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CN120703852A - A method and system for identifying submarine unexploded bombs based on multi-source data - Google Patents

A method and system for identifying submarine unexploded bombs based on multi-source data

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Publication number
CN120703852A
CN120703852A CN202511165605.0A CN202511165605A CN120703852A CN 120703852 A CN120703852 A CN 120703852A CN 202511165605 A CN202511165605 A CN 202511165605A CN 120703852 A CN120703852 A CN 120703852A
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magnetic
magnetic anomaly
data
mine
anomaly
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CN120703852B (en
Inventor
孙运坤
陈美�
郭增卿
孙淼军
张昆
金忠良
徐建
李广场
张雷
陈益茂
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Zhejiang East China Geotechnical Survey And Design Institute Co ltd
PowerChina Huadong Engineering Corp Ltd
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Zhejiang East China Geotechnical Survey And Design Institute Co ltd
PowerChina Huadong Engineering Corp Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V3/00—Electric or magnetic prospecting or detecting; Measuring magnetic field characteristics of the earth, e.g. declination, deviation
    • G01V3/38—Processing data, e.g. for analysis, for interpretation, for correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/30—Assessment of water resources

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  • Physics & Mathematics (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Geophysics (AREA)
  • Engineering & Computer Science (AREA)
  • Environmental & Geological Engineering (AREA)
  • Geology (AREA)
  • Remote Sensing (AREA)
  • Geophysics And Detection Of Objects (AREA)

Abstract

本发明涉及海底检测技术领域，具体涉及一种基于多源数据的海底未爆弹识别方法及系统，包括：海底面多源探测数据获取与磁异常初筛；基于水雷磁矩建模的疑似雷点磁异常筛选；疑似雷点预估埋深筛选；疑似雷点预估重量筛选；疑似雷点精细化验证。方法根据获得的未爆弹磁异常数据进行初步筛选，并结合浅地层剖面数据、侧扫声纳数据、合成孔径声呐数据等地质信息、水雷建模与磁异常匹配算法、预估埋深与预估重量筛选方法等，实现非未爆弹磁异常剔除，最终通过磁法加密探测方法精细化验证，实现未爆弹判识与定位。

The present invention relates to the field of seabed detection technology, and specifically to a method and system for identifying submarine unexploded ordnance based on multi-source data. The system includes: acquiring multi-source seabed detection data and initial screening of magnetic anomalies; screening of magnetic anomalies at suspected mine sites based on mine magnetic moment modeling; screening of estimated depths of suspected mine sites; screening of estimated weights of suspected mine sites; and detailed verification of suspected mine sites. The method performs preliminary screening based on acquired magnetic anomaly data for unexploded ordnance. It then combines geological information such as shallow stratum profile data, side-scan sonar data, and synthetic aperture sonar data, with mine modeling and magnetic anomaly matching algorithms, as well as methods for screening estimated depths and estimated weights, to eliminate magnetic anomalies that are not unexploded ordnance. Finally, through detailed verification using magnetic encryption detection methods, unexploded ordnance identification and location are achieved.

Description

Submarine non-explosive identification method and system based on multi-source data
Technical Field
The invention relates to the technical field of submarine detection, in particular to a submarine non-explosive bomb identification method and system based on multi-source data.
Background
The site selected by the offshore wind power project may coincide with a suspected lightning storage area defined at sea, the existence of the nonexploited bomb threatens the safe construction of the offshore wind power plant, and the nonexploited bomb position of the suspected lightning storage area needs to be ascertained in advance, so that lightning discharge work can be developed in a targeted manner. Currently, the nonexploited bombs in the offshore suspected lightning storage area are mostly detected by adopting a marine magnetometer, and the method can receive the magnetic response, namely the magnetic abnormality, of ferromagnetic objects buried at the bottom of the sea. However, the method has the defects that on one hand, a feasible data processing means and a judging method do not exist for the problem that whether the magnetic abnormality is generated by the nonexplosive in the obtained magnetic method data, and on the other hand, the ocean magnetic method only utilizes the ferromagnetism of an object to detect, so that the detection means is single and the polynary is strong, and the accuracy of nonexplosive judgment is limited.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a submarine non-explosive identification method and a submarine non-explosive identification system based on multi-source data, and the adopted technical scheme is as follows:
in a first aspect, the invention provides a method for identifying a submarine non-explosive bomb based on multi-source data, which comprises the following steps:
Acquiring submarine multisource detection data, and acquiring primary screening magnetic anomaly data representing magnetic anomalies of the seabed based on the submarine multisource detection data and preprocessing;
establishing a mine magnetic anomaly sample library based on the magnetic anomaly condition corresponding to the mine type, and matching the mine magnetic anomaly sample library according to the primary screening magnetic anomaly data and the magnetic anomaly condition in the mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve matched with the mine magnetic anomaly sample library;
Calculating the burial depth of the magnetic anomaly object according to the magnetic anomaly signal curve data, and screening the magnetic anomaly signal curve again to obtain an initial suspected lightning point;
Calculating the quality of a ferromagnetic object generating each magnetic anomaly based on an underwater target magnetic anomaly intensity calculation formula, screening initial suspected radar points according to the quality, and determining the suspected radar points;
And obtaining the identification result of the seabed nonexplosive bomb according to the shape, the size and the burying state of the object at the position of the suspected lightning point.
Preferably, the method for acquiring the multi-source detection data specifically includes:
And for the low-lying area of the sea bottom surface topography, checking the small-sized non-detonated bombs of the sea bottom surface based on side scan sonar, and performing full-coverage ocean magnetic method detection to obtain total field data.
Preferably, the acquiring the preliminary screening magnetic anomaly data representing the magnetic anomalies of the sea floor based on the submarine multisource detection data and the preprocessing specifically comprises:
Sequentially performing skip point deletion, altitude correction and nonlinear filtering on the total field data to obtain background field data, and subtracting the background field data from the total field data to obtain residual field data;
and eliminating linear or band-shaped distributed magnetic anomalies corresponding to the geological structure positions displayed by the multi-beam measurement data in the residual field data to obtain primary screening magnetic anomaly data.
Preferably, the establishing a mine magnetic anomaly sample library based on the magnetic anomaly condition corresponding to the mine model specifically includes:
acquiring the spatial magnetic field distribution of various mines;
determining the minimum distance and the maximum distance between the mine and the magnetic gradiometer according to the off-bottom height of the magnetic gradiometer and the maximum detection distance of the magnetometer in the actual ocean magnetic method detection process, and forming a distance range;
And selecting a plurality of linear paths at equal intervals in the distance range in the spatial magnetic field distribution of each type of mine, obtaining magnetic field signal curves on the paths, and establishing a mine magnetic anomaly sample library based on the magnetic field signal curves on all paths of each type of mine.
Preferably, the matching is performed according to the magnetic anomaly data of each primary screen and each magnetic anomaly condition in the mine magnetic anomaly sample library, so as to obtain a magnetic anomaly signal curve matched with the mine magnetic anomaly sample library, which specifically comprises:
And (3) based on 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 water mine magnetic anomaly sample library, calculating Minkowski distance, obtaining 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 water mine magnetic anomaly sample library, and taking the signal curves in the preliminary screening magnetic anomaly data with the similarity larger than a preset threshold value as magnetic field anomaly signal curves.
Preferably, the calculating the burial depth of the magnetic anomaly object according to the magnetic anomaly signal curve data specifically includes:
Acquiring signal average values of maximum value points and minimum value points on a magnetic anomaly signal curve, and determining the position of the marked signal average value on the magnetic anomaly signal curve as a marked point;
The method comprises the steps of obtaining a first distance from a transverse axis between a mark point and a maximum value point on a magnetic abnormal signal curve, obtaining a second distance from the transverse axis between the mark point and a minimum value point on the magnetic abnormal signal curve, and taking the minimum value of the first distance and the second distance as a half value point distance;
And obtaining the buried depth of the magnetic anomaly object based on the half-value point distance combined with the buried depth inversion model.
Preferably, the calculation formula of the magnetic anomaly intensity of the underwater target is specifically as follows:
Wherein DeltaT is the abnormal intensity of magnetism, kappa is the magnetizing intensity of mass, m is the mass, and r is the detection distance.
In a second aspect, the present invention provides a multi-source data-based subsea non-explosive bomb identification system for implementing the steps of a multi-source data-based subsea non-explosive bomb identification method, the multi-source data-based subsea non-explosive bomb identification system comprising:
The data acquisition and primary screening module is used for acquiring submarine multisource detection data, and acquiring primary screening magnetic anomaly data representing magnetic anomalies of the seabed based on the submarine multisource detection data and preprocessing;
The magnetic anomaly matching module is used for establishing a mine magnetic anomaly sample library based on the magnetic anomaly condition corresponding to the mine type, and matching the magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library according to each primary screening magnetic anomaly data to obtain a magnetic anomaly signal curve matched with the mine magnetic anomaly sample library;
The buried depth screening module calculates the buried depth of the magnetic anomaly object according to the magnetic anomaly signal curve data, and screens the magnetic anomaly signal curve again to obtain an initial suspected lightning point;
The quality screening module is used for calculating the quality of the ferromagnetic object generating each magnetic anomaly based on the calculation formula of the magnetic anomaly intensity of the underwater target, screening the initial suspected radar points according to the quality, and determining the suspected radar points;
And the refinement verification module is used for obtaining the identification result of the seabed nonexplosive bomb according to the shape, the size and the burial state of the object at the position of the suspected lightning point.
The embodiment of the invention has at least the following beneficial effects:
The method is based on geological priori, magnetic anomaly signal waveform, quality and buried depth multi-angle screening of the magnetic anomaly signals, and can eliminate a large number of non-nonexplosive elasto-magnetic anomalies in marine magnetic data. Aiming at the problems that the current detection of the non-explosive bomb at sea is only detected by a single means of a marine magnetic method, the multi-resolution is high and the accuracy of the determination of the non-explosive bomb is limited, the advantages of each sea detection method such as side-scan sonar, marine magnetic method and synthetic aperture sonar are exerted, the suspected radar points are screened and accurately positioned according to the multi-scale topography, size and shape of the seabed by combining multi-source data, and the comprehensive detection of the non-explosive bomb at the seabed is realized.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for identifying a subsea non-explosive bomb based on multi-source data;
FIG. 2 is a plot of a region obtained via multi-beam measurements provided by the present invention;
FIG. 3 is a submarine imaging result obtained by the side scan sonar provided by the invention;
FIG. 4 is a schematic diagram of the invention for removing linear or banded distribution of geologic structures from residual fields;
FIG. 5 is a schematic diagram of a mine magnetic anomaly sample library provided by the invention;
FIG. 6 is a schematic diagram of a comparison of one magnetic anomaly in the prescreened magnetic anomaly data provided by the present invention with a magnetic anomaly curve in a mine magnetic anomaly sample library;
FIG. 7 is an imaging result of a synthetic aperture sonar in a suspected radar point refinement verification process provided by the invention;
FIG. 8 is an imaging result of a shallow formation profile method in a suspected radar point refinement verification process provided by the invention;
Fig. 9 is a diagram of the final determined result of suspected radar points in the area provided by the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of a submarine non-explosive identification method and system based on multi-source data according to the invention, and the detailed implementation, structure, characteristics and effects thereof are as follows. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
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.
The invention provides a submarine non-explosive identification method and a submarine non-explosive identification system based on multi-source data, which are specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of steps of a method for identifying a subsea non-explosive bomb based on multi-source data according to an embodiment of the present invention is shown, the method includes the following steps:
Step S1, acquiring submarine multisource detection data, and acquiring preliminary screening magnetic anomaly data representing magnetic anomalies of the seabed based on the submarine multisource detection data and preprocessing.
The main purpose of the step is to comprehensively detect the sea bottom and acquire multi-source data, and specifically comprises the steps of determining whether the sea bottom has large exposed nonexplosive bombs and integral topography based on multi-beam measurement, and determining the low-lying area of the sea bottom topography, wherein the topography data of the integral area is shown in fig. 2. For small non-explosive cartridges of the sea bottom surface based on side scan sonar investigation in low-lying areas of the sea bottom surface topography, typical imaging data are shown in fig. 3. And carrying out full-coverage ocean magnetic detection to obtain magnetic anomaly data, namely total field data, generated by the seafloor surface superimposed on the seafloor geomagnetic background field and all buried ferromagnetic objects in the region.
And then, removing the submarine geomagnetic background field in the total field data to obtain data only containing magnetic anomalies generated by all ferromagnetic objects, namely residual field data. That is, the total field data is sequentially subjected to skip point deletion, altitude correction and nonlinear filtering to obtain background field data, and the background field data is subtracted from the total field data to obtain residual field data.
The method comprises the steps of performing jump point elimination in magnetic method data, namely performing jump point elimination and interpolation on each measuring line positioning data, performing jump point elimination and interpolation on off-bottom height data, performing off-bottom height correction on the magnetic method data in the second step, and reducing the magnetic method data to magnetic method data at a uniform off-bottom height of 5m, performing nonlinear filtering on the magnetic field data subjected to the height correction in the third step, wherein the size of a filter is set to be 30, the threshold value is 0.1-1, background field data is obtained, and primary magnetic field data is subtracted from the background field to obtain primary screening magnetic abnormal data.
Furthermore, after the residual field data are obtained, the magnetic anomalies generated by the known non-nonexplosive bombs exposed on the seabed surface in the residual field data can be removed according to the multi-beam topographic survey data and the ferromagnetic objects exposed on the seabed surface and displayed in the side scan sonar data, the obvious linear or strip-shaped distributed magnetic anomalies corresponding to the geological structure position displayed by the multi-beam survey data in the primary screening magnetic anomaly data are removed to obtain primary screening magnetic anomaly data, the interference generated by the geological structure is removed, all the magnetic anomaly data in the total magnetic field data are screened, the accidental magnetic anomalies caused by instrument noise, environmental interference, topographic variation and the like are removed, and the primary screening magnetic anomaly data representing the magnetic anomalies on the seabed surface are obtained, as shown in fig. 4.
And S2, establishing a mine magnetic anomaly sample library based on the magnetic anomaly condition corresponding to the mine type, and matching the magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library according to each primary screening magnetic anomaly data to obtain a magnetic anomaly signal curve matched with the mine magnetic anomaly sample library.
The method comprises the steps of obtaining space magnetic field distribution of each type of mine, determining minimum distance and maximum distance between the mine and the magnetic gradiometer according to the bottom-off height of the magnetic gradiometer and the maximum detection distance of the magnetometer in the actual ocean magnetic method detection process to form a distance range, selecting a plurality of linear paths at equal intervals in the distance range in the space magnetic field distribution of each type of mine to obtain magnetic field signal curves on the paths, and establishing a mine magnetic anomaly sample library based on the magnetic field signal curves on all paths of each type of mine.
As a specific example, the present embodiment is described taking a solid model for making an MK-25 undersea as an example, measuring magnetic moment parameters of the obtained undersea, and simulating the spatial magnetic field distribution of the MK-25 undersea by magnetic field forward modeling. Magnetic moment of nonexplosive bombConsisting of the following parts, namely, the longitudinal component along the axial direction of the nonexplosive bomb isThe transverse component isThe vertical component isThe geomagnetic meridian plane is taken as a reference plane to establish a geomagnetic coordinate system, the magnetocaloric north is taken as an x direction, the geomagnetic east is taken as a y direction, and the z direction is vertically downward.
Is provided with、Respectively longitudinal induction and fixed magnetic moment under a geomagnetic coordinate system,、For transverse induction and fixed magnetic moment in the geomagnetic coordinate system,In order to synthesize the magnetic moment in the vertical direction,The geomagnetic declination is:
Wherein, the Representing the longitudinal component along the axis of the mine,Representing a transverse component along the axis of the mine,Representing the vertical component along the mine axis.
The non-explosive bomb models are sequentially placed on the south side, the west side, the north side and the east side of the magnetic detector, the detection distance is set to be a fixed distance (for example, 5.0 meters), the orientations of the non-explosive bomb models are sequentially adjusted to be 0 degrees, 90 degrees, 180 degrees and 270 degrees, and 4 times of data are measured in each direction. And acquiring magnetic anomalies of the non-explosive model in different states, and calculating each magnetic moment component of the non-explosive model according to the magnetic moment processing model. In the whole acquisition process, the position and the posture of the magnetometer are kept unchanged, and geomagnetic daily variation measurement is synchronously carried out.
The magnetic moment of the non-explosive bomb model can be solved from the measured value, and (5) completing the characteristic modeling of the nonexplosive elasto-magnetic model. Finally, calculating the magnetic moment of the nonexplosive bomb according to the formula as follows:
Wherein, the 、Respectively longitudinal induction and fixed magnetic moment under a geomagnetic coordinate system,、Respectively the transverse induction and fixed magnetic moment under the geomagnetic coordinate system, r is the distance from the model to the magnetometer,Representing the magnetic anomaly value when the model orientation is 0 DEG in the south of the magnetometer, S is the south, W is the west, N is the north, E is the east, the model orientation comprises 0 DEG, 90 DEG, 180 DEG and 270 DEG, and I is the geomagnetic inclination angle.
And according to the magnetic moment parameters obtained through experiments, performing magnetic field simulation on the non-explosive bomb model through the spatial distribution characteristics of magnetic dipoles. And determining the minimum distance and the maximum distance between the mine and the magnetic gradiometer according to the off-bottom height of the magnetic gradiometer and the maximum detection distance of the magnetometer in the actual ocean magnetic method detection process, selecting a plurality of linear paths at equal intervals within the distance range in the magnetic field distribution generated by the MK-25 mine, obtaining a magnetic field signal curve on the paths, namely magnetic anomalies, and establishing a mine magnetic anomaly sample library based on the magnetic anomalies on all paths of the MK-25 mine, as shown in figure 5.
Further, based on 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 water mine magnetic anomaly sample library, the Minkowski distance is calculated, 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 water mine magnetic anomaly sample library is obtained, and the signal curves in the preliminary screening magnetic anomaly data with the similarity larger than a preset threshold value are used as magnetic field anomaly signal curves.
Specifically, comparing each magnetic anomaly in the preliminary screening magnetic anomaly data with each magnetic anomaly in the mine magnetic anomaly sample library, measuring the similarity of the two magnetic anomalies, and eliminating the magnetic anomalies which cannot be well matched in the preliminary screening magnetic anomaly data.
More specifically, firstly, alignment matching is performed on two curves based on characteristic points on a magnetic anomaly curve, and considering that the typical form of a magnetic dipole generally shows relatively common unimodal, bimodal and unusual trimodal forms, a maximum value or a minimum value deviating from the mean value of the curves is taken as the aligned characteristic point, the position and the shape of one magnetic anomaly curve are changed through rotation, scaling and translation operations so as to be similar to the other magnetic anomaly curve as much as possible, and the similarity between the two magnetic anomaly curves is calculated by adopting a parameter-adaptive minkowski distance, as shown in fig. 6.
And S3, calculating the burial depth of the magnetic anomaly object according to the magnetic anomaly signal curve data, and screening the magnetic anomaly signal curve again to obtain an initial suspected lightning point.
The main purpose of this step is to estimate the buried depth and to carry out the buried depth screening, specifically, in the first step, the signal mean value of the maximum value point and the minimum value point on the magnetic anomaly signal curve is obtained, and the position of the marked signal mean value on the magnetic anomaly signal curve is determined as the marked point. And secondly, acquiring a transverse axis distance between the mark point and a maximum value point on the magnetic anomaly signal curve as a first distance, acquiring a transverse axis distance between the mark point and a minimum value point on the magnetic anomaly signal curve as a second distance, and taking the minimum value of the first distance and the second distance as a half value point distance. And thirdly, obtaining the buried depth of the magnetic anomaly object based on the half-value point distance combined with the buried depth inversion model.
As a specific example, the magnetic field signal curve of each magnetic anomaly in the preliminary screening magnetic anomaly data finds a point x 1/2, i.e., a marker point, whose magnetic field T 1/2 is equal to the algebraic average of the maxima T max and minima T min of the magnetic anomaly signal curve, which can be expressed as:
The distance between the point x 1/2 and the maximum point x max is dx max=x1/2-xmax, the distance between the point x 1/2 and the minimum point x min is dx min=x1/2-xmin, the smaller point is defined as half-value point distance dx, 2.1 x dx is taken as the actual burial depth of an object generating the magnetic anomaly, the verification error is less than 5%, theoretical deduction is carried out according to data acquired from a local sea area, the settlement of the mine at the sea bottom is not more than 2cm each year, the total depth is not more than 5m, and the anomaly with the burial depth being too deep is eliminated.
And S4, calculating the mass of the ferromagnetic object generating each magnetic anomaly based on an underwater target magnetic anomaly intensity calculation formula, screening the initial suspected radar points according to the mass, and determining the suspected radar points.
The main purpose of this step is to estimate the quality and carry out the quality screening, according to the magnetic field signal of each magnetic anomaly in the preliminary screening magnetic anomaly data, calculate the ferromagnetic object quality producing each magnetic anomaly based on the underwater target magnetic anomaly intensity calculation formula, the underwater target magnetic anomaly intensity calculation formula adopts:
wherein DeltaT is the abnormal magnetic intensity, the unit is nT, kappa is the mass magnetization, the unit is CGSM (m)/T, m is the mass, r is the detection distance, the unit is meter, and the mass of the abnormal magnetic object is reversely deduced according to the abnormal magnetic intensity calculation formula. According to the description in the G-882 ocean magnetometer operating manual, the magnetic anomaly intensity generated by 450kg of aerial bullets at 30 meters is 1.0nT, the mass magnetization intensity is6 multiplied by 105CGSM (m)/t, the value is equivalent to the mass magnetization intensity of common ferromagnetic substances, and the magnetic anomaly which does not meet the mass of MK-25 undersea is eliminated based on the magnetic anomaly intensity.
After the processing, the magnetic anomalies which are not removed in the preliminary screening magnetic anomaly data are used as suspected lightning points.
And S5, obtaining the identification result of the seabed nonexplosive bomb according to the shape, the size and the buried state of the object at the position of the suspected lightning point.
And scanning the suspected lightning points, namely, arranging a plurality of measuring lines around the suspected lightning points in a crossing way by adopting a shallow stratum profile method, determining the shape, the size and the buried state of an object at the suspected lightning points, judging that the shape and the size of the object accord with MK-25 bottom mine, and typical data are shown in FIG. 8. The final result diagram of the suspected radar points in the determined area is shown in fig. 9.
The invention also provides a submarine non-explosive bomb identification system based on the multi-source data, which comprises the following steps:
The data acquisition and primary screening module is used for acquiring submarine multisource detection data, and acquiring primary screening magnetic anomaly data representing magnetic anomalies of the seabed based on the submarine multisource detection data and preprocessing;
The magnetic anomaly matching module is used for establishing a mine magnetic anomaly sample library based on the magnetic anomaly condition corresponding to the mine type, and matching the magnetic anomaly data with each magnetic anomaly condition in the mine magnetic anomaly sample library according to each primary screening magnetic anomaly data to obtain a magnetic anomaly signal curve matched with the mine magnetic anomaly sample library;
The buried depth screening module calculates the buried depth of the magnetic anomaly object according to the magnetic anomaly signal curve data, and screens the magnetic anomaly signal curve again to obtain an initial suspected lightning point;
The quality screening module is used for calculating the quality of the ferromagnetic object generating each magnetic anomaly based on the calculation formula of the magnetic anomaly intensity of the underwater target, screening the initial suspected radar points according to the quality, and determining the suspected radar points;
And the refinement verification module is used for obtaining the identification result of the seabed nonexplosive bomb according to the shape, the size and the burial state of the object at the position of the suspected lightning point.
Wherein, a seabed nonexplosive identification system based on multi-source data is used for executing the steps of a seabed nonexplosive identification method based on multi-source data, and since the embodiments of the method have been described in detail, the description is not repeated here.
Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the foregoing embodiments may be modified or equivalents may be substituted for some of the features thereof, and that the modification or substitution does not depart from the scope of the embodiments of the present application.

Claims (8)

1.一种基于多源数据的海底未爆弹识别方法，其特征在于，该方法包括以下步骤：1. A method for identifying submarine unexploded ordnance based on multi-source data, characterized in that the method comprises the following steps: 采集海底多源探测数据，基于海底多源探测数据以及预处理，获取表征海底面磁异常的初筛磁异常数据；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; 基于水雷型号对应的磁异常情况建立水雷磁异常样本库，根据各初筛磁异常数据与水雷磁异常样本库中各磁异常情况进行匹配，获得与水雷磁异常样本库匹配的磁异常信号曲线；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. 根据所述磁异常信号曲线数据计算磁异常物体的埋藏深度，对所述磁异常信号曲线进行再次筛选获得初始疑似雷点；Calculating the buried 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; 基于水下目标磁异常强度计算公式计算产生各磁异常的铁磁性物体的质量，根据质量对初始疑似雷点进行筛选，确定疑似雷点；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; 根据疑似雷点所在位置处物体的形状、大小与埋藏状态，获得海底未爆弹的识别结果。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.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述多源探测数据的获取方法具体为：2. The method for identifying submarine unexploded ordnance based on multi-source data according to claim 1, wherein the multi-source detection data is obtained by: 基于多波束测量确定海底面是否有大型裸露未爆弹与整体地形情况，确定海底面地势低洼区域；对于海底面地势低洼区域，基于侧扫声呐排查海底面的小型未爆弹，进行全覆盖的海洋磁法探测获得总场数据。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.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述基于海底多源探测数据以及预处理，获取表征海底面磁异常的初筛磁异常数据，具体包括：3. The method for identifying submarine unexploded ordnance based on multi-source data according to claim 1, wherein the method comprises: obtaining preliminary screening magnetic anomaly data representing submarine surface magnetic anomalies based on the submarine multi-source detection data and preprocessing the data; 对总场数据依次进行跳点删除、高度校正和非线性滤波后得到背景场数据，将总场数据减去背景场数据得到剩余场数据；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; 对剩余场数据中与多波束测量数据显示的地质构造位置对应的线状或带状分布的磁异常进行剔除，得到初筛磁异常数据。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.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述基于水雷型号对应的磁异常情况建立水雷磁异常样本库，具体包括：4. The method for identifying submarine unexploded ordnance based on multi-source data according to claim 1, wherein establishing a mine magnetic anomaly sample library based on magnetic anomalies corresponding to mine models specifically comprises: 获取各型号水雷的空间磁场分布；Obtain the spatial magnetic field distribution of various types of mines; 根据实际海洋磁法探测过程中磁梯度仪的离底高度与磁力仪最大探测距离确定水雷与磁梯度仪的最小距离与最大距离，构成距离范围；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. 在各型号水雷的空间磁场分布中所述距离范围内等间隔选择多条直线型路径，获得路径上的磁场信号曲线，基于各型号水雷全部路径上的磁场信号曲线建立水雷磁异常样本库。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.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述根据各初筛磁异常数据与水雷磁异常样本库中各磁异常情况进行匹配，获得与水雷磁异常样本库匹配的磁异常信号曲线，具体包括：5. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1 is characterized in that the step of matching each preliminary screening magnetic anomaly data with each magnetic anomaly in a mine magnetic anomaly sample library to obtain a magnetic anomaly signal curve that matches the mine magnetic anomaly sample library specifically comprises: 基于初筛磁异常数据中各个磁异常的信号曲线和水雷磁异常样本库中各个磁异常的信号曲线进行匹配，计算闵可夫斯基距离，获得初筛磁异常数据中个磁异常的信号曲线和水雷磁异常样本库中各个磁异常的信号曲线之间的相似度，将所述相似度大于预设阈值的初筛磁异常数据中的信号曲线作为磁场异常信号曲线。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.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述根据所述磁异常信号曲线数据计算磁异常物体的埋藏深度，具体包括：6. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, wherein the step of calculating the buried depth of the magnetic anomaly object based on the magnetic anomaly signal curve data comprises: 获取磁异常信号曲线上的极大值点和极小值点的信号均值，在磁异常信号曲线上标记信号均值所在位置确定为标记点；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; 获取标记点与磁异常信号曲线上极大值点之间的横轴距离记为第一距离，获取标记点与磁异常信号曲线上极小值点之间的横轴距离记为第二距离，将第一距离和第二距离中的最小值作为半值点距离；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; 基于半值点距离结合埋深反演模型，获得磁异常物体的埋藏深度。The burial depth of magnetic anomaly objects is obtained based on the half-value point distance and the burial depth inversion model. 7.根据权利要求1所述的一种基于多源数据的海底未爆弹识别方法，其特征在于，所述水下目标磁异常强度计算公式具体为：7. The method for identifying submarine unexploded bombs based on multi-source data according to claim 1, wherein the calculation formula for the magnetic anomaly intensity of underwater targets is: 其中，ΔT为磁异常强度，κ为质量磁化强度， m为质量，r为探测距离。Where ΔT is the magnetic anomaly intensity, κ is the mass magnetization intensity, m is the mass, and r is the detection distance. 8.一种基于多源数据的海底未爆弹识别系统，其特征在于，该系统用于实现如权利要求1-7任一项所述的一种基于多源数据的海底未爆弹识别方法的步骤，所述基于多源数据的海底未爆弹识别系统包括：8. A system for identifying underwater unexploded ordnance based on multi-source data, characterized in that the system is used to implement the steps of the method for identifying underwater unexploded ordnance based on multi-source data according to any one of claims 1 to 7, wherein the system comprises: 数据获取和初筛模块，用于采集海底多源探测数据，基于海底多源探测数据以及预处理，获取表征海底面磁异常的初筛磁异常数据；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; 磁异常匹配模块，用于基于水雷型号对应的磁异常情况建立水雷磁异常样本库，根据各初筛磁异常数据与水雷磁异常样本库中各磁异常情况进行匹配，获得与水雷磁异常样本库匹配的磁异常信号曲线；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; 埋深筛选模块，根据所述磁异常信号曲线数据计算磁异常物体的埋藏深度，对所述磁异常信号曲线进行再次筛选获得初始疑似雷点；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; 质量筛选模块，用于基于水下目标磁异常强度计算公式计算产生各磁异常的铁磁性物体的质量，根据质量对初始疑似雷点进行筛选，确定疑似雷点；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; 精细化验证模块，用于根据疑似雷点所在位置处物体的形状、大小与埋藏状态，获得海底未爆弹的识别结果。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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