A backscattering data fusion method and device, electronic equipment and storage medium

Abstract

The application discloses a backscattering data fusion method and device, electronic equipment and storage medium, and the method comprises the steps of determining a first similar result based on first backscattering data and second backscattering data; in the case that the first similar result meets a first preset requirement, determining a second similar result based on the backscattering data corresponding to the overlapping area between the first backscattering data and the second backscattering data; in the case that the second similar result and the first similar result meet a second preset requirement, determining a first reference point based on the global data distribution result of the first backscattering data and a second reference point based on the global data distribution result of the second backscattering data; and fusing the backscattering data at the same position point in the first backscattering data and the second backscattering data based on the first reference point and the second reference point. The scheme can fuse the backscattering data obtained by different voyage tasks.

Description

Technical Field

[0001] This invention relates to the field of marine surveying and mapping technology, and in particular to a backscatter data fusion method, apparatus, electronic device and storage medium. Background Technology

[0002] Multibeam bathymetry systems play a crucial role in marine mapping and underwater topographic surveying, providing high-resolution underwater topographic data. However, the acquisition of multibeam backscatter data is often affected by various factors such as the emission intensity of the acquisition instrument, the acquisition direction, and environmental variations. This leads to discrepancies in the numerical results obtained from multiple expeditions to the same area, making data standardization and comparability difficult, and hindering the comprehensive application of multibeam backscatter data acquired from different expeditions. Summary of the Invention

[0003] This invention provides a backscatter data fusion method, apparatus, electronic device, and storage medium, which can fuse backscatter data obtained from different missions and make the fused data have high accuracy both overall and locally.

[0004] In a first aspect, the present invention provides a backscattering data fusion method, comprising: Based on the first backscattered data and the second backscattered data, a first similarity result is determined; wherein the first backscattered data and the second backscattered data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscattered data and the second backscattered data; the first similarity result is used to indicate the degree of similarity between the global data distribution results of the first backscattered data and the global data distribution results of the second backscattered data; If the first similarity result meets the first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data. If the second similarity result and the first similarity result meet the second preset requirements, a first reference point is determined based on the global data distribution result of the first backscattered data, and a second reference point is determined based on the global data distribution result of the second backscattered data. Based on the first reference point and the second reference point, the backscattered data at the same location point in the first backscattered data and the second backscattered data are fused.

[0005] Secondly, the present invention also provides a backscattered data fusion apparatus, comprising: The first similarity result determination module is used to determine a first similarity result based on first backscattered data and second backscattered data; wherein the first backscattered data and the second backscattered data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscattered data and the second backscattered data; the first similarity result is used to indicate the degree of similarity between the global data distribution result of the first backscattered data and the global data distribution result of the second backscattered data; The second similarity result determination module is used to determine a second similarity result based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data, when the first similarity result meets the first preset requirements. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data. The reference point determination module is used to determine a first reference point based on the global data distribution result of the first backscattered data, and to determine a second reference point based on the global data distribution result of the second backscattered data, provided that the second similarity result and the first similarity result meet the second preset requirements. The data fusion module is used to fuse backscattered data from the first backscattered data and the second backscattered data at the same location point based on the first reference point and the second reference point.

[0006] Thirdly, this invention also provides an electronic device, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the backscatter data fusion method as provided in any embodiment of the present invention.

[0007] Fourthly, embodiments of the present invention also provide a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the backscattered data fusion method provided in any embodiment of the present invention.

[0008] The technical solution of this invention determines a first similarity result using first backscattered data and second backscattered data. The first and second backscattered data are data measured during different voyages targeting the same sea area, and the measurement areas corresponding to the first and second backscattered data overlap. This first similarity result indicates the degree of similarity between the global data distribution of the first and second backscattered data, thereby identifying differences in the overall data distribution / trend of the backscattered data from the two voyages. Then, if the first similarity result meets a first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first and second backscattered data. This second similarity result indicates the degree of similarity between the local data distribution of the first and second backscattered data, thus enabling precise comparison of the data in the overlapping area between the two voyages and comparing their local data distributions. This allows for the capture of changes in seabed reflectivity that may be caused by sediment migration, biological activity, or subtle topographical changes. Next, if the second similarity result and the first similarity result meet the second preset requirements, a first reference point is determined based on the global data distribution result of the first backscattered data, and a second reference point is determined based on the global data distribution result of the second backscattered data. Based on the first and second reference points, backscattered data at the same location points in the first and second backscattered data are fused, thus making the data measured in the two expeditions comparable and enabling data fusion. This scheme can analyze backscattered data collected from different expeditions based on both the "similarity of global data distribution" and the "similarity of local data distribution," accurately identifying and correcting systematic biases in the backscattered data. This process brings the first and second backscattered data to the same benchmark, making previously difficult-to-compare backscattered data comparable. This achieves the fusion of backscattered data from different expeditions, resulting in high accuracy in both the overall and local aspects of the fused data. This provides more reliable basic data support for subsequent applications such as seabed sediment classification and geomorphological analysis.

[0009] The above description of the invention is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0010] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0011] Figure 1 This is a flowchart illustrating a backscattered data fusion method provided in an embodiment of the present invention. Figure 2 This is a flowchart illustrating another backscattered data fusion method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the effect of a first data distribution map provided in an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the effect of a second data distribution map provided in an embodiment of the present invention; Figure 5 This is a schematic diagram illustrating the effect of a third data distribution map provided in an embodiment of the present invention; Figure 6 This is a schematic diagram illustrating the effect of a fourth data distribution map provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of a backscatter data fusion device provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of an electronic device for implementing a backscattered data fusion method according to an embodiment of the present invention. Detailed Implementation

[0012] Embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the invention.

[0013] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0014] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0015] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0016] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0017] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0018] Figure 1 This is a flowchart illustrating a backscattering data fusion method provided in an embodiment of the present invention. This embodiment is applicable to the fusion of backscattering data obtained from measurements of different missions. The method can be executed by a backscattering data fusion device, which can be implemented in software and / or hardware and is generally integrated into any electronic device with network communication capabilities, such as a mobile terminal, PC, or server. Figure 1 As shown, the backscattered data fusion method of this invention may include the following process: S110. Based on the first backscatter data and the second backscatter data, determine the first similarity result; wherein, the first backscatter data and the second backscatter data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscatter data and the second backscatter data; the first similarity result is used to indicate the degree of similarity between the global data distribution result of the first backscatter data and the global data distribution result of the second backscatter data.

[0019] Backscatter data refers to the intensity information of sound waves that are scattered back to the receiver after impacting the seabed in a non-specular reflection manner. Backscatter data can contain backscatter intensities collected from multiple locations. In this embodiment, backscatter data can be understood as a data set composed of multiple backscatter intensity values, each of which is associated with a corresponding acquisition location. For example, the process of obtaining backscatter data can be as follows: When it is necessary to measure a target sea area A, the survey vessel will sail to the target sea area A. The survey vessel can transmit sound waves to the seabed of the target sea area A through a beam echo sounder and receive the reflected signal strength. When measuring the specific intensity value reflected back at various locations in the target sea area A, the sea area A can be divided into 5000 measurement squares (for example, each measurement square is 2m×2m in size), and the specific received signal strength value can be detected in each measurement square. Then, 5000 backscatter intensity values ​​can be obtained, and each backscatter intensity value is associated with a corresponding acquisition location point (the acquisition location point can be represented by the center location point of each measurement square). These 5000 backscatter intensity values ​​constitute multibeam backscatter data.

[0020] Accordingly, in this embodiment, the first backscattered data and the second backscattered data are data obtained from different voyages targeting the same sea area, and there is overlap between the measurement areas corresponding to the first backscattered data and the second backscattered data. It is understood that in actual measurement processes, even when measuring the same target sea area, different backscattered data may be obtained due to different voyages. These different voyages may differ in at least one of the following aspects: the type of measurement equipment configured, the measurement cycle, the configuration parameters of the acquisition instrument, the acquisition direction, and the specific sea state parameters during the voyage. The configuration parameters of the acquisition instrument include at least one of the following: the type of sound source signal, the signal transmission intensity, and the signal gain control parameters. The acquisition direction is the heading of the measurement vessel. The specific sea state parameters during the voyage include at least one of the following: water body parameters, seabed sediment information, and weather parameters. Furthermore, although measurements are conducted on the same target sea area, differences in the actual execution of each voyage can lead to variations in the actual measurement areas. These variations may overlap and differ in some areas. For example, if two voyages both measure target sea area A, the measurement area corresponding to the first backscatter data obtained from one voyage might be the total area consisting of "a+b+c+d," while the measurement area corresponding to the second backscatter data obtained from the other voyage might be the total area consisting of "b+c+d+e." This demonstrates an overlap between the two measurement areas.

[0021] It should be noted that due to the different specific voyage missions, and especially due to the influence of various factors such as the emission intensity of the acquisition instrument, the acquisition direction, and environmental changes, the specific numerical results of the first and second backscatter data obtained from multiple measurements of the same sea area often differ. This makes the standardization and comparability of these two data sets difficult, hindering direct stitching or fusion. The solution in this embodiment addresses this problem by fusing backscatter data obtained from measurements of different voyage missions.

[0022] It is understandable that for the same target sea area, the seabed sediment at different locations within that area may differ (meaning the hardness and / or roughness of the seabed sediment varies). Different seabed sediments will exhibit different backscattering characteristics for sound waves, resulting in different backscattering intensities. For example, in target sea area A (which can correspond to 5000 measurement squares), only sub-region a (which can correspond to 1000 measurement squares) has a seabed sediment containing a large amount of rock and gravel, while the remaining sub-regions are composed of fine-grained sediments such as silt. The differences in seabed sediment between these sub-regions will directly affect the backscattering intensities collected in each sub-region, particularly demonstrating a clear contrast in the relative strength of the backscattering intensities between these sub-regions. For example, by using the backscattering intensity data corresponding to the entire target sea area A, it can be determined that the backscattering intensity value of sub-region a is the highest in the entire region, far exceeding that of other sub-regions, and this relatively high intensity value accounts for 25% of the points in the entire region. In this embodiment, however, global data distribution results are used to characterize this, indicating the backscattering intensity distribution in the entire measurement area. For example, the global data distribution results can indicate the concentration trend, dispersion, and intensity contrast of backscattering intensity in the entire measurement area. That is, the global data distribution results of the first backscattering data can indicate the backscattering intensity distribution in the measurement area corresponding to the first backscattering data. The global data distribution results of the second backscattering data can indicate the backscattering intensity distribution in the measurement area corresponding to the second backscattering data.

[0023] Specifically, after obtaining the first and second backscattered data, the global data distribution results corresponding to each can be determined. For example, to determine the global data distribution result of the first backscattered data, a statistical chart can be drawn based on the backscattered intensity values ​​contained therein to obtain the global data distribution result; alternatively, a distribution fitting relationship can be determined based on the backscattered intensity values ​​to obtain the global data distribution result. It is understandable that since the first and second backscattered data are measured for the same target sea area, the relative strength of the backscattered intensities at different locations on the seabed of this target sea area remains essentially constant. For example, continuing with the example described earlier, in the various sub-regions corresponding to target sea area A, the backscattered intensity value of sub-region a is the highest in the entire region, far exceeding that of other sub-regions. Therefore, regardless of the type of cruise mission used to measure the target sea area A, the backscatter intensity data obtained from each cruise mission will theoretically exhibit a strong-weak contrast / data distribution relationship, such as "the intensity of sub-region a is much greater than the intensity of other sub-regions." Consequently, a similarity calculation can be performed based on the global data distribution results of the first and second backscatter data to determine the first similarity result between them.

[0024] S120. If the first similarity result meets the first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data.

[0025] The first preset requirement is used to indicate that the similarity between the global data distribution result of the first backscattered data and the global data distribution result of the second backscattered data is greater than a first similarity threshold. The first similarity threshold can be set differently based on actual needs.

[0026] The overlapping region refers to the area where the measurement areas of the first backscattered data and the second backscattered data overlap. Simply put, it's the overlapping area between the actual measurement areas of two missions. For example, continuing with the previous example, if the actual measurement area corresponding to the first backscattered data obtained in one mission is the total area composed of "a+b+c+d", and the actual measurement area corresponding to the second backscattered data obtained in another mission is the total area composed of "b+c+d+e", then the overlapping region is the area composed of "b+c+d".

[0027] Correspondingly, the local data distribution results are used to indicate the distribution of backscattering intensity in the overlapping region. For example, the local data distribution results can indicate details such as the concentration trend, dispersion, and intensity contrast of backscattering intensity in the overlapping region.

[0028] Specifically, after obtaining the first similarity result, it can be analyzed to determine whether it meets the first preset requirement. If the first similarity result meets the first preset requirement, the overlapping area between the measurement area of ​​the first backscattered data and the measurement area of ​​the second backscattered data can be determined first, and then the specific backscattered data of each data point within this overlapping area can be determined. For example, after determining that the overlapping area is the region composed of "b+c+d", multiple backscattered intensities belonging to the "b+c+d" region can be determined from the first backscattered data based on the location information corresponding to the overlapping area (which can form a dataset X1); similarly, multiple backscattered intensities belonging to the "b+c+d" region can also be determined from the second backscattered data (which can form a dataset X2). Furthermore, based on the backscattered data of each data point within this overlapping area, the local data distribution results of each data point can be calculated. For example, the local data distribution result can be determined based on the dataset X1 corresponding to the first backscattered data, and the local data distribution result can be determined based on the dataset X2 corresponding to the second backscattered data. Subsequently, similarity calculations can be performed based on the local data distribution results of the two to determine the second similarity result between them. This second similarity result can indicate the degree of local similarity between the two in terms of data distribution, which is essentially the degree of similarity between the backscattered data in the overlapping area of ​​the two.

[0029] S130. If the second similarity result and the first similarity result meet the second preset requirements, determine the first reference point based on the global data distribution result of the first backscattered data, and determine the second reference point based on the global data distribution result of the second backscattered data.

[0030] The second preset requirement indicates that the difference between the second similarity result and the first similarity result is less than a difference threshold. This difference threshold can be set differently based on actual needs. In other words, if the difference between the second similarity result and the first similarity result is less than the difference threshold, it means that the second preset requirement is met. Essentially, it indicates that the second similarity result and the first similarity result are basically the same, or have little change. The actual meaning is that the "similarity of the global data distribution results" and the "similarity of the local data distribution results" between the first backscattered data and the second backscattered data are consistent, or have little difference. This means that the comparable data portions have been identified, and the first and second backscattered data can then be processed to bring them to the same baseline, making the previously difficult-to-compare backscattered data comparable.

[0031] The first reference point can be understood as a special marker point determined based on the global data distribution result of the first backscattered data. In this embodiment, the first reference point can be preferentially selected as the point with the highest probability distribution density in the global data distribution result of the first backscattered data. Similarly, the second reference point can be understood as a special marker point determined based on the global data distribution result of the second backscattered data, and the second reference point can also be preferentially selected as the point with the highest probability distribution density in the global data distribution result of the second backscattered data. It should be noted that in this embodiment, the selection criteria for determining the first and second reference points must be consistent; for example, both should simultaneously select the point with the highest probability distribution density.

[0032] Specifically, after determining the first and second similarity results, these two results can be analyzed and judged to determine whether they meet the second preset requirements. If they meet the second preset requirements, the first reference point can be determined based on the global data distribution of the first backscattered data, and the second reference point can be determined based on the global data distribution of the second backscattered data. The obtained first and second reference points essentially represent the most concentrated numerical points in the first and second backscattered data, respectively. These numerical points theoretically correspond to the same geographical location (i.e., the same location information) in the target sea area.

[0033] S140. Based on the first reference point and the second reference point, the backscattered data at the same location point in the first backscattered data and the second backscattered data are fused.

[0034] Specifically, by using the first and second reference points, it is possible to determine which data in the first and second backscattered data correspond to the same location information. This is equivalent to determining the positional mapping relationship between the first and second backscattered data, which allows for the further fusion of backscattered data at the same location points.

[0035] The technical solution of this invention determines a first similarity result using first backscattered data and second backscattered data. The first and second backscattered data are data measured during different voyages targeting the same sea area, and the measurement areas corresponding to the first and second backscattered data overlap. This first similarity result indicates the degree of similarity between the global data distribution of the first and second backscattered data, thereby identifying differences in the overall data distribution / trend of the backscattered data from the two voyages. Then, if the first similarity result meets a first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first and second backscattered data. This second similarity result indicates the degree of similarity between the local data distribution of the first and second backscattered data, thus enabling precise comparison of the data in the overlapping area between the two voyages and comparing their local data distributions. This allows for the capture of changes in seabed reflectivity that may be caused by sediment migration, biological activity, or subtle topographical changes. Next, if the second similarity result and the first similarity result meet the second preset requirements, a first reference point is determined based on the global data distribution result of the first backscattered data, and a second reference point is determined based on the global data distribution result of the second backscattered data. Based on the first and second reference points, backscattered data at the same location points in the first and second backscattered data are fused, thus making the data measured in the two expeditions comparable and enabling data fusion. This scheme can analyze backscattered data collected from different expeditions based on both the "similarity of global data distribution" and the "similarity of local data distribution," accurately identifying and correcting systematic biases in the backscattered data. This process brings the first and second backscattered data to the same benchmark, making previously difficult-to-compare backscattered data comparable. This achieves the fusion of backscattered data from different expeditions, resulting in high accuracy in both the overall and local aspects of the fused data. This provides more reliable basic data support for subsequent applications such as seabed sediment classification and geomorphological analysis.

[0036] Figure 2 This is a flowchart illustrating another backscattered data fusion method provided by an embodiment of the present invention. The technical solution of this embodiment further optimizes the process of fusing backscattered data from the first and second backscattered data at the same location point based on a first and a second reference point, building upon the technical solutions of the aforementioned embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. For example... Figure 2 As shown, the backscattered data fusion method of this invention may include the following process: S210. Based on the first backscatter data and the second backscatter data, determine the first similarity result; wherein the first backscatter data and the second backscatter data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscatter data and the second backscatter data; the first similarity result is used to indicate the degree of similarity between the global data distribution result of the first backscatter data and the global data distribution result of the second backscatter data.

[0037] As an optional but non-limiting implementation, determining a first similarity result based on first backscattered data and second backscattered data includes: plotting a histogram based on each backscattered intensity value contained in the first backscattered data to obtain a first data distribution map; plotting a histogram based on each backscattered intensity value contained in the second backscattered data to obtain a second data distribution map; and determining the first similarity result based on the first and second data distribution maps. Using this optional scheme, the global data distribution results of the first and second backscattered data can be characterized separately using histograms plotted based on backscattered intensity values, thereby determining the first similarity result.

[0038] Specifically, a histogram can be drawn based on the various backscattering intensity values ​​contained in the first backscattering data to obtain the first data distribution map. For example, Figure 3 This is a schematic diagram illustrating the effect of a first data distribution map provided in an embodiment of the present invention, such as... Figure 3 As shown, Figure 3 The horizontal axis represents the backscattering intensity value, and the vertical axis represents the quantity (i.e., the total number of occurrences of a specific backscattering intensity value). This first data distribution map can serve as the global data distribution result corresponding to the first backscattering data, reflecting the specific distribution of each backscattering intensity value in the overall measurement area corresponding to the first backscattering data. For example, through... Figure 3It can be seen that the distribution of backscattering intensity values ​​in the overall measurement area follows a normal distribution, and the specific backscattering intensity value corresponding to the highest peak point (i.e. the point with the highest probability distribution density) in the figure is -18.9169944.

[0039] Then, following the same principle, a histogram can be plotted based on the individual backscattering intensity values ​​contained in the second backscattering data, thus obtaining the second data distribution map. For example, Figure 4 This is a schematic diagram illustrating the effect of a second data distribution map provided in an embodiment of the present invention, such as... Figure 4 As shown, Figure 4 The horizontal axis represents the backscattering intensity value, and the vertical axis represents the quantity (i.e., the total number of occurrences of a specific intensity value). This second data distribution map can serve as the global data distribution result corresponding to the second backscattering data, reflecting the specific distribution of each backscattering intensity value in the overall measurement area corresponding to the second backscattering data. Figure 4 It can be seen that the distribution of backscattering intensity values ​​in the overall measurement area also follows a normal distribution, and the specific backscattering intensity value corresponding to the highest peak point (i.e., the point with the highest probability distribution density) in the figure is -20.7016455.

[0040] Subsequently, a similarity analysis can be performed based on the first and second data distribution maps to determine the first similarity result. For example, the curve shapes and peak values ​​presented in the first and second data distribution maps (the curves are formed by connecting the vertices of the various pillars) can be analyzed to determine the first similarity result. This allows for the analysis and determination of the overall trend of the first and second backscattered data.

[0041] As an optional but non-limiting implementation, after determining the first similarity result, the method further includes: if the first similarity result meets the first preset requirement, determining the global peak difference based on the peak value of the first data distribution map and the peak value of the second data distribution map; if the first similarity result does not meet the first preset requirement, eliminating the graphical false peaks present in the first data distribution map or the second data distribution map.

[0042] Specifically, after analyzing the similarity between the first and second data distribution maps, if their curve shapes and peak values ​​are generally similar, the obtained first similarity result meets the first preset requirement; otherwise, the obtained first similarity result does not meet the first preset requirement. Furthermore, if the first similarity result meets the first preset requirement, the global peak difference can be determined based on the peak values ​​of the first and second data distribution maps. Of course, if the first similarity result does not meet the first preset requirement, the spurious peaks in the first or second data distribution maps can be eliminated to remove systematic errors in the data measurement process of the first or second backscattered data.

[0043] S220. If the first similarity result meets the first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data.

[0044] As an optional but non-limiting implementation, the overlapping region between the first backscattered data and the second backscattered data is determined as follows: a first measurement region corresponding to the first backscattered data and a second measurement region corresponding to the second backscattered data are determined; based on the first and second measurement regions, an intersection region is determined, and this intersection region is taken as the overlapping region. Using this optional scheme, the overlapping region can be determined based on the intersection portion of the actual measurement regions between the first and second backscattered data.

[0045] The first measurement region can be understood as the actual measurement region corresponding to the first backscattered data. The second measurement region can be understood as the actual measurement region corresponding to the second backscattered data.

[0046] Specifically, based on a specific flight mission, a first measurement region corresponding to the first backscattered data and a second measurement region corresponding to the second backscattered data can be determined. Then, based on the first and second measurement regions, the intersection region between them is determined, and this intersection region is taken as the overlapping region.

[0047] As an optional but non-limiting implementation, a second similarity result is determined based on the backscattered data corresponding to the overlapping region between the first and second backscattered data. This includes: determining a third backscattered data based on the first backscattered data and the overlapping region, where the measurement region corresponding to the third backscattered data is the overlapping region; determining a fourth backscattered data based on the second backscattered data and the overlapping region, where the measurement region corresponding to the fourth backscattered data is the overlapping region; and determining the second similarity result based on the third and fourth backscattered data. Using this optional scheme, the second similarity result can be determined based on the backscattered data that the first and second backscattered data each possess in the overlapping region.

[0048] Specifically, after identifying the overlapping region, multiple backscattering intensity values ​​belonging to the acquisition point within that overlapping region can be determined from the first backscattering data based on the location information corresponding to the overlapping region. These multiple backscattering intensity values ​​that meet the requirements collectively constitute the third backscattering data, and the measurement area corresponding to this third backscattering data is essentially the overlapping region. Similarly, based on the second backscattering data and the overlapping region, a fourth backscattering data can be determined, and the measurement area corresponding to this fourth backscattering data is also essentially the overlapping region. Subsequently, a second similarity result can be determined based on the third and fourth backscattering data.

[0049] As an optional but non-limiting implementation, the second similarity result is determined based on the third and fourth backscattered data, including: plotting a histogram based on each backscattered intensity value contained in the third backscattered data to obtain a third data distribution map; plotting a histogram based on each backscattered intensity value contained in the fourth backscattered data to obtain a fourth data distribution map; and determining the second similarity result based on the third and fourth data distribution maps. Using this optional scheme, the local data distribution result of the first backscattered data can be characterized by the histogram plotted using the third backscattered intensity value, and the local data distribution result of the second backscattered data can be characterized by the histogram plotted using the fourth backscattered intensity value, thereby determining the second similarity result.

[0050] Specifically, a histogram can be created based on the various backscattering intensity values ​​contained in the third backscattering data to obtain a third data distribution map. For example, Figure 5 This is a schematic diagram illustrating the effect of a third data distribution map provided in an embodiment of the present invention, such as... Figure 5 As shown, Figure 5The horizontal axis represents the backscattering intensity value, and the vertical axis represents the quantity (that is, the total number of times a specific intensity value appears). This third data distribution map can serve as the local data distribution result corresponding to the first backscattering data, reflecting the specific distribution of each backscattering intensity value of the first backscattering data in the overlapping area.

[0051] Using the same principle, a histogram can be plotted based on the various backscattering intensity values ​​contained in the fourth backscattering data to obtain the fourth data distribution map. For example, Figure 6 This is a schematic diagram illustrating the effect of a fourth data distribution map provided in an embodiment of the present invention, such as... Figure 6 As shown, Figure 6 The horizontal axis represents the backscattering intensity value, and the vertical axis represents the quantity (that is, the total number of times a specific intensity value appears). This fourth data distribution map can serve as the local data distribution result corresponding to the second backscattering data, reflecting the specific distribution of each backscattering intensity value of the second backscattering data in the overlapping area.

[0052] Subsequently, a similarity analysis can be performed based on the third and fourth data distribution maps to determine the second similarity result. For a detailed explanation of the calculation principles, please refer to the previous section on determining the first similarity result; it will not be elaborated upon here.

[0053] S230, if the second similarity result and the first similarity result meet the second preset requirements, determine the first reference point based on the global data distribution result of the first backscattered data, and determine the second reference point based on the global data distribution result of the second backscattered data.

[0054] Specifically, if the second similarity result and the first similarity result meet the second preset requirements, in this embodiment, the peak point (i.e., the point with the highest frequency of occurrence / the point with the highest probability distribution density) in the first data distribution map can be used as the first reference point. Similarly, the peak point (i.e., the point with the highest frequency of occurrence / the point with the highest probability distribution density) in the second data distribution map can be used as the second reference point.

[0055] S240. Determine the deviation value between the first reference point and the second reference point, and determine the backscatter data to be adjusted and the reference backscatter data from the first backscatter data and the second backscatter data.

[0056] The deviation value refers to the difference between the first reference point and the second reference point at specific backscattering intensity values. Backscattering data to be adjusted can be understood as data whose backscattering intensity value (i.e., the specific intensity value) needs adjustment. Conversely, reference backscattering data can be understood as data that does not require adjustment of its backscattering intensity value.

[0057] Specifically, after determining the first and second reference points, the specific backscattering intensity values ​​corresponding to the first and second reference points can be determined. Subtracting these two values ​​yields the deviation value. Further, backscattering data to be adjusted and reference backscattering data can be determined from the first and second backscattering data. The backscattering data to be adjusted can be either the first or second backscattering data, and the reference backscattering data can also be either the first or second backscattering data. Furthermore, the backscattering data to be adjusted and the reference backscattering data are different from each other. That is, one of the two backscattering data is selected as the backscattering data to be adjusted, and the other is used as the reference backscattering data. Preferably, the data with lower quality can be used as the backscattering data to be adjusted, and the data with higher quality can be used as the reference backscattering data. The methods for judging data quality can be customized based on actual needs, and this embodiment will not limit them in detail.

[0058] S250. Based on the deviation value, adjust each backscattering intensity value contained in the backscattering data to be adjusted to obtain the registered backscattering data.

[0059] Understandably, since the first reference point originates from the global data distribution of the first backscattered data and the second reference point originates from the global data distribution of the second backscattered data, this is equivalent to identifying which data in the first and second backscattered data correspond to the same location information. Based on this, the determined deviation value is equivalent to determining the numerical difference in specific intensity values ​​between the first and second backscattered data. Therefore, adjustments can be made to the various backscattered intensity values ​​included in the backscattered data to be adjusted based on the deviation value, thus obtaining the registered backscattered data. Through this processing, systematic deviations in the backscattered data can be accurately identified and corrected, bringing the first and second backscattered data to the same reference, thus ensuring the consistency and uniformity of their intensity levels (the intensity standards are consistent), making previously difficult-to-compare backscattered data comparable.

[0060] For example, with Figure 3 and Figure 4 For example, suppose Figure 3 The first backscattering data is used as the reference backscattering data. Figure 4 The second backscattering data is used as the backscattering data to be adjusted, so it can be... Figure 4The second backscattering data shown is subjected to a global translation process to align the peak points of the two curves (i.e., align the first reference point and the second reference point). Based on the second backscattering data after this global translation process, the registration backscattering data can be determined. It is evident that after this global translation process, the first and second backscattering data are processed onto the same reference, making the previously difficult-to-compare backscattering data comparable.

[0061] S260. The registered backscattered data is fused with the reference backscattered data so that backscattered data at the same location points are fused.

[0062] Specifically, the registered backscattered data and the reference backscattered data obtained at this point already share the same standard, and the positional correspondence between the various backscattered intensity values ​​in both is clear. Therefore, the registered backscattered data and the reference backscattered data can be fused, allowing backscattered data at the same location points to be integrated. This achieves a natural and smooth transition, completely avoiding the drawbacks of "cliff-like stitching" and the obvious "gap" or "steps" that may appear at the data connection points that can result from traditional simple stitching methods. The fused backscattered dataset exhibits a high degree of continuity both visually and numerically, greatly improving the quality and usability of the final data product and providing users with seamless, high-quality comprehensive seabed information.

[0063] Optionally, when fusing backscattered data at the same location, for a single location, the average value of the backscattered intensity values ​​corresponding to that location in the registered backscattered data and the reference backscattered data can be taken, and the resulting average value is the fusion result for that location.

[0064] Optionally, when fusing backscattered data at the same location point, for a single location point, the following steps can be taken: determine the region to be fused corresponding to the location point (for example, a 3×3 grid region or a 9×9 grid region near the location point), and determine multiple backscattered intensity values ​​corresponding to the region to be fused in the registered backscattered data and the reference backscattered data, respectively. Then, average these multiple determined backscattered intensity values, and the average result can be used as the fusion result for that location point.

[0065] The technical solution of this invention determines a first similarity result using first backscattered data and second backscattered data. The first and second backscattered data are data measured during different voyages targeting the same sea area, and the measurement areas corresponding to the first and second backscattered data overlap. This first similarity result indicates the degree of similarity between the global data distribution of the first and second backscattered data, thereby identifying differences in the overall data distribution / trend of the backscattered data from the two voyages. Then, if the first similarity result meets a first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first and second backscattered data. This second similarity result indicates the degree of similarity between the local data distribution of the first and second backscattered data, thus enabling precise comparison of the data in the overlapping area between the two voyages and comparing their local data distributions. This allows for the capture of changes in seabed reflectivity that may be caused by sediment migration, biological activity, or subtle topographical changes. Next, if the second similarity result and the first similarity result meet the second preset requirements, a first reference point is determined based on the global data distribution result of the first backscattered data, and a second reference point is determined based on the global data distribution result of the second backscattered data; the deviation value between the first reference point and the second reference point is determined, and the backscattered data to be adjusted and the reference backscattered data are determined from the first backscattered data and the second backscattered data; based on the deviation value, the backscattered intensity values ​​contained in the backscattered data to be adjusted are adjusted to obtain the registered backscattered data; the registered backscattered data is fused with the reference backscattered data so that the backscattered data at the same location point are fused. This approach analyzes backscattered data collected from different expeditions based on both the similarity of global and local data distributions. It accurately identifies and corrects systematic biases in the backscattered data, bringing the first and second backscattered data to the same benchmark. This makes previously difficult-to-compare backscattered data comparable, enabling the fusion of backscattered data from different expeditions with high accuracy both overall and locally. This provides more reliable foundational data for subsequent applications such as seabed sediment classification and geomorphological analysis.

[0066] Figure 7This is a schematic diagram of a backscatter data fusion device provided in an embodiment of the present invention. This embodiment is applicable to the fusion of backscatter data obtained from measurements of different missions. The backscatter data fusion device can be implemented in software and / or hardware, and is generally integrated into any electronic device with network communication capabilities, such as a mobile terminal, PC, or server. Figure 7 As shown, the backscattering data fusion apparatus of this embodiment may include a first similarity result determination module 710, a second similarity result determination module 720, a reference point determination module 730, and a data fusion module 740. Wherein: The first similarity result determination module 710 is used to determine a first similarity result based on the first backscatter data and the second backscatter data; wherein the first backscatter data and the second backscatter data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscatter data and the second backscatter data; the first similarity result is used to indicate the degree of similarity between the global data distribution result of the first backscatter data and the global data distribution result of the second backscatter data; The second similarity result determination module 720 is used to determine a second similarity result based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data when the first similarity result meets the first preset requirements. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data. The reference point determination module 730 is used to determine a first reference point based on the global data distribution result of the first backscattered data, and to determine a second reference point based on the global data distribution result of the second backscattered data, when the second similarity result and the first similarity result meet the second preset requirements. The data fusion module 740 is used to fuse backscattered data at the same location point in the first backscattered data and the second backscattered data based on the first reference point and the second reference point.

[0067] The technical solution of this invention involves a first similarity result determination module that determines a first similarity result based on first backscattered data and second backscattered data. The first and second backscattered data are data measured during different voyages targeting the same sea area, and the measurement areas corresponding to the first and second backscattered data overlap. This first similarity result indicates the degree of similarity between the global data distribution results of the first and second backscattered data, thereby identifying the differences in the overall data distribution / trend of the backscattered data from the two voyages. Then, the second similarity result determination module, under the condition that the first similarity result meets the first preset requirements, determines the second similarity result based on the backscattered data corresponding to the overlapping area between the first and second backscattered data. The second similarity result is used to indicate the degree of similarity between the local data distribution results of the first and second backscattered data. This enables a precise comparison of the data in the overlapping area of ​​the two expeditions, and allows for a comparison of the local data distribution of the two, capturing changes in seabed reflectivity that may be caused by sediment migration, biological activity, or subtle topographic changes. Next, the reference point determination module, under the condition that the second and first similarity results meet the second preset requirements, determines the first reference point based on the global data distribution result of the first backscattered data, and the second reference point based on the global data distribution result of the second backscattered data. The data fusion module, based on the first and second reference points, fuses the backscattered data at the same location in the first and second backscattered data, thereby making the data measured in the two expeditions comparable and enabling data fusion. This approach analyzes backscattered data collected from different expeditions based on both the similarity of global and local data distributions. It accurately identifies and corrects systematic biases in the backscattered data, bringing the first and second backscattered data to the same benchmark. This makes previously difficult-to-compare backscattered data comparable, enabling the fusion of backscattered data from different expeditions with high accuracy both overall and locally. This provides more reliable foundational data for subsequent applications such as seabed sediment classification and geomorphological analysis.

[0068] As an optional but non-limiting implementation, the first similarity result determination module 710 includes a first data distribution map determination unit, a second data distribution map determination unit, and a first similarity result determination unit. Wherein: The first data distribution map determination unit is used to draw a bar chart based on each backscattering intensity value contained in the first backscattering data to obtain the first data distribution map; The second data distribution map determination unit is used to draw a bar chart based on each backscattering intensity value contained in the second backscattering data to obtain the second data distribution map; The first similarity result determination unit is used to determine the first similarity result based on the first data distribution map and the second data distribution map.

[0069] As an optional but non-limiting implementation, the first similarity result determination module 710 is further configured to: determine the global peak difference based on the peak value of the first data distribution map and the peak value of the second data distribution map when the first similarity result meets the first preset requirements; and eliminate the graphical false peaks present in the first data distribution map or the second data distribution map when the first similarity result does not meet the first preset requirements.

[0070] As an optional but non-limiting implementation, the overlapping region between the first backscattered data and the second backscattered data is determined as follows: a first measurement region corresponding to the first backscattered data and a second measurement region corresponding to the second backscattered data are determined; based on the first measurement region and the second measurement region, an intersection region is determined, and the intersection region is taken as the overlapping region.

[0071] As an optional but non-limiting implementation, the second similarity result determination module 720 includes a third backscattering data determination unit, a fourth backscattering data determination unit, and a second similarity result determination unit. Wherein: The third backscatter data determination unit is used to determine third backscatter data based on the first backscatter data and the overlapping region, wherein the measurement region corresponding to the third backscatter data is the overlapping region; The fourth backscatter data determination unit is used to determine fourth backscatter data based on the second backscatter data and the overlapping region, wherein the measurement region corresponding to the fourth backscatter data is the overlapping region; The second similarity result determination unit is used to determine the second similarity result based on the third backscattering data and the fourth backscattering data.

[0072] As an optional but non-limiting implementation, the second similarity result determination unit includes a third data distribution map determination subunit, a fourth data distribution map determination subunit, and a second similarity result determination subunit. Wherein: The third data distribution map determines the sub-units, which are used to draw a bar chart based on each backscattering intensity value contained in the third backscattering data, thus obtaining the third data distribution map; The fourth data distribution map is determined by a sub-unit, which is used to draw a bar chart based on each backscattering intensity value contained in the fourth backscattering data, thus obtaining the fourth data distribution map. The second similarity result determination subunit is used to determine the second similarity result based on the third data distribution map and the fourth data distribution map.

[0073] As an optional but non-limiting implementation, the data fusion module 740 includes a first determining unit, an adjusting unit, and a fusion unit. Wherein: The first determining unit is used to determine the deviation value between the first reference point and the second reference point, and to determine the backscatter data to be adjusted and the reference backscatter data from the first backscatter data and the second backscatter data. An adjustment unit is used to adjust each backscattering intensity value contained in the backscattering data to be adjusted based on the deviation value, so as to obtain registered backscattering data. The fusion unit is used to fuse the registered backscattered data with the reference backscattered data so that backscattered data at the same location point are fused.

[0074] The backscattered data fusion apparatus provided in this embodiment of the invention can be used to execute the backscattered data fusion method, and has the corresponding functional modules and beneficial effects for executing the backscattered data fusion method.

[0075] It is worth noting that the various units and modules included in the above-mentioned device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the protection scope of the embodiments of the present invention.

[0076] Figure 8 This is a schematic diagram of an electronic device for implementing a backscattered data fusion method according to an embodiment of the present invention. The following refers to... Figure 8 The diagram illustrates a structural schematic of an electronic device 810 suitable for implementing embodiments of the present invention. The terminal devices in these embodiments may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 8The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0077] like Figure 8 As shown, the electronic device 810 includes at least one processor 811 and a memory, such as a read-only memory (ROM) 812 and a random access memory (RAM) 813, communicatively connected to the at least one processor 811. The memory stores computer programs executable by the at least one processor. The processor 811 can perform various appropriate actions and processes based on the computer program stored in the ROM 812 or loaded from storage unit 818 into the RAM 813. The RAM 813 can also store various programs and data required for the operation of the electronic device 810. The processor 811, ROM 812, and RAM 813 are interconnected via a bus 814. An input / output (I / O) interface 815 is also connected to the bus 814.

[0078] Multiple components in electronic device 810 are connected to input / output (I / O) interface 815, including: input unit 816, such as keyboard, mouse, etc.; output unit 817, such as various types of monitors, speakers, etc.; storage unit 818, such as disk, optical disk, etc.; and communication unit 819, such as network card, modem, wireless transceiver, etc. Communication unit 819 allows electronic device 810 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0079] Processor 811 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 811 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 811 performs the backscattered data fusion method provided in any embodiment of the present invention.

[0080] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the backscattered data fusion method shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 819, or installed from storage unit 818, or installed from read-only memory (ROM) 812. When the computer program is executed by processor 811, it performs the functions defined in the backscattered data fusion method of the embodiments of the present invention.

[0081] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0082] The electronic device provided in this embodiment of the invention and the backscattered data fusion method provided in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0083] This invention provides a computer storage medium storing a computer program that, when executed by a processor, implements the backscattered data fusion method provided in the above embodiments.

[0084] It should be noted that the computer-readable medium described above in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0085] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0086] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can 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 can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0087] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0088] The units described in the embodiments of the present invention can be implemented in software or in hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0089] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0090] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0091] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of disclosure in this invention is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-disclosed concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this invention.

[0092] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the invention. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0093] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A backscattering data fusion method, characterized in that, The method includes: Based on the first backscattered data and the second backscattered data, a first similarity result is determined; wherein the first backscattered data and the second backscattered data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscattered data and the second backscattered data; the first similarity result is used to indicate the degree of similarity between the global data distribution results of the first backscattered data and the global data distribution results of the second backscattered data; If the first similarity result meets the first preset requirement, a second similarity result is determined based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data. If the second similarity result and the first similarity result meet the second preset requirements, a first reference point is determined based on the global data distribution result of the first backscattered data, and a second reference point is determined based on the global data distribution result of the second backscattered data. Based on the first reference point and the second reference point, the backscattered data at the same location point in the first backscattered data and the second backscattered data are fused.

2. The method according to claim 1, characterized in that, The determination of the first similarity result based on the first backscattered data and the second backscattered data includes: A histogram is plotted based on the backscattering intensity values ​​contained in the first backscattering data to obtain the first data distribution map; A histogram is plotted based on the backscattering intensity values ​​contained in the second backscattering data to obtain the second data distribution map; Based on the first data distribution map and the second data distribution map, the first similarity result is determined.

3. The method according to claim 2, characterized in that, After determining the first similarity result, the process also includes: If the first similarity result meets the first preset requirement, the global peak difference is determined based on the peak value of the first data distribution map and the peak value of the second data distribution map; If the first similarity result does not meet the first preset requirement, the graphical false peaks existing in the first data distribution map or the second data distribution map are eliminated.

4. The method according to claim 1, characterized in that, The overlapping region between the first backscattered data and the second backscattered data is determined in the following manner: Determine the first measurement region corresponding to the first backscattered data and the second measurement region corresponding to the second backscattered data; Based on the first measurement region and the second measurement region, an intersection region is determined, and the intersection region is taken as the overlapping region.

5. The method according to claim 1, characterized in that, The determination of the second similarity result based on the backscattered data corresponding to the overlapping region between the first backscattered data and the second backscattered data includes: Based on the first backscattered data and the overlapping region, a third backscattered data is determined, and the measurement region corresponding to the third backscattered data is the overlapping region; Based on the second backscattered data and the overlapping region, fourth backscattered data is determined, and the measurement region corresponding to the fourth backscattered data is the overlapping region; The second similarity result is determined based on the third backscattering data and the fourth backscattering data.

6. The method according to claim 5, characterized in that, The determination of the second similarity result based on the third backscattered data and the fourth backscattered data includes: A histogram was drawn based on the backscattering intensity values ​​contained in the third backscattering data to obtain the third data distribution map; A histogram was drawn based on the backscattering intensity values ​​contained in the fourth backscattering data to obtain the fourth data distribution map; Based on the third data distribution map and the fourth data distribution map, the second similarity result is determined.

7. The method according to claim 1, characterized in that, The step of fusing backscattered data at the same location point in the first backscattered data and the second backscattered data based on the first reference point and the second reference point includes: Determine the deviation between the first reference point and the second reference point, and determine the backscatter data to be adjusted and the reference backscatter data from the first backscatter data and the second backscatter data; Based on the deviation value, the backscattering intensity values ​​contained in the backscattering data to be adjusted are adjusted to obtain the registered backscattering data. The registered backscatter data is fused with the reference backscatter data so that backscatter data at the same location point are fused.

8. A backscattered data fusion device, characterized in that, The device includes: The first similarity result determination module is used to determine a first similarity result based on first backscattered data and second backscattered data; wherein the first backscattered data and the second backscattered data are data obtained by performing different voyages for the same target sea area, and there is an overlap between the measurement areas corresponding to the first backscattered data and the second backscattered data; the first similarity result is used to indicate the degree of similarity between the global data distribution result of the first backscattered data and the global data distribution result of the second backscattered data; The second similarity result determination module is used to determine a second similarity result based on the backscattered data corresponding to the overlapping area between the first backscattered data and the second backscattered data, when the first similarity result meets the first preset requirements. The second similarity result is used to indicate the degree of similarity between the local data distribution result of the first backscattered data and the local data distribution result of the second backscattered data. The reference point determination module is used to determine a first reference point based on the global data distribution result of the first backscattered data, and to determine a second reference point based on the global data distribution result of the second backscattered data, provided that the second similarity result and the first similarity result meet the second preset requirements. The data fusion module is used to fuse backscattered data from the first backscattered data and the second backscattered data at the same location point based on the first reference point and the second reference point.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the backscatter data fusion method as described in any one of claims 1-7.

10. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the backscatter data fusion method as described in any one of claims 1-7.

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