A method and system for identifying unexploded ordnance on the seabed based on multi-source data

Abstract

This invention relates to the field of seabed detection technology, specifically to a method and system for identifying unexploded ordnance (UFOs) based on multi-source data. The method includes: acquiring multi-source detection data from the seabed surface and initial screening of magnetic anomalies; screening of suspected mine points based on mine magnetic moment modeling; screening of suspected mine points based on estimated burial depth; screening of suspected mine points based on estimated weight; and refined verification of suspected mine points. The method performs initial screening based on the obtained unexploded ordnance magnetic anomaly data, and combines this with geological information such as shallow seismic profile data, side-scan sonar data, and synthetic aperture sonar data, mine modeling and magnetic anomaly matching algorithms, and methods for screening based on estimated burial depth and estimated weight to eliminate non-unexploded ordnance magnetic anomalies. Finally, refined verification is achieved through a magnetically encrypted detection method, enabling the identification and location of unexploded ordnance.

Description

Technical Field

[0001] This invention relates to the field of seabed exploration technology, specifically to a method and system for identifying unexploded ordnance on the seabed based on multi-source data. Background Technology

[0002] The sites selected for offshore wind power projects may overlap with designated suspected minefields at sea. The presence of unexploded ordnance (UFOs) threatens the safe construction of offshore wind farms, necessitating advance identification of UFO locations within suspected minefields to enable targeted mine clearance operations. Currently, most UFO detection in suspected offshore minefields utilizes marine magnetometers, which receive magnetic responses (magnetic anomalies) from the seabed surface and buried ferromagnetic objects. However, this method has limitations. Firstly, there is no feasible data processing or determination method to determine whether the magnetic anomalies in the obtained magnetic data are caused by UFOs. Secondly, marine magnetometers rely solely on the ferromagnetism of objects for detection, resulting in a limited range of methods and multiple interpretations, thus restricting the accuracy of UFO identification. Summary of the Invention

[0003] To address the aforementioned technical problems, the present invention aims to provide a method and system for identifying unexploded ordnance on the seabed based on multi-source data. The specific technical solution adopted is as follows:

[0004] In a first aspect, the present invention provides a method for identifying unexploded ordnance on the seabed based on multi-source data, comprising:

[0005] Collect multi-source seabed detection data, and based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly of the seabed surface;

[0006] A magnetic anomaly sample library for mines is established based on the magnetic anomaly conditions corresponding to the mine types. The magnetic anomaly data of each initial screening are matched with the magnetic anomaly conditions in the mine magnetic anomaly sample library to obtain the magnetic anomaly signal curve that matches the mine magnetic anomaly sample library.

[0007] The burial depth of the magnetic anomaly object is calculated based on the magnetic anomaly signal curve data, and the magnetic anomaly signal curve is further screened to obtain initial suspected mine points.

[0008] The mass of the ferromagnetic object that generates each magnetic anomaly is calculated based on the formula for calculating the intensity of the underwater target magnetic anomaly. The initial suspected mine points are screened based on the mass to determine the suspected mine points.

[0009] Based on the shape, size, and burial status of objects at the suspected mine location, the identification results of unexploded ordnance on the seabed were obtained.

[0010] Preferably, the method for acquiring the multi-source detection data specifically includes:

[0011] Multibeam sonar is used to determine whether there are large unexploded ordnance on the seabed and the overall topography, and to identify low-lying areas on the seabed. For low-lying areas on the seabed, side-scan sonar is used to search for small unexploded ordnance on the seabed, and full-coverage marine magnetic detection is carried out to obtain total field data.

[0012] Preferably, the step of obtaining preliminary magnetic anomaly data characterizing seabed surface magnetic anomalies based on multi-source seabed detection data and preprocessing specifically includes:

[0013] After sequentially performing jump point deletion, height correction, and nonlinear filtering on the total field data, the background field data is obtained. Subtracting the background field data from the total field data yields the remaining field data.

[0014] Linear or banded magnetic anomalies corresponding to the geological structures shown in the multibeam measurement data are removed from the remaining field data to obtain preliminary magnetic anomaly data.

[0015] Preferably, the establishment of a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine type specifically includes:

[0016] Obtain the spatial magnetic field distribution of various types of sea mines;

[0017] Based on the actual ocean magnetic detection process, the minimum and maximum distances between the mine and the magnetic gradient meter are determined, forming a distance range;

[0018] Multiple straight paths are selected at equal intervals within the distance range of the spatial magnetic field distribution of each type of mine to obtain the magnetic field signal curves on the paths. A sample library of mine magnetic anomalies is established based on the magnetic field signal curves on all paths of each type of mine.

[0019] Preferably, the step of matching each initial screening magnetic anomaly data with each magnetic anomaly in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve matching the mine magnetic anomaly sample library specifically includes:

[0020] Based on the matching of the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, the Minkowski distance is calculated to obtain the similarity between the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library. The signal curves in the initial screening magnetic anomaly data with similarity greater than a preset threshold are taken as magnetic field anomaly signal curves.

[0021] Preferably, the step of calculating the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data specifically includes:

[0022] Obtain the mean signal values ​​of the maximum and minimum points on the magnetic anomaly signal curve, and mark the location of the mean signal value on the magnetic anomaly signal curve as the marker point;

[0023] The horizontal axis distance between the marker point and the maximum point on the magnetic anomaly signal curve is recorded as the first distance, and the horizontal axis distance between the marker point and the minimum point on the magnetic anomaly signal curve is recorded as the second distance. The minimum value between the first distance and the second distance is taken as the half-value point distance.

[0024] The burial depth of magnetic anomaly objects is obtained based on the half-value point distance combined with the burial depth inversion model.

[0025] Preferably, the formula for calculating the intensity of the underwater target magnetic anomaly is as follows:

[0026]

[0027] Where ΔT is the magnetic anomaly intensity, κ is the mass magnetization intensity, m is the mass, and r is the detection distance.

[0028] Secondly, the present invention provides a seabed unexploded ordnance identification system based on multi-source data. This system is used to implement the steps of a seabed unexploded ordnance identification method based on multi-source data. The seabed unexploded ordnance identification system based on multi-source data includes:

[0029] The data acquisition and preliminary screening module is used to collect multi-source seabed detection data and, based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly of the seabed surface.

[0030] The magnetic anomaly matching module is used to establish a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine type. It matches each initial screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library.

[0031] The burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and further screens the magnetic anomaly signal curve to obtain initial suspected mine points.

[0032] The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the formula for calculating the intensity of underwater target magnetic anomalies, and to screen the initial suspected mine points based on the mass to determine the suspected mine points;

[0033] The refined verification module is used to obtain the identification results of unexploded ordnance on the seabed based on the shape, size and burial state of objects at the location of suspected mine points.

[0034] The embodiments of the present invention have at least the following beneficial effects:

[0035] This invention utilizes geological priors, magnetic anomaly signal waveforms, quality, and burial depth to screen magnetic anomaly signals from multiple angles, effectively eliminating a large number of non-unexploded ordnance magnetic anomalies in marine magnetic data. Addressing the current limitations of relying solely on marine magnetic methods for unexploded ordnance detection at sea, which suffers from multiple interpretations and restricts accuracy, this invention leverages the strengths of various marine detection methods, including side-scan sonar, marine magnetics, and synthetic aperture sonar. By combining multi-source data and considering seabed topography, size, and shape across multiple scales, it screens for and accurately locates suspected mine points, achieving comprehensive detection of unexploded ordnance on the seabed. Attached Figure Description

[0036] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart of a method for identifying unexploded ordnance on the seabed based on multi-source data provided by the present invention;

[0038] Figure 2 This invention provides the topography of the survey area obtained through multibeam measurement;

[0039] Figure 3 These are the seabed imaging results obtained by the side-scan sonar provided by this invention;

[0040] Figure 4 This is a schematic diagram of linear or banded magnetic anomalies generated by geological structures in the residual field provided by the present invention.

[0041] Figure 5 This is a schematic diagram of the marine mine magnetic anomaly sample library provided by the present invention;

[0042] Figure 6 This is a schematic diagram comparing a magnetic anomaly in the initial screening magnetic anomaly data provided by this invention with a magnetic anomaly curve in the mine magnetic anomaly sample library.

[0043] Figure 7 The image results of synthetic aperture sonar during the refined verification of suspected mine points provided by this invention;

[0044] Figure 8 The imaging results of the shallow seismic profiling method during the refined verification of suspected mine points provided by this invention;

[0045] Figure 9 This is the final result diagram of suspected lightning spots in the test area provided by the present invention. Detailed Implementation

[0046] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method and system for identifying unexploded ordnance on the seabed based on multi-source data proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0048] The following description, in conjunction with the accompanying drawings, details the specific scheme of the seabed unexploded ordnance identification method and system based on multi-source data provided by the present invention.

[0049] Please see Figure 1 The diagram illustrates a flowchart of a method for identifying unexploded ordnance on the seabed based on multi-source data, according to an embodiment of the present invention. The method includes the following steps:

[0050] Step S1: Collect multi-source seabed detection data. Based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly on the seabed surface.

[0051] The main objective of this step is comprehensive seabed surface exploration and multi-source data acquisition. Specifically, this includes determining the presence of large exposed unexploded ordnance and the overall topography of the seabed based on multibeam bathymetry, identifying low-lying areas on the seabed, and obtaining topographic data for the entire survey area, such as... Figure 2 As shown. For searching for small unexploded ordnance on the seabed in low-lying areas using side-scan sonar, typical imaging data is as follows: Figure 3 As shown, a full-coverage marine magnetic survey was conducted to obtain magnetic anomaly data (i.e., total field data) generated by the seabed surface and all buried ferromagnetic objects within the survey area, superimposed on the seabed geomagnetic background field.

[0052] Then, the seafloor geomagnetic background field is removed from the total field data to obtain the data containing only magnetic anomalies generated by all ferromagnetic objects, i.e., the residual field data. That is, the background field data is obtained by sequentially performing jump point deletion, height correction, and nonlinear filtering on the total field data, and the residual field data is obtained by subtracting the background field data from the total field data.

[0053] Specifically, the process of removing skipped points includes: First, deleting skipped points in the magnetic data, deleting and interpolating skipped points in the positioning data of each survey line, and deleting and interpolating skipped points in the height data above the ground; Second, correcting the height above the ground in the magnetic data, reducing the magnetic data to a uniform height of 5m above the ground; Third, performing nonlinear filtering on the height-corrected magnetic field data, setting the filter size to 30 and the threshold to 0.1~1 to obtain the background field data, and subtracting the background field from the original magnetic field data to obtain the initial screening magnetic anomaly data.

[0054] Furthermore, after obtaining the residual field data, ferromagnetic objects exposed on the seabed can be identified in the multibeam topographic survey data and side-scan sonar data to eliminate known magnetic anomalies caused by non-unexploded ordnance on the seabed. Obvious linear or banded magnetic anomalies corresponding to geological structures shown in the multibeam measurement data are removed from the initial screening magnetic anomaly data to eliminate interference from geological structures. All magnetic anomaly data in the total magnetic field data are then screened, and accidental magnetic anomalies caused by instrument noise, environmental interference, topographic changes, etc., are eliminated to obtain initial screening magnetic anomaly data characterizing the magnetic anomalies on the seabed, such as... Figure 4 As shown.

[0055] Step S2: Establish a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine type. Match each initial screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library to obtain the magnetic anomaly signal curve that matches the mine magnetic anomaly sample library.

[0056] Specifically, the spatial magnetic field distribution of each type of mine is obtained; the minimum and maximum distances between the mine and the magnetic gradient instrument are determined based on the height of the magnetic gradient instrument above the bottom and the maximum detection distance of the magnetometer during actual marine magnetic detection, forming a distance range; multiple straight paths are selected at equal intervals within the distance range in the spatial magnetic field distribution of each type of mine, and the magnetic field signal curves on the paths are obtained; a mine magnetic anomaly sample library is established based on the magnetic field signal curves on all paths of each type of mine.

[0057] As a concrete example, this embodiment uses the fabrication of a physical model of the MK-25 bottom mine as an illustration. The measured magnetic moment parameters of the mine are used to simulate the spatial magnetic field distribution of the MK-25 bottom mine through magnetic field forward modeling. (Unexploded ordnance magnetic moment...) It consists of the following parts, namely the longitudinal component along the axis of the unexploded ordnance: The horizontal component is The vertical component is Establish a geomagnetic coordinate system with the geomagnetic meridian as the reference plane, with geomagnetic north as the x-direction, geomagnetic east as the y-direction, and the z-direction vertically downward.

[0058] set up , These represent the longitudinal induced and fixed magnetic moments in the geomagnetic coordinate system, respectively. , For the lateral induced and fixed magnetic moments in the geomagnetic coordinate system, For the vertical resultant magnetic moment, Let be the magnetic declination, then:

[0059]

[0060] in, This represents the longitudinal component along the mine's axis. This represents the lateral component along the mine's axis. This represents the vertical component along the mine's axis.

[0061] An unexploded ordnance model was placed sequentially to the south, west, north, and east of the magnetometer, with a fixed detection distance (e.g., 5.0 meters). The azimuth of the unexploded ordnance model was adjusted sequentially to 0°, 90°, 180°, and 270°, meaning data was measured four times in each direction. Magnetic anomalies of the unexploded ordnance model under different conditions were collected, and the various magnetic moment components of the model were calculated based on the magnetic moment processing model. Throughout the data acquisition process, the position and attitude of the magnetometer remained constant, and geomagnetic diurnal variation measurements were conducted simultaneously.

[0062] The magnetic moment of the unexploded ordnance model can be calculated from the above measurements, thus completing the modeling of the magnetic characteristics of the unexploded ordnance. Finally, the magnetic moment of the unexploded ordnance is calculated using the formula as follows:

[0063]

[0064]

[0065]

[0066]

[0067]

[0068] in, , These represent the longitudinal induced and fixed magnetic moments in the geomagnetic coordinate system, respectively. , These represent the lateral induced and fixed magnetic moments in the geomagnetic coordinate system, respectively, where r is the distance from the model to the magnetometer. The magnetic anomaly value represents the magnetic field when the magnetometer is located south and the model azimuth is 0°. S represents south, W represents west, N represents north, and E represents east. The model azimuth includes 0°, 90°, 180°, and 270°. I represents the geomagnetic tilt angle.

[0069] Based on the magnetic moment parameters obtained from experiments, magnetic field simulation was performed on the unexploded ordnance model using the spatial distribution characteristics of magnetic dipoles. The minimum and maximum distances between the mine and the magnetic gradiometer were determined based on the bottom height of the magnetic gradiometer and the maximum detection distance of the magnetometer during actual marine magnetic detection. Within this distance range, multiple equally spaced linear paths were selected in the magnetic field distribution generated by the MK-25 bottom mine, and the magnetic field signal curves (magnetic anomalies) along these paths were obtained. A mine magnetic anomaly sample library was established based on the magnetic anomalies along all paths of the MK-25 bottom mine. Figure 5 As shown.

[0070] Furthermore, based on the matching of the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, the Minkowski distance is calculated to obtain the similarity between the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library. The signal curves in the initial screening magnetic anomaly data with similarity greater than a preset threshold are taken as magnetic field anomaly signal curves.

[0071] Specifically, each magnetic anomaly in the initial screening magnetic anomaly data is compared with each magnetic anomaly in the mine magnetic anomaly sample library to measure the similarity between the two, and magnetic anomalies that cannot be well matched in the initial screening magnetic anomaly data are removed.

[0072] More specifically, the first step is to align and match the two magnetic anomaly curves based on feature points on the curves. Considering that the typical morphology of a magnetic dipole is generally a relatively common single-peak, double-peak, and less common triple-peak shape, a maximum or minimum value that deviates most from the curve mean is used as the alignment feature point. The position and shape of one magnetic anomaly curve are changed through rotation, scaling, and translation operations to make it as similar as possible to the other. Finally, the similarity between the two magnetic anomaly curves is calculated using the parameter-adaptive Minkowski distance. Figure 6 As shown.

[0073] Step S3: Calculate the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and further screen the magnetic anomaly signal curve to obtain initial suspected mine points.

[0074] The main purpose of this step is to estimate the burial depth and perform burial depth screening. Specifically, the first step is to obtain the signal mean values ​​of the maximum and minimum points on the magnetic anomaly signal curve, and mark the locations of the signal mean values ​​on the magnetic anomaly signal curve as marker points. The second step is to obtain the horizontal axis distance between the marker point and the maximum point on the magnetic anomaly signal curve, recorded as the first distance, and the horizontal axis distance between the marker point and the minimum point on the magnetic anomaly signal curve, recorded as the second distance. The minimum value between the first and second distances is taken as the half-value point distance. The third step is to obtain the burial depth of the magnetic anomaly object based on the half-value point distance and the burial depth inversion model.

[0075] As a concrete example, find a point x in the magnetic field signal curves of each magnetic anomaly in the initial screening magnetic anomaly data. 1 / 2 That is, a marker point, so that its magnetic field T 1 / 2 Equal to the maximum value T of the magnetic anomaly signal curve max and the minimum value T min The algebraic mean of can be expressed as:

[0076]

[0077] This point x 1 / 2 With the maximum point x max The distance is dx max =x 1 / 2 -x max , and the minimum point x min The distance is dx min =x 1 / 2 -x min The smaller of the two values ​​is defined as the half-value point distance dx. 2.1×dx is taken as the actual burial depth of the object that generates the magnetic anomaly. This method has been verified to have an error of less than 5%. Based on the data collected in the local sea area, theoretical deduction is made to believe that the sinking of the mine on the seabed will not exceed 2cm per year and the total depth will not exceed 5m, thus eliminating anomalies with excessive burial depth.

[0078] Step S4: Calculate the mass of the ferromagnetic object that generates each magnetic anomaly based on the formula for calculating the intensity of the underwater target magnetic anomaly, and screen the initial suspected mine points according to the mass to determine the suspected mine points.

[0079] The main purpose of this step is to estimate the mass and perform mass screening. Based on the magnetic field signals of each magnetic anomaly in the initial screening magnetic anomaly data, the mass of the ferromagnetic object that generated each magnetic anomaly is calculated using the underwater target magnetic anomaly intensity calculation formula. The underwater target magnetic anomaly intensity calculation formula is as follows:

[0080]

[0081] In the formula, ΔT is the magnetic anomaly intensity in nT; κ is the mass magnetization in CGSM(m) / t; m is the mass in t; and r is the detection distance in meters. The mass of the object generating the magnetic anomaly is deduced from the formula for calculating the magnetic anomaly intensity. According to the "Operating Manual for G-882 Marine Magnetometer," a 450kg bomb generates a magnetic anomaly intensity of 1.0nT at a distance of 30 meters, with a mass magnetization intensity of 6×10⁵CGSM(m) / t. This value is comparable to the mass magnetization intensity of general ferromagnetic materials. Based on this, magnetic anomalies that do not meet the mass requirement of the MK-25 bottom mine are eliminated.

[0082] After the above processing, the magnetic anomalies that were not removed from the initial screening magnetic anomaly data were designated as suspected minefields.

[0083] Step S5: Based on the shape, size, and burial status of the object at the suspected mine location, obtain the identification result of the unexploded ordnance on the seabed.

[0084] Synthetic aperture sonar was used to scan each suspected mine site to accurately locate its position. Typical data are as follows: Figure 7 As shown; shallow seismic profiling was used to scan the suspected mine location and surrounding area using multiple intersecting survey lines to determine the shape, size, and burial state of the object at the suspected mine location. Its shape and size were determined to be consistent with the MK-25 bottom mine. Typical data are shown below. Figure 8 As shown in the image. The final identified results of suspected lightning strike points within the test area are shown in the image. Figure 9 As shown.

[0085] The present invention also provides a system for identifying unexploded ordnance on the seabed based on multi-source data, comprising:

[0086] The data acquisition and preliminary screening module is used to collect multi-source seabed detection data and, based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly of the seabed surface.

[0087] The magnetic anomaly matching module is used to establish a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine type. It matches each initial screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library.

[0088] The burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and further screens the magnetic anomaly signal curve to obtain initial suspected mine points.

[0089] The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the formula for calculating the intensity of underwater target magnetic anomalies, and to screen the initial suspected mine points based on the mass to determine the suspected mine points;

[0090] The refined verification module is used to obtain the identification results of unexploded ordnance on the seabed based on the shape, size and burial state of objects at the location of suspected mine points.

[0091] One of the methods is a seabed unexploded ordnance identification system based on multi-source data, which is used to perform the steps of a seabed unexploded ordnance identification method based on multi-source data. Since the method embodiments have been described in detail, they will not be described in detail here.

[0092] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for identifying unexploded ordnance on the seabed based on multi-source data, characterized in that, The method includes the following steps: Collect multi-source seabed detection data, and based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly of the seabed surface; A magnetic anomaly sample library for mines is established based on the magnetic anomaly conditions corresponding to the mine types. The magnetic anomaly data of each initial screening are matched with the magnetic anomaly conditions in the mine magnetic anomaly sample library to obtain the magnetic anomaly signal curve that matches the mine magnetic anomaly sample library. The burial depth of the magnetic anomaly object is calculated based on the magnetic anomaly signal curve data, and the magnetic anomaly signal curve is further screened to obtain initial suspected mine points. The mass of the ferromagnetic object that generates each magnetic anomaly is calculated based on the formula for calculating the intensity of the underwater target magnetic anomaly. The initial suspected mine points are screened based on the mass to determine the suspected mine points. Based on the shape, size, and burial status of objects at the suspected mine location, the identification results of unexploded ordnance on the seabed were obtained.

2. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The method for acquiring the multi-source detection data is as follows: Multibeam sonar is used to determine whether there are large unexploded ordnance on the seabed and the overall topography, and to identify low-lying areas on the seabed. For low-lying areas on the seabed, side-scan sonar is used to search for small unexploded ordnance on the seabed, and full-coverage marine magnetic detection is carried out to obtain total field data.

3. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The process of acquiring preliminary magnetic anomaly data characterizing seabed surface magnetic anomalies based on multi-source seabed detection data and preprocessing specifically includes: After sequentially performing jump point deletion, height correction, and nonlinear filtering on the total field data, the background field data is obtained. Subtracting the background field data from the total field data yields the remaining field data. Linear or banded magnetic anomalies corresponding to the geological structures shown in the multibeam measurement data are removed from the remaining field data to obtain preliminary magnetic anomaly data.

4. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The establishment of a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to different mine types specifically includes: Obtain the spatial magnetic field distribution of various types of sea mines; Based on the actual ocean magnetic detection process, the minimum and maximum distances between the mine and the magnetic gradient meter are determined, forming a distance range; Multiple straight paths are selected at equal intervals within the distance range of the spatial magnetic field distribution of each type of mine to obtain the magnetic field signal curves on the paths. A sample library of mine magnetic anomalies is established based on the magnetic field signal curves on all paths of each type of mine.

5. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The step of matching each initial screening magnetic anomaly data with each magnetic anomaly in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library specifically includes: Based on the matching of the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, the Minkowski distance is calculated to obtain the similarity between the signal curves of each magnetic anomaly in the initial screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library. The signal curves in the initial screening magnetic anomaly data with similarity greater than a preset threshold are taken as magnetic field anomaly signal curves.

6. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The calculation of the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data specifically includes: Obtain the mean signal values ​​of the maximum and minimum points on the magnetic anomaly signal curve, and mark the location of the mean signal value on the magnetic anomaly signal curve as the marker point; The horizontal axis distance between the marker point and the maximum point on the magnetic anomaly signal curve is recorded as the first distance, and the horizontal axis distance between the marker point and the minimum point on the magnetic anomaly signal curve is recorded as the second distance. The minimum value between the first distance and the second distance is taken as the half-value point distance. The burial depth of magnetic anomaly objects is obtained based on the half-value point distance combined with the burial depth inversion model.

7. The method for identifying unexploded ordnance on the seabed based on multi-source data according to claim 1, characterized in that, The specific formula for calculating the intensity of the underwater target magnetic anomaly is as follows: Where ΔT is the magnetic anomaly intensity, κ is the mass magnetization intensity, m is the mass, and r is the detection distance.

8. A system for identifying unexploded ordnance on the seabed based on multi-source data, characterized in that, This system is used to implement the steps of the method for identifying unexploded ordnance on the seabed based on multi-source data as described in any one of claims 1-7, wherein the system for identifying unexploded ordnance on the seabed based on multi-source data includes: The data acquisition and preliminary screening module is used to collect multi-source seabed detection data and, based on the multi-source seabed detection data and preprocessing, obtain preliminary magnetic anomaly data characterizing the magnetic anomaly of the seabed surface. The magnetic anomaly matching module is used to establish a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine type. It matches each initial screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library. The burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and further screens the magnetic anomaly signal curve to obtain initial suspected mine points. The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the formula for calculating the intensity of underwater target magnetic anomalies, and to screen the initial suspected mine points based on the mass to determine the suspected mine points; The refined verification module is used to obtain the identification results of unexploded ordnance on the seabed based on the shape, size and burial state of objects at the location of suspected mine points.

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