Seabed unexploded ordnance identification method and system based on multi-source data

Abstract

The invention relates to the technical field of seafloor detection, in particular to a seafloor unexploded ordnance identification method and system based on multi-source data, and the method comprises the steps: obtaining seafloor surface multi-source detection data, and carrying out the preliminary screening of magnetic anomalies; suspected mine point magnetic anomaly screening based on mine magnetic moment modeling; pre-estimated burial depth screening of suspected thunder points; screening estimated weights of suspected thunder points; and performing refined verification on the suspected lightning point. According to the method, preliminary screening is carried out according to obtained unexploded ammunition magnetic anomaly data, and non-unexploded ammunition magnetic anomaly elimination is realized by combining geological information such as shallow stratum profile data, side-scan sonar data and synthetic aperture sonar data, a mine modeling and magnetic anomaly matching algorithm, a pre-estimated burial depth and pre-estimated weight screening method and the like. Finally, fine verification is carried out through a magnetic encryption detection method, and unexploded ordnance identification and positioning are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of seabed detection, and in particular to a method and system for identifying seabed unexploded bombs based on multi-source data. Background Art

[0002] Sites selected for offshore wind power projects may overlap with designated areas of suspected minefields. The presence of unexploded ordnance (UXO) poses a threat to the safe construction of offshore wind farms. Pre-determining the location of UXO in these areas is crucial for targeted mine clearance. Currently, UXO detection in suspected minefields is mostly performed using marine magnetometers, which detect magnetic responses from the seafloor and buried ferromagnetic objects, known as magnetic anomalies. However, this method has drawbacks. Firstly, there is a lack of reliable data processing methods to determine whether magnetic anomalies in the acquired magnetic data are caused by UXO. Secondly, marine magnetometers rely solely on the ferromagnetic properties of objects, resulting in a single detection method and high multi-solution capability, which limits the accuracy of UXO determination. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention aims to provide a method and system for identifying submarine unexploded ordnance based on multi-source data. The technical solutions adopted are as follows: In a first aspect, the present invention provides a method for identifying submarine unexploded ordnance based on multi-source data, comprising: Collect seabed multi-source detection data, and obtain preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing; A mine magnetic anomaly sample library is established based on the magnetic anomaly conditions corresponding to the mine model. The initial screening magnetic anomaly data are matched with the magnetic anomaly conditions in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library. Calculating the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screening the magnetic anomaly signal curve to obtain an initial suspected mine point; The mass of the ferromagnetic object that generates each magnetic anomaly is calculated based on the underwater target magnetic anomaly intensity calculation formula, and the initial suspected lightning points are screened according to the mass to determine the suspected lightning points; The identification results of unexploded bombs on the seabed are obtained based on the shape, size and burial status of the objects at the location of the suspected minepoints.

[0004] Preferably, the method for acquiring the multi-source detection data is specifically as follows: Multi-beam measurements are used to determine whether there are large exposed unexploded bombs on the seabed and the overall terrain conditions, and to identify low-lying areas on the seabed. For low-lying areas on the seabed, side-scan sonar is used to screen for small unexploded bombs on the seabed, and full-coverage marine magnetic detection is conducted to obtain total field data.

[0005] Preferably, the method of obtaining preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on seabed multi-source detection data and preprocessing specifically includes: The total field data is sequentially subjected to jump point deletion, height correction and nonlinear filtering to obtain background field data, and the background field data is subtracted from the total field data to obtain the residual field data; The linear or zonal magnetic anomalies corresponding to the geological structure positions shown by the multi-beam measurement data in the remaining field data are eliminated to obtain the preliminary screening magnetic anomaly data.

[0006] Preferably, the step of establishing a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine models specifically includes: Obtain the spatial magnetic field distribution of various types of mines; The minimum and maximum distances between the mine and the magnetic gradiometer are determined based on the height of the magnetic gradiometer from the bottom and the maximum detection distance of the magnetometer during actual marine magnetic detection, forming a distance range. A plurality of linear paths are equally spaced within the distance range in the spatial magnetic field distribution of each type of mine, and 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.

[0007] Preferably, the matching of each preliminary screening magnetic anomaly data with each magnetic anomaly situation in a mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve matching the mine magnetic anomaly sample library specifically includes: Based on the matching of the signal curves of each magnetic anomaly in the preliminary 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 preliminary screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, and the signal curves in the preliminary screening magnetic anomaly data with the similarity greater than a preset threshold are used as magnetic field anomaly signal curves.

[0008] Preferably, the calculating the burial depth of the magnetic anomaly object according to the magnetic anomaly signal curve data specifically includes: Obtain the signal mean of the maximum value point and the minimum value point on the magnetic anomaly signal curve, and mark the position of the signal mean on the magnetic anomaly signal curve as a marked point; The horizontal axis distance between the obtained mark point and the maximum value point on the magnetic anomaly signal curve is recorded as the first distance, the horizontal axis distance between the obtained mark point and the minimum value point on the magnetic anomaly signal curve is recorded as the second distance, and the minimum value of 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 and the burial depth inversion model.

[0009] Preferably, the calculation formula for the underwater target magnetic anomaly intensity is specifically:

[0010] Where ΔT is the magnetic anomaly intensity, κ is the mass magnetization intensity, m is the mass, and r is the detection distance.

[0011] In a second aspect, the present invention provides a system for identifying submarine unexploded ordnance based on multi-source data. The system is used to implement the steps of a method for identifying submarine unexploded ordnance based on multi-source data. The system comprises: The data acquisition and preliminary screening module is used to collect seabed multi-source detection data, and obtain preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing; 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 model, match each preliminary screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library, and obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library; A burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screens the magnetic anomaly signal curve to obtain an initial suspected minepoint; The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the underwater target magnetic anomaly intensity calculation formula, and to screen the initial suspected lightning points according to the mass to determine the suspected lightning points; The refined verification module is used to obtain the identification results of unexploded bombs on the seabed based on the shape, size and burial status of the object at the location of the suspected mine point.

[0012] The embodiments of the present invention have at least the following beneficial effects: This method uses multi-dimensional screening of magnetic anomaly signals based on geological priors, magnetic anomaly waveform, quality, and burial depth to eliminate a large number of non-UXO magnetic anomalies from marine magnetic data. This method addresses the current problem of marine magnetics alone, which limits the accuracy of UXO determination due to its high multi-solution capability. This method leverages the strengths of various marine detection methods, including side-scan sonar, marine magnetics, and synthetic aperture sonar, and combines multi-source data to screen and accurately locate suspected minepoints based on seafloor topography, size, and shape, achieving comprehensive detection of submarine UXO. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0014] Figure 1 This is a flow chart of a method for identifying submarine unexploded bombs based on multi-source data provided by the present invention; Figure 2 The topography of the survey area obtained by multi-beam measurement provided by the present invention; Figure 3 It is the seabed imaging result obtained by the side-scan sonar provided by the present invention; Figure 4 It is a schematic diagram of the linear or banded distribution of magnetic anomalies in the residual field provided by the present invention after removing the geological structure; Figure 5 This is a schematic diagram of the mine magnetic anomaly sample library provided by the present invention; Figure 6 It is a schematic diagram of comparing a magnetic anomaly in the primary screening magnetic anomaly data provided by the present invention with a magnetic anomaly curve in a mine magnetic anomaly sample library; Figure 7 It is the imaging result of synthetic aperture sonar in the process of fine verification of suspected minepoints provided by the present invention; Figure 8 It is the imaging result of the shallow stratum profile method in the process of fine verification of suspected minepoints provided by the present invention; Figure 9 This is the final result map of suspected lightning points in the survey area provided by the present invention. DETAILED DESCRIPTION

[0015] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a method and system for identifying submarine unexploded ordnance based on multi-source data, as proposed by the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0016] Unless defined otherwise, 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 belongs.

[0017] The following describes in detail a method and system for identifying submarine unexploded ordnance based on multi-source data provided by the present invention with reference to the accompanying drawings.

[0018] See also Figure 1 , which shows a flowchart of a method for identifying submarine unexploded ordnance based on multi-source data according to an embodiment of the present invention. The method comprises the following steps: Step S1: collecting seabed multi-source detection data, and obtaining preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing.

[0019] The main purpose of this step is to comprehensively detect the seabed and obtain multi-source data, including determining whether there are large exposed unexploded bombs and the overall terrain conditions on the seabed based on multi-beam measurement, determining the low-lying areas on the seabed, and the terrain data of the entire survey area. Figure 2 For low-lying areas on the seabed, the typical imaging data for detecting small unexploded bombs on the seabed using side-scan sonar is as follows: Figure 3 Conduct full-coverage marine magnetic surveys to obtain magnetic anomaly data generated by the seabed surface and all buried ferromagnetic objects superimposed on the seabed geomagnetic background field within the survey area, namely, total field data.

[0020] The seafloor geomagnetic background field is then removed from the total field data, resulting in data containing only the magnetic anomalies generated by all ferromagnetic objects, known as the residual field data. Specifically, the total field data is sequentially subjected to jump point removal, height correction, and nonlinear filtering to obtain the background field data, which is then subtracted from the total field data to obtain the residual field data.

[0021] Specifically, the skip point removal process includes: the first step is to select and delete points in the magnetic data, skip point deletion and interpolation of the positioning data of each survey line, and skip point deletion and interpolation of the bottom height data; the second step is to correct the bottom height of the magnetic data and convert the magnetic data to the magnetic data at a unified bottom height of 5m; the third step is to perform nonlinear filtering on the height-corrected magnetic field data, with the filter size set to 30 and the threshold value set to 0.1~1 to obtain background field data, and the original magnetic field data is subtracted from the background field to obtain the preliminary screening magnetic anomaly data.

[0022] Furthermore, after obtaining the residual field data, the ferromagnetic objects exposed on the seabed shown in the multi-beam topographic survey data and the side-scan sonar data can be used to exclude the magnetic anomalies caused by non-unexploded bombs exposed on the seabed in the residual field data; the obvious linear or banded magnetic anomalies corresponding to the geological structure positions shown in the multi-beam survey data in the preliminary screening magnetic anomaly data are eliminated to obtain preliminary screening magnetic anomaly data to eliminate the interference caused by the geological structure, screen all magnetic anomaly data in the total magnetic field data, eliminate accidental magnetic anomalies caused by instrument noise, environmental interference, terrain changes, etc., and obtain preliminary screening magnetic anomaly data representing the magnetic anomalies of the seabed, such as Figure 4 shown.

[0023] Step S2: establishing a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine models, matching each preliminary screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library, and obtaining a magnetic anomaly signal curve matching the mine magnetic anomaly sample library.

[0024] Specifically, the spatial magnetic field distribution of each type of mine is obtained; the minimum and maximum distances between the mine and the magnetic gradiometer are determined based on the height of the magnetic gradiometer from the bottom and the maximum detection distance of the magnetometer during actual marine magnetic detection, thereby forming a distance range; multiple linear paths are equally spaced within the distance range in the spatial magnetic field distribution of each type of mine, and magnetic field signal curves on the paths are obtained. Based on the magnetic field signal curves on all paths of each type of mine, a mine magnetic anomaly sample library is established.

[0025] As a specific example, this embodiment uses the production of a physical model of an MK-25 bottom mine as an example to illustrate the measured magnetic moment parameters of the mine and simulate the spatial magnetic field distribution of the MK-25 bottom mine through magnetic field forward modeling. It consists of the following parts, namely, the longitudinal component along the axis of the unexploded bomb is , the transverse component is , the vertical component is The geomagnetic coordinate system is established with the geomagnetic meridian plane as the reference plane, with geomagnetic north as the x direction, geomagnetic east as the y direction, and z direction vertically downward.

[0026] set up 、 are the longitudinal induction and fixed magnetic moment in the geomagnetic coordinate system, 、 is the transverse induction and fixed magnetic moment in the geomagnetic coordinate system, is the vertical resultant magnetic moment, is the geomagnetic declination, then:

[0027] in, represents the longitudinal component along the mine axis, represents the lateral component along the axis of the mine, Represents the vertical component along the axis of the mine.

[0028] The unexploded bomb model was placed on the south, west, north, and east sides of the magnetometer, with a fixed detection distance (e.g., 5.0 meters). The orientation of the unexploded bomb model was adjusted to 0°, 90°, 180°, and 270°, resulting in four measurements in each direction. Magnetic anomalies of the unexploded bomb model were collected under different conditions. Based on the magnetic moment processing model, the individual magnetic moment components of the unexploded bomb model were calculated. Throughout the acquisition process, the magnetometer position and attitude remained unchanged, while diurnal geomagnetic variations were measured simultaneously.

[0029] The magnetic moment of the unexploded bomb model can be solved from the above measured values, completing the modeling of the magnetic model characteristics of the unexploded bomb. Finally, the magnetic moment of the unexploded bomb is calculated according to the following formula:

[0030]

[0031]

[0032]

[0033]

[0034] in, 、 are the longitudinal induction and fixed magnetic moment in the geomagnetic coordinate system, 、 are the transverse induction and fixed magnetic moment in the geomagnetic coordinate system, r is the distance from the model to the magnetometer, Represents the magnetic anomaly value when located south of the magnetometer and the model orientation is 0°, S is south, W is west, N is north, and E is east. The model orientation includes 0°, 90°, 180°, and 270°. I is the geomagnetic inclination.

[0035] Based on the magnetic moment parameters obtained from the experiment and the spatial distribution characteristics of the magnetic dipole, the magnetic field of the unexploded bomb model was simulated. The minimum and maximum distances between the mine and the magnetic gradiometer were determined based on the height of the magnetic gradiometer from the bottom and the maximum detection distance of the magnetometer during actual marine magnetic detection. Multiple linear paths were selected at equal intervals within this distance range in the magnetic field distribution generated by the MK-25 bottom mine to obtain the magnetic field signal curves on the paths, i.e., magnetic anomalies. A sample library of mine magnetic anomalies was established based on the magnetic anomalies along all paths of the MK-25 bottom mine, such as Figure 5 shown.

[0036] Furthermore, based on the matching of the signal curves of each magnetic anomaly in the preliminary 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 preliminary screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, and the signal curves in the preliminary screening magnetic anomaly data with the similarity greater than a preset threshold are used as magnetic field anomaly signal curves.

[0037] Specifically, each magnetic anomaly in the initial screening magnetic anomaly data is compared with each magnetic anomaly in the mine magnetic anomaly sample library, the similarity between the two is measured, and the magnetic anomalies that cannot be well matched in the initial screening magnetic anomaly data are eliminated.

[0038] More specifically, the two curves are first aligned and matched based on the characteristic points on the magnetic anomaly curves. Considering that the typical morphology of the magnetic dipole is generally manifested as a relatively common single peak, double peak and uncommon triple peak morphology, a maximum or minimum value that deviates from the mean of the curve is used as the alignment feature point. The position and shape of one magnetic anomaly curve are changed by rotation, scaling and translation operations to make it as similar as possible to the other magnetic anomaly curve. The parameter-adaptive Minkowski distance is used to calculate the similarity between the two magnetic anomaly curves, as shown in the following example: Figure 6 shown.

[0039] Step S3: Calculate the buried depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screen the magnetic anomaly signal curve to obtain an initial suspected lightning point.

[0040] The main purpose of this step is to estimate burial depth and perform burial depth screening. Specifically, in the first step, the signal mean of the maximum and minimum points on the magnetic anomaly signal curve is obtained. The location of the signal mean is marked on the magnetic anomaly signal curve as a marker point. In the second step, 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 of the first and second distances is used as the half-point distance. In the third step, the burial depth of the magnetic anomaly object is determined based on the half-point distance and the burial depth inversion model.

[0041] As a specific example, the magnetic field signal curve of each magnetic anomaly in the initial screening magnetic anomaly data is used to find a point x 1 / 2 , which is also the marking point, making 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 can be expressed as:

[0042] This point x 1 / 2 and 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 is defined as the half-value point distance dx, and 2.1×dx is used as the actual burial depth of the object that produces 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 conducted, and it is believed that the settlement of mines on the seabed will not exceed 2 cm per year, and the total depth will not exceed 5 m, and anomalies that are buried too deep are excluded.

[0043] Step S4, calculating the mass of the ferromagnetic object that generates each magnetic anomaly based on the underwater target magnetic anomaly intensity calculation formula, screening the initial suspected lightning points according to the mass, and determining the suspected lightning points.

[0044] The main purpose of this step is to estimate the mass and perform mass screening. According to the magnetic field signal of each magnetic anomaly in the initial screening magnetic anomaly data, the mass of the ferromagnetic object that produces each magnetic anomaly is calculated based on the underwater target magnetic anomaly intensity calculation formula. The underwater target magnetic anomaly intensity calculation formula adopts:

[0045] Where 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 inferred from the magnetic anomaly intensity calculation formula. According to the G-882 Marine Magnetometer Operation Manual, a 450kg aerial bomb produces a magnetic anomaly intensity of 1.0nT at 30 meters, and its mass magnetization is 6×105CGSM(m) / t. This value is comparable to the mass magnetization of common ferromagnetic materials. Based on this value, magnetic anomalies that do not meet the mass requirements of the MK-25 bottom mine are eliminated.

[0046] After the above processing, the magnetic anomalies that are not eliminated in the initial screening of magnetic anomaly data are regarded as suspected thunder points.

[0047] Step S5: Obtain the identification result of the submarine unexploded bomb based on the shape, size and burial state of the object at the location of the suspected mine point.

[0048] Synthetic aperture sonar is used to scan each suspected mine point to accurately locate the suspected mine point. Typical data include Figure 7 As shown in the figure, the shallow layer profile method is used to scan the suspected mine point location and the surrounding area with multiple cross-line survey lines to determine the shape, size and burial status of the object at the suspected mine point. It is determined that its shape and size are consistent with the MK-25 bottom mine. Typical data are as follows Figure 8 The final results of the suspected lightning points in the survey area are shown in the figure below. Figure 9 shown.

[0049] The present invention also provides a submarine unexploded bomb identification system based on multi-source data, comprising: The data acquisition and preliminary screening module is used to collect seabed multi-source detection data, and obtain preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing; 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 model, match each preliminary screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library, and obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library; A burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screens the magnetic anomaly signal curve to obtain an initial suspected minepoint; The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the underwater target magnetic anomaly intensity calculation formula, and to screen the initial suspected lightning points according to the mass to determine the suspected lightning points; The refined verification module is used to obtain the identification results of unexploded bombs on the seabed based on the shape, size and burial status of the object at the location of the suspected mine point.

[0050] A system for identifying submarine unexploded ordnance based on multi-source data is used to execute the steps of a method for identifying submarine unexploded ordnance based on multi-source data. Since the method embodiment has been described in detail, it will not be described in detail here.

[0051] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for identifying submarine unexploded bombs based on multi-source data, characterized in that: The method comprises the following steps: Collect seabed multi-source detection data, and obtain preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing; A mine magnetic anomaly sample library is established based on the magnetic anomaly conditions corresponding to the mine model. The initial screening magnetic anomaly data are matched with the magnetic anomaly conditions in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library. Calculating the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screening the magnetic anomaly signal curve to obtain an initial suspected mine point; The mass of the ferromagnetic object that generates each magnetic anomaly is calculated based on the underwater target magnetic anomaly intensity calculation formula, and the initial suspected lightning points are screened according to the mass to determine the suspected lightning points; The identification results of unexploded bombs on the seabed are obtained based on the shape, size and burial status of the objects at the location of the suspected minepoints.

2. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The method for acquiring the multi-source detection data is specifically as follows: Multi-beam measurements are used to determine whether there are large exposed unexploded bombs on the seabed and the overall terrain conditions, and to identify low-lying areas on the seabed. For low-lying areas on the seabed, side-scan sonar is used to screen for small unexploded bombs on the seabed, and full-coverage marine magnetic detection is conducted to obtain total field data.

3. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The method of obtaining preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on seabed multi-source detection data and preprocessing specifically includes: The total field data is sequentially subjected to jump point deletion, height correction and nonlinear filtering to obtain background field data, and the background field data is subtracted from the total field data to obtain the residual field data; The linear or zonal magnetic anomalies corresponding to the geological structure positions shown by the multi-beam measurement data in the remaining field data are eliminated to obtain the preliminary screening magnetic anomaly data.

4. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The method of establishing a mine magnetic anomaly sample library based on the magnetic anomaly conditions corresponding to the mine models specifically includes: Obtain the spatial magnetic field distribution of various types of mines; The minimum and maximum distances between the mine and the magnetic gradiometer are determined based on the height of the magnetic gradiometer from the bottom and the maximum detection distance of the magnetometer during actual marine magnetic detection, forming a distance range. A plurality of linear paths are equally spaced within the distance range in the spatial magnetic field distribution of each type of mine, and 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.

5. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The method of matching each preliminary screening magnetic anomaly data with each magnetic anomaly situation 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 preliminary 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 preliminary screening magnetic anomaly data and the signal curves of each magnetic anomaly in the mine magnetic anomaly sample library, and the signal curves in the preliminary screening magnetic anomaly data with the similarity greater than a preset threshold are used as magnetic field anomaly signal curves.

6. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The calculating the buried depth of the magnetic anomaly object according to the magnetic anomaly signal curve data specifically includes: Obtain the signal mean of the maximum value point and the minimum value point on the magnetic anomaly signal curve, and mark the position of the signal mean on the magnetic anomaly signal curve as a marked point; The horizontal axis distance between the obtained mark point and the maximum value point on the magnetic anomaly signal curve is recorded as the first distance, the horizontal axis distance between the obtained mark point and the minimum value point on the magnetic anomaly signal curve is recorded as the second distance, and the minimum value of 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 and the burial depth inversion model.

7. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, characterized in that: The calculation formula for the underwater target magnetic anomaly intensity is specifically: 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 submarine unexploded bomb identification system based on multi-source data, characterized by: The system is used to implement the steps of a method for identifying submarine unexploded ordnance based on multi-source data as described in any one of claims 1 to 7. The submarine unexploded ordnance identification system based on multi-source data comprises: The data acquisition and preliminary screening module is used to collect seabed multi-source detection data, and obtain preliminary screening magnetic anomaly data representing seabed surface magnetic anomalies based on the seabed multi-source detection data and preprocessing; 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 model, match each preliminary screening magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library, and obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library; A burial depth screening module calculates the burial depth of the magnetic anomaly object based on the magnetic anomaly signal curve data, and re-screens the magnetic anomaly signal curve to obtain an initial suspected minepoint; The mass screening module is used to calculate the mass of the ferromagnetic objects that generate each magnetic anomaly based on the underwater target magnetic anomaly intensity calculation formula, and to screen the initial suspected lightning points according to the mass to determine the suspected lightning points; The refined verification module is used to obtain the identification results of unexploded bombs on the seabed based on the shape, size and burial status of the object at the location of the suspected mine point.

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