengths of these k first shortest paths are reciprocally summed. Both i and k are positive integers, and i is not greater than k.

[0102] In addition, it is also possible to determine the second numerical interval that a single first shortest path falls into, and then based on the first mapping relationship, determine the importance index corresponding to the second numerical interval according to the first mapping relationship, and use the importance index as the importance index of the first buoy point corresponding to the first shortest path.

[0103] The importance index can characterize the importance of the first difference (the difference between the measured data and the simulated data) of each first buoy point. Then, in order to simplify the calculation, the embodiment of the present disclosure uses each first shortest path. The workload of determining each path is reduced. Since the standard of the path used is unified (for each first buoy point, the first shortest path to the request point is used), the accuracy and rationality of determining the importance index are further improved.

[0104] In a possible implementation, the first measurement point includes: a target reflection point at which the sea surface effectively reflects the microwave signal, the first measurement data includes: target remote sensing inversion data obtained by inverting the wave height of the target reflection point based on the reflection of the microwave signal, and determining the importance index of each of the multiple first measurement points based on the multiple paths from the request point to each of the first measurement points, including: screening the reflection points that reflect the microwave signal according to spatial conditions to obtain multiple first reflection points; screening the remote sensing inversion data corresponding to the multiple first reflection points according to numerical conditions to obtain multiple target remote sensing inversion data and the target reflection point corresponding to each of the target remote sensing inversion data; determining the second shortest path from the request point to each of the target reflection points to obtain multiple second shortest paths; performing the following steps for each of the target reflection points to obtain each of the importance indexes: determining the importance index of the single target reflection point based on the multiple second shortest paths and the second shortest path of the single target reflection point.

[0105] Satellites can be equipped with radar systems that can send microwave signals to the surface of the earth (e.g., the sea surface). The microwave signals reflected from the surface of the earth can be used to determine the distance between the surface of the earth and the satellite. This distance can reflect the height change of the surface of the earth. Therefore, based on the microwave signals reflected back to the satellite, the wave height data of the reflection point can be determined by inversion, that is, the remote sensing inversion data corresponding to the reflection point.

[0106] The device for measuring wave height data may include a satellite and a device carried by the satellite. In the embodiment of the present disclosure, the first measurement point may include a target reflection point; and the measurement data may be target remote sensing inversion data corresponding to the target reflection point.

[0107] Spatial conditions can be used to limit the sea area where the target reflection point is located. For example, the spatial condition can be that the reflection point belonging to the deep sea area among the reflection points is used as the first reflection point. Another example is that the spatial condition can be to exclude the reflection points within the third distance from the coast and use the remaining reflection points as the first reflection point. The third distance can be determined according to actual needs. Spatial conditions are used to reduce the negative impact of factors such as terrain and land on the accuracy of remote sensing inversion data.

[0108] In addition, experiments have shown that under the influence of disastrous weather systems (such as typhoons), the accuracy of wave height data obtained through numerical simulation is significantly lower than the general level. Since disastrous weather systems will increase wave heights, remote sensing inversion data with wave heights that meet numerical conditions may be wave height data in disastrous weather systems and can be excluded; thus, the first reflection points corresponding to these excluded remote sensing inversion data are also excluded, and the remaining reflection points are used as target reflection points.

[0109] The numerical condition can be: excluding remote sensing inversion data greater than the first wave height threshold, or excluding remote sensing inversion data that does not fall into the first wave height threshold interval. The first wave height threshold and the first wave height threshold interval can be set as needed. For example: the first wave height threshold is 4 meters. The first wave height threshold interval is (1,4], in meters. Numerical conditions are used to reduce the negative impact of disastrous weather systems on the accuracy of remote sensing inversion data.

[0110] By using spatial conditions and numerical conditions to screen reflection points, the target reflection point can be obtained. The second shortest path can be the shortest path among one or more paths from the request point to a single target reflection point. The degree of mutual influence of waves at two locations in the sea area is negatively correlated with the length of the path between the two locations. Therefore, the second shortest path can be used to determine the importance index.

[0111] Exemplarily, the importance index may be determined using formula (2).

[0112]

[0113] W p Characterizes the importance index corresponding to the p-th target reflection point. p Characterizes the length of the second shortest path from the request point to p target reflection points. ∑1 / Path t In this example, there are t second shortest paths in total. The lengths of the second shortest paths are reciprocally summed. Both p and t are positive integers, and p is not greater than t.

[0114] In addition, the third numerical interval into which a single second shortest path falls can also be determined, and then based on the first mapping relationship, the importance index corresponding to the third numerical interval can be determined according to the first mapping relationship, and the importance index can be used as the importance index of the target reflection point corresponding to the second shortest path.

[0115] In the embodiment of the present disclosure, in the sea area where no buoys are deployed, satellites can be used to measure wave height data, and importance indicators corresponding to target inversion data can be obtained, thereby improving the applicability of the method of the present disclosure.

[0116] In a possible implementation, the determining of the spatial correlation of the wave data in the spatial dimension based on the historical measurement time series and the multiple historical simulation time series includes: filtering the data in the historical measurement time series according to the wave level to obtain a first sub-time series corresponding to each wave level; step 1, for each moment in a single first sub-time series, extracting the simulated data at each moment from each of the historical simulation time series to obtain multiple second sub-time series; step 2, performing correlation detection on the single first sub-time series and each of the second sub-time series to obtain multiple correlation indicators; step 3, based on each of the correlation indicators, determining a strongly correlated second sub-time series that is mutually associated with the second measurement point, and using the grid corresponding to the strongly correlated second sub-time series as the selected grid of the wave level corresponding to the single first sub-time series; for each of the first sub-time series, executing steps 1 to 3 to obtain the selected grid of each of the wave levels, and using the spatial position relationship between the second measurement point and the selected grid of each of the wave levels as the spatial correlation.

[0117] By dividing the waves according to the wave height value, multiple wave grades can be obtained. For example, the wave grades may include: light waves, medium waves, large waves, huge waves, etc. In one example, the wave grades may be conventional grades. In another example, the wave grades may merge and re-divide the conventional grades, for example, the wave grades include medium waves and below, medium waves to large waves, and large waves and above. The embodiments of the present disclosure do not limit the specific form of the wave grades.

[0118] Each wave level may correspond to a wave height value interval. For a single wave level, data (measurement data and corresponding measurement time) whose values ​​conform to the single wave level may be extracted from the historical measurement time series to obtain a first time subsequence corresponding to the wave level. The historical measurement time series may be split into first sub-time series. A single wave level may correspond to a first sub-time series.

[0119] For a single first sub-time series, a second sub-time series can be extracted from a single historical simulation time series according to each moment of the first sub-time series. Since there are multiple historical simulation time series, a single first sub-time series can correspond to multiple second sub-time series. The first sub-time series can be subjected to correlation detection with each second sub-time series respectively to obtain multiple correlation indicators. The correlation indicator can represent the degree of correlation between the first sub-time series and the single second sub-time series. The correlation indicator is positively correlated with the degree of correlation. For example: the correlation indicator can be the Pearson correlation coefficient, the Spearman rank correlation coefficient, the determination coefficient, etc. The disclosed embodiment does not limit the specific forms of correlation detection and correlation indicators.

[0120] A single second sub-time series may correspond to a correlation index. When the correlation index of the second sub-time series is greater than the correlation index threshold, it indicates that the second sub-time series is strongly correlated with the first sub-time series. For ease of description, the second sub-time series whose correlation index is greater than the correlation index threshold is named a strongly correlated second sub-time series.

[0121] As mentioned above, a single peripheral grid may correspond to a historical simulation time series. Therefore, a single second sub-time series may correspond to a peripheral grid. The selected grid for a single wave level may be: the grid corresponding to the second sub-time series that is strongly related to the first sub-time series corresponding to the single wave level. Each first sub-time series (wave level) may be determined to be associated with a set of selected grids, i.e., a selected grid for each wave level may be determined.

[0122] For a single wave level, there is a set of spatial position relationships between the grid where the second measurement point is located and the selected grid of the wave level. In the case of multiple wave levels, there may be multiple sets of spatial position relationships. These spatial position relationships may be collectively regarded as spatial correlation relationships. The spatial correlation relationship may be the spatial position relationship between the grid where the second measurement point is located and the selected grid under each wave level.

[0123] Under different wave levels, the area range associated with the target position (e.g., the second measurement point) in the sea area may be different. Therefore, in the embodiment of the present disclosure, the spatial correlation relationship is determined by using the correlation between the measurement data and the surrounding simulation data under different wave levels. The spatial correlation relationship can accurately and finely express the spatial position relationship of the interconnected grids under different wave levels, and also improve the accuracy of the subsequent determination of the second correction data.

[0124] In a possible implementation, the determining of multiple target grids corresponding to the request point based on the spatial correlation includes: determining a first wave height level corresponding to the wave height simulation data; determining the multiple target grids based on the first wave height level and the spatial correlation; the determining of second correction data characterizing the error between simulation data related in the spatial dimension based on the wave height simulation data and the multiple second simulation data includes: determining a second difference between the wave height simulation data and each of the second simulation data; and determining the second correction data based on each of the second differences.

[0125] In the disclosed embodiment, the wave height level of the wave height simulation data can be determined. For ease of description, the wave height level of the wave height simulation data of the request point is named the first wave height level. The spatial position relationship between the selected grid of the first wave height level and the second measurement point can be determined in the spatial correlation relationship. This spatial position relationship is applied to the request point, and according to the position relationship, the target grid around the request point is determined.

[0126] In the embodiment of the present disclosure, the wave height simulation data and the second simulation data of each target grid can be used to perform difference calculations respectively, and the obtained difference is used as the single second difference. A single second difference can characterize the difference between the simulation data of the request point and an adjacent position. The average value of each second difference can be used as the second correction data. It is also possible to assign weights to each second difference, for example: setting a weight according to the distance between the target grid and the request point, and taking the weighted average value of all second differences as the second correction data. The above is only an example, and the embodiment of the present disclosure is not limited to this.

[0127] In the disclosed embodiment, the spatial position relationship between the remote second measurement point and the selected grids of each wave level is applied to the request point, which improves the correlation between the determined target grid and the request point, corrects the wave height simulation data more specifically, and improves the accuracy of the second corrected data.

[0128] Figure 3 This is a schematic diagram of the structure of a data fusion device provided in an embodiment of the present disclosure. The device 20 includes:

[0129] A measuring point acquisition unit 21, used to acquire a plurality of measuring points around a request point for determining a wave height;

[0130] A first measurement data and first simulation data acquisition unit 22 is used for acquiring, when the plurality of measurement points include a plurality of first measurement points, a plurality of first measurement data obtained by measuring the wave height at each of the plurality of first measurement points, and a plurality of first simulation data obtained by numerically simulating the wave height for each of the grids where the plurality of first measurement points are located, wherein the first measurement point is a measurement point that is not more than a first distance threshold from the request point;

[0131] A first correction data determination unit 23, configured to determine first correction data representing a difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data;

[0132] The target wave height data determining unit 24 is used to correct the wave height simulation data of the request point using the first correction data to obtain the target wave height data of the request point.

[0133] In a possible implementation, the device 20 further includes:

[0134] a second measurement point time series acquisition unit, configured to acquire, when the plurality of measurement points include at least one second measurement point, a historical measurement time series obtained by measuring wave heights at the second measurement point, and a plurality of historical simulation time series obtained by numerically simulating wave heights for a plurality of surrounding grids around the second measurement point, wherein the second measurement point is farther from the request point than the first measurement point;

[0135] A spatial correlation determination unit, configured to determine the spatial correlation of the wave data in a spatial dimension based on the historical measurement time series and the plurality of historical simulation time series;

[0136] A target grid determination unit, configured to determine a plurality of target grids corresponding to the request point based on the spatial correlation relationship;

[0137] A second simulation data determining unit, configured to obtain the wave height simulation data, and perform wave height numerical simulation on the plurality of target grids to obtain a plurality of second simulation data;

[0138] A second correction data determination unit, configured to determine, based on the wave height simulation data and the plurality of second simulation data, second correction data representing errors between simulation data related in a spatial dimension;

[0139] The second target wave height data determining unit is used to correct the wave height simulation data using the second correction data to obtain the target wave height data.

[0140] In a possible implementation, the first correction data determining unit 23 is further configured to:

[0141] Determining, based on a plurality of paths from the request point to each of the first measurement points, an importance index of each of the plurality of first measurement points;

[0142] Determine a first difference between each of the first measurement data and the first simulation data corresponding to each of the first measurement data;

[0143] The first correction data is determined based on each of the first differences and each of the importance indicators.

[0144] In a possible implementation, the first measurement point includes a first buoy point, and determining the importance index of each of the plurality of first measurement points based on the plurality of paths from the request point to each of the first measurement points includes:

[0145] Determine the first shortest path from the request point to each of the first buoy points, and obtain multiple first shortest paths;

[0146] For each of the first buoy points, the following steps are performed to obtain each of the importance indicators:

[0147] Based on the multiple first shortest paths and the first shortest path of a single first buoy point, an importance index of the single first buoy point is determined.

[0148] In a possible implementation, the first measurement point includes: a target reflection point where the sea surface effectively reflects the microwave signal, the first measurement data includes: target remote sensing inversion data obtained by inverting the wave height of the target reflection point based on the microwave signal reflection, and the importance index of each of the multiple first measurement points based on the multiple paths from the request point to each of the first measurement points includes:

[0149] According to the spatial conditions, the reflection points reflecting the microwave signal are screened to obtain a plurality of first reflection points;

[0150] According to the numerical conditions, the remote sensing inversion data corresponding to the plurality of first reflection points are screened to obtain the plurality of target remote sensing inversion data and the target reflection points corresponding to the respective target remote sensing inversion data;

[0151] Determine the second shortest path from the request point to each of the target reflection points to obtain multiple second shortest paths;

[0152] The following steps are performed for each target reflection point to obtain each importance index:

[0153] Based on the multiple second shortest paths and the second shortest path of a single target reflection point, an importance index of the single target reflection point is determined.

[0154] In a possible implementation manner, the spatial correlation relationship determining unit is further configured to:

[0155] According to the wave level, the data in the historical measurement time series are screened to obtain a first sub-time series corresponding to each wave level;

[0156] Step 1, for each moment in a single first sub-time series, extract each moment and the simulation data at each moment from each of the historical simulation time series to obtain multiple second sub-time series;

[0157] Step 2, performing correlation detection on the single first sub-time series and each of the second sub-time series to obtain multiple correlation indicators;

[0158] Step 3: Based on each of the correlation indicators, determine a strongly correlated second sub-time series that is mutually associated with the second measurement point, and use the grid corresponding to the strongly correlated second sub-time series as the selected grid for the wave level corresponding to the single first sub-time series;

[0159] For each of the first sub-time series, execute steps 1 to 3 to obtain the selected grid for each of the wave levels, and use the spatial position relationship between the second measurement point and the selected grid for each of the wave levels as the spatial correlation relationship.

[0160] In a possible implementation manner, the target grid determination unit is further configured to:

[0161] Determining a first wave height level corresponding to the wave height simulation data;

[0162] Determining the plurality of target grids based on the first wave height level and the spatial correlation relationship;

[0163] The second correction data determination unit is further used to:

[0164] determining a second difference between the wave height simulation data and each of the second simulation data;

[0165] Based on each of the second differences, the second correction data are determined.

[0166] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0167] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0168] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0169] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0170] Figure 4The electronic device 1900 is a schematic diagram of the structure of the electronic device for English data fusion provided by the embodiment of the present disclosure. For example, the electronic device 1900 can be provided as a server or a terminal device. Figure 4 , the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions executable by the processing component 1922, such as an application. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0171] The electronic device 1900 may also include a power supply component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). The electronic device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2003. TM , Mac OS X TM , Unix TM ,Linux TM , FreeBSD TM or similar.

[0172] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the electronic device 1900 to perform the above method.

[0173] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0174] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0175] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0176] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0177] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0178] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0179] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0180] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0181] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A data fusion method, characterized in that: include: Obtain multiple measurement points around the request point for determining the wave height; In the case where the multiple measurement points include multiple first measurement points, obtaining multiple first measurement data obtained by measuring the wave height at each of the multiple first measurement points, and multiple first simulation data obtained by numerically simulating the wave height for each grid where the multiple first measurement points are located, wherein the first measurement point is a measurement point that is no more than a first distance threshold from the request point; Determining first correction data representing a difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data; The wave height simulation data of the request point is corrected using the first correction data to obtain the target wave height data of the request point.

2. The method according to claim 1, characterized in that: The method further comprises: When the plurality of measurement points include at least one second measurement point, obtaining a historical measurement time series obtained by measuring the wave height at the second measurement point, and a plurality of historical simulation time series obtained by numerically simulating the wave height for a plurality of surrounding grids around the second measurement point, wherein the second measurement point is farther from the request point than the first measurement point; Determining the spatial correlation of the ocean wave data in a spatial dimension based on the historical measurement time series and the plurality of historical simulation time series; Based on the spatial correlation relationship, determining a plurality of target grids corresponding to the request point; Acquiring the wave height simulation data, and performing wave height numerical simulation on the plurality of target grids to obtain a plurality of second simulation data; Determining second correction data representing errors between simulation data related in a spatial dimension based on the wave height simulation data and the plurality of second simulation data; The wave height simulation data is corrected using the second correction data to obtain the target wave height data.

3. The method according to claim 1, characterized in that: The determining, based on each of the first measurement data and each of the first simulation data, first correction data characterizing a difference between the simulation data and the measurement data comprises: Determining, based on a plurality of paths from the request point to each of the first measurement points, an importance index of each of the plurality of first measurement points; Determine a first difference between each of the first measurement data and the first simulation data corresponding to each of the first measurement data; The first correction data is determined based on each of the first differences and each of the importance indicators.

4. The method according to claim 3, characterized in that The first measurement point includes a first buoy point, and determining the importance index of each of the plurality of first measurement points based on the plurality of paths from the request point to each of the first measurement points includes: Determine the first shortest path from the request point to each of the first buoy points, and obtain multiple first shortest paths; For each of the first buoy points, the following steps are performed to obtain each of the importance indicators: Based on the multiple first shortest paths and the first shortest path of a single first buoy point, an importance index of the single first buoy point is determined.

5. The method according to claim 3, characterized in that: The first measurement point includes: a target reflection point where the sea surface effectively reflects the microwave signal, the first measurement data includes: target remote sensing inversion data obtained by inverting the wave height of the target reflection point based on the microwave signal reflection, and the importance index of each of the multiple first measurement points is determined based on multiple paths from the request point to each of the first measurement points, including: According to the spatial conditions, the reflection points reflecting the microwave signal are screened to obtain a plurality of first reflection points; According to the numerical conditions, the remote sensing inversion data corresponding to the plurality of first reflection points are screened to obtain the plurality of target remote sensing inversion data and the target reflection points corresponding to the respective target remote sensing inversion data; Determine the second shortest path from the request point to each of the target reflection points to obtain multiple second shortest paths; The following steps are performed for each target reflection point to obtain each importance index: Based on the multiple second shortest paths and the second shortest path of a single target reflection point, an importance index of the single target reflection point is determined.

6. The method according to claim 2, characterized in that The determining of the spatial correlation of the wave data in the spatial dimension based on the historical measurement time series and the plurality of historical simulation time series comprises: According to the wave level, the data in the historical measurement time series are screened to obtain a first sub-time series corresponding to each wave level; Step 1, for each moment in a single first sub-time series, extract each moment and the simulation data at each moment from each of the historical simulation time series to obtain multiple second sub-time series; Step 2, performing correlation detection on the single first sub-time series and each of the second sub-time series to obtain multiple correlation indicators; Step 3: Based on each of the correlation indicators, determine a strongly correlated second sub-time series that is mutually associated with the second measurement point, and use the grid corresponding to the strongly correlated second sub-time series as the selected grid for the wave level corresponding to the single first sub-time series; For each of the first sub-time series, execute steps 1 to 3 to obtain the selected grid for each of the wave levels, and use the spatial position relationship between the second measurement point and the selected grid for each of the wave levels as the spatial correlation relationship.

7. The method according to claim 2, characterized in that: The step of determining a plurality of target grids corresponding to the request point based on the spatial correlation relationship includes: Determining a first wave height level corresponding to the wave height simulation data; Determining the plurality of target grids based on the first wave height level and the spatial correlation relationship; The step of determining second correction data representing errors between simulation data related in a spatial dimension based on the wave height simulation data and the plurality of second simulation data comprises: determining a second difference between the wave height simulation data and each of the second simulation data; Based on each of the second differences, the second correction data are determined.

8. A data fusion device, characterized in that: include: A measuring point acquisition unit, used to acquire a plurality of measuring points around a request point for determining a wave height; A first measurement data and first simulation data acquisition unit, configured to acquire, when the plurality of measurement points include a plurality of first measurement points, a plurality of first measurement data obtained by measuring the wave height at each of the plurality of first measurement points, and a plurality of first simulation data obtained by numerically simulating the wave height for each of the grids where the plurality of first measurement points are located, wherein the first measurement point is a measurement point that is not more than a first distance threshold from the request point; A first correction data determination unit, configured to determine first correction data representing a difference between simulation data and measurement data based on each of the first measurement data and each of the first simulation data; The first target wave height data determining unit is used to correct the wave height simulation data of the request point using the first correction data to obtain the target wave height data of the request point.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 7 when executing the instructions stored in the memory.

10. A non-volatile computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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