Ocean gravity measurement error compensation method and system

Abstract

The present invention discloses a method and system for compensating ocean gravity measurement errors, belonging to the technical field of gravity measurement, and comprising the following steps: obtaining topographic parameters of a predicted ocean area and water flow fluctuation parameters of the predicted ocean area, and comprehensively analyzing to obtain a comprehensive complexity index of the predicted ocean area; obtaining an ocean gravity measurement constraint parameter set; obtaining an ocean gravity difference index, thereby matching to obtain an ocean gravity revision coefficient, synchronously obtaining ocean tide parameters and a preset ocean tide influence prediction model, and inputting the ocean tide parameters into the ocean tide influence prediction model to obtain an ocean tide influence index, thereby matching to obtain an ocean tide revision coefficient; obtaining an ocean gravity error revision coefficient, and analyzing an ocean gravity correction data set based on the ocean gravity error revision coefficient and an ocean gravity data set, solving the problem of inaccurate ocean gravity measurement caused by complex seabed topography and tidal fluctuation interference in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of gravity measurement, and particularly to a method and system for compensating errors in marine gravity measurement. Background Art

[0002] With the in-depth research of marine science, marine gravity measurement, as an important means for studying marine geology, seabed topography, and ocean current changes, has gradually become one of the key technologies for marine monitoring. Existing marine gravity measurement error correction systems are achieved through methods such as zero-drift compensation and horizontal acceleration error compensation.

[0003] For example, the method for improving the spatial resolution of marine gravity based on seabed topography-gravity combination disclosed in the invention patent announcement with the publication number CN113341476B includes: after performing height correction and intermediate layer correction on the normal gravity field of the geoid, obtaining the theoretical gravity value at the seabed control point; determining the relationship among the free-air gravity anomaly at the seabed control point, the gravity anomaly caused by water depth changes, and the free-air gravity anomaly on the geoid; obtaining the basic formula model of the seabed topography-gravity combination method; solving to obtain the absolute gravity value at discrete seabed control points; solving to obtain the gridded seabed absolute gravity value; through existing gridded high-precision seabed topography data and gravity correction, obtaining the seabed topography-gravity combination method model, and solving to obtain the gridded free-air gravity anomaly on the geoid.

[0004] For example, a method for processing gravity anomaly data applicable to a strapdown marine gravimeter disclosed in the invention patent announcement with the publication number CN106405670B includes: using a Kalman filter to estimate the attitude error in inertial navigation solution, correcting the attitude matrix and vertical specific force components to obtain more accurate specific force information, then calculating each gravity correction term from the position, velocity, and height information provided by PPP technology, and finally obtaining the gravity anomaly information along the route through low-pass filtering.

[0005] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0006] In the prior art, error compensation is only carried out through methods such as zero-drift compensation and horizontal acceleration error compensation. However, in the face of complex marine environments, these measures are still difficult to completely eliminate errors. In particular, factors such as the undulation of the seabed topography, the complexity of water flow fluctuations, and the periodic changes of tides will all have a significant impact on gravity measurement. Therefore, there is currently a problem of inaccurate marine gravity measurement caused by complex seabed topography and tidal fluctuation interference. Summary of the Invention

[0007] The embodiments of the present application provide a method and system for compensating ocean gravity measurement errors, which solve the problem of inaccurate ocean gravity measurement caused by complex seabed topography and tidal fluctuation interference in the prior art, and achieve accurate analysis of ocean gravity.

[0008] The embodiments of the present application provide a method for compensating ocean gravity measurement errors, including the following steps: obtaining the terrain parameters of the ocean area to be measured and the water flow fluctuation parameters of the ocean area to be measured, and comprehensively analyzing to obtain the comprehensive complexity index of the ocean area to be measured; analyzing based on the comprehensive complexity index of the ocean area to be measured to obtain a set of ocean gravity measurement constraint parameters; performing ocean gravity measurement based on the set of ocean gravity measurement constraint parameters to obtain an ocean gravity data set, analyzing to obtain an ocean gravity difference index, thereby matching to obtain an ocean gravity revision coefficient, synchronously obtaining ocean tide parameters and a preset ocean tide influence prediction model, and inputting the ocean tide parameters into the ocean tide influence prediction model to obtain an ocean tide influence index, thereby matching to obtain an ocean tide revision coefficient; analyzing based on the ocean tide revision coefficient and the ocean gravity revision coefficient to obtain an ocean gravity error revision coefficient, and analyzing based on the ocean gravity error revision coefficient and the ocean gravity data set to obtain an ocean gravity correction data set.

[0009] Further, the steps of obtaining the terrain parameters of the ocean area to be measured and the water flow fluctuation parameters of the ocean area to be measured, and comprehensively analyzing to obtain the comprehensive complexity index of the ocean area to be measured specifically include: obtaining the terrain parameters of the ocean area to be measured, where the terrain parameters of the ocean area to be measured include the average seabed slope, the extreme difference in seabed terrain height, the average thickness of the seabed rock layer, and the average hardness of the seabed rock layer; obtaining the water flow fluctuation parameters of the ocean area to be measured, where the water flow fluctuation parameters of the ocean area to be measured include the maximum water flow velocity, the extreme difference in water flow velocity, and the turbulence intensity at each screening point within a preset time period; obtaining a preset terrain reference set and a water flow fluctuation reference set in the database, and comparing them with the terrain parameters of the ocean area to be measured and the water flow fluctuation parameters of the ocean area to be measured respectively to obtain the comprehensive complexity index of the ocean area to be measured; the comprehensive complexity index of the ocean area to be measured is used to characterize the complexity of the ocean area to be measured; the terrain reference set includes a slope reference value, an extreme difference in terrain height reference value, a seabed rock layer thickness reference value, and a seabed rock layer hardness reference value; the water flow fluctuation reference set includes a water flow velocity reference value, an extreme difference in water flow velocity reference value, and a turbulence intensity reference value.

[0010] Further, the specific analysis steps for the comprehensive complexity index of the predicted ocean area include: analyzing based on the terrain parameters and terrain reference set of the predicted ocean area to obtain the terrain complexity index of the predicted ocean area; analyzing based on the water flow fluctuation parameters and water flow fluctuation reference set of the predicted ocean area to obtain the water flow fluctuation complexity index of the predicted ocean area; analyzing based on the terrain complexity index and water flow fluctuation complexity index of the predicted ocean area to obtain the comprehensive complexity index of the predicted ocean area; the terrain complexity index of the predicted ocean area is used to characterize the terrain complexity degree of the predicted ocean area; the water flow fluctuation complexity index of the predicted ocean area is used to characterize the water flow fluctuation complexity degree of the predicted ocean area.

[0011] Further, the specific steps for analyzing based on the comprehensive complexity index of the predicted ocean area to obtain the marine gravity measurement constraint parameter set include: obtaining each preset comprehensive complexity index interval and the corresponding marine gravity measurement constraint reference parameter set in the database, and comparing with the comprehensive complexity index of the predicted ocean area. If the comprehensive complexity index of the predicted ocean area is within a certain preset comprehensive complexity index interval, then obtain the marine gravity measurement constraint reference parameter set corresponding to this comprehensive complexity index interval as the marine gravity measurement constraint parameter set; the marine gravity measurement constraint parameter set includes the number of marine gravimeters deployed and the measurement constraint period.

[0012] Further, the specific steps for performing marine gravity measurement based on the marine gravity measurement constraint parameter set, obtaining the marine gravity data set, and analyzing to obtain the marine gravity difference index include: deploying marine gravimeters based on the marine gravity measurement constraint parameter set, thereby performing marine gravity measurement to obtain the marine gravity data set. The marine gravity data set includes the gravitational acceleration measured by each marine gravimeter each time, as well as the central distribution distance and vertical distribution height of each gravity measuring instrument; obtaining the marine gravity fitting data set, and analyzing with the marine gravity data set to obtain the marine gravity difference index; the marine gravity fitting data set includes the gravitational acceleration fitting value, the central distribution distance fitting value, and the vertical distribution height fitting value; the marine gravity difference index is used to characterize the measurement difference degree of the marine gravimeter.

[0013] Further, the specific steps for obtaining the marine gravity revision coefficient by matching include: obtaining each preset marine gravity difference index interval and the corresponding compensation reference factor in the database; based on the marine gravity difference index and comparing with each marine gravity difference index interval. If the marine gravity difference index is within a certain preset marine gravity difference index interval, then obtain the compensation reference factor corresponding to this interval as the marine gravity revision coefficient; the marine gravity revision coefficient is used to revise the marine gravity.

[0014] Further, inputting the ocean tide parameters into the ocean tide influence prediction model to obtain the ocean tide influence index, and thus matching to obtain the ocean tide revision coefficient. The specific steps include: obtaining the ocean tide parameters, where the ocean tide parameters include the tide amplitude, the maximum tide velocity, and the tide water level change rate of the predicted ocean area during the measurement constraint period; inputting the ocean tide parameters into the ocean tide influence prediction model to obtain the ocean tide influence index; the ocean tide influence index is used to characterize the influence degree of the ocean tide; obtaining each preset ocean tide influence index interval and the corresponding ocean tide reference revision coefficient in the database, and comparing with the ocean tide influence index. If the ocean tide influence index is within a certain ocean tide influence index interval, then obtain the ocean tide reference revision coefficient corresponding to this ocean tide influence index interval as the ocean tide revision coefficient. The ocean tide revision coefficient is used to reduce the measurement influence of the ocean tide on the ocean gravitational acceleration.

[0015] Further, the ocean tide influence prediction model is specifically:

[0016] ;

[0017] In the formula, represents the ocean tide influence index, represents the tide amplitude of the predicted ocean area during the measurement constraint period, and represents the unit tide amplitude influence factor, represents the maximum tide velocity of the predicted ocean area during the measurement constraint period, represents the unit maximum tide velocity influence factor, represents the tide water level change rate of the predicted ocean area during the measurement constraint period, represents the unit tide water level change rate influence factor.

[0018] Further, the specific steps for analyzing the ocean gravity correction data set based on the ocean gravity error revision coefficient and the ocean gravity data set include: extracting the gravitational acceleration measured by each ocean gravimeter in the ocean gravity data set, and performing discrete mean processing to obtain the specified gravitational acceleration; based on the ocean gravity error revision coefficient, analyzing with the ocean gravity data set to obtain the gravitational acceleration correction adjustment value, and combining with the specified gravitational acceleration to construct the specified gravitational acceleration interval of the predicted ocean area; jointly recording the specified gravitational acceleration and the specified gravitational acceleration interval of the predicted ocean area as the ocean gravity correction data set.

[0019] An embodiment of the present application provides an ocean gravity measurement error compensation system, including: a comprehensive complex analysis module, a constraint determination module, a revised coefficient evaluation module, and a correction execution module; wherein, the comprehensive complex analysis module is used to obtain the terrain parameters of the ocean area to be measured and the water flow fluctuation parameters of the ocean area to be measured, and comprehensively analyze to obtain the comprehensive complex index of the ocean area to be measured; the constraint determination module is used to analyze based on the comprehensive complex index of the ocean area to be measured to obtain an ocean gravity measurement constraint parameter set; the revised coefficient evaluation module is used to perform ocean gravity measurement based on the ocean gravity measurement constraint parameter set, obtain an ocean gravity data set, analyze to obtain an ocean gravity difference index, thereby matching to obtain an ocean gravity revised coefficient, synchronously obtain ocean tide parameters and a preset ocean tide influence prediction model, and input the ocean tide parameters into the ocean tide influence prediction model to obtain an ocean tide influence index, thereby matching to obtain an ocean tide revised coefficient; the correction execution module is used to analyze based on the ocean tide revised coefficient and the ocean gravity revised coefficient to obtain an ocean gravity error revised coefficient, and analyze based on the ocean gravity error revised coefficient and the ocean gravity data set to obtain an ocean gravity correction data set.

[0020] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0021] 1. The ocean gravity measurement error compensation method provided by the present invention obtains the terrain parameters of the ocean area to be measured and the water flow fluctuation parameters of the ocean area to be measured, and comprehensively analyzes to obtain the comprehensive complex index of the ocean area to be measured, thereby obtaining an ocean gravity measurement constraint parameter set, and further realizing the accurate analysis of ocean gravity and ensuring that the resources invested during measurement can fully conform to the actual characteristics of the ocean, providing a reliable guarantee for the effective utilization of resources, and effectively solving the problem of inaccurate ocean gravity measurement caused by complex seabed terrain and tidal fluctuation interference in the prior art.

[0022] 2. The present invention obtains an ocean gravity data set, analyzes to obtain an ocean gravity revised coefficient, thereby analyzes in combination with the ocean tide revised coefficient to obtain an ocean gravity error revised coefficient, and further analyzes based on the ocean gravity error revised coefficient and the ocean gravity data set to obtain an ocean gravity correction data set, realizing the precise correction of ocean gravity data.

[0023] 3. By obtaining ocean tide parameters and inputting them into the ocean tide influence prediction model to obtain an ocean tide influence index, thereby matching with the preset ocean tide revised coefficient, the compensation and correction of the ocean tide effect are realized, and the interference of tidal changes on ocean gravity measurement data is reduced. Description of the Drawings

[0024] Figure 1Flowchart of the marine gravity measurement error compensation method provided by the embodiments of the present application;

[0025] Figure 2 Schematic diagram of the modules of the marine gravity measurement error compensation system provided by the embodiments of the present application. Detailed implementation manners

[0026] By providing the marine gravity measurement error compensation method and its system, the embodiments of the present application solve the problem of inaccurate marine gravity measurement caused by complex seabed topography and tidal fluctuation interference in the prior art, and achieve accurate analysis of marine gravity.

[0027] In order to better understand the above technical solution, the above technical solution will be described in detail below in combination with the accompanying drawings of the specification and specific implementation manners.

[0028] As Figure 1 shown, it is a flowchart of the marine gravity measurement error compensation method provided by the embodiments of the present application. The method includes the following steps: obtaining the terrain parameters of the pre-measured ocean area and the water flow fluctuation parameters of the pre-measured ocean area, and comprehensively analyzing to obtain the comprehensive complexity index of the pre-measured ocean area; analyzing based on the comprehensive complexity index of the pre-measured ocean area to obtain the marine gravity measurement constraint parameter set; performing marine gravity measurement based on the marine gravity measurement constraint parameter set to obtain the marine gravity data set, analyzing to obtain the marine gravity difference index, thereby matching to obtain the marine gravity revision coefficient, synchronously obtaining the ocean tide parameters and the preset ocean tide influence prediction model, and inputting the ocean tide parameters into the ocean tide influence prediction model to obtain the ocean tide influence index, thereby matching to obtain the ocean tide revision coefficient; analyzing based on the ocean tide revision coefficient and the marine gravity revision coefficient to obtain the marine gravity error revision coefficient, and analyzing based on the marine gravity error revision coefficient and the marine gravity data set to obtain the marine gravity correction data set.

[0029] In this embodiment, by analyzing the comprehensive complexity index of the pre-measured ocean area, it is possible to adaptively adjust the error compensation measurement scheme according to the terrain and water flow fluctuation characteristics of different ocean areas, achieve accurate analysis of marine gravity, and ensure that the resources invested during measurement can fully conform to the actual characteristics of the ocean, providing a reliable guarantee for the effective utilization of resources. Furthermore, the accuracy of error compensation is improved, especially in applications under different seasons, tides, and ocean current conditions, ensuring high consistency and accuracy of measurement data.

[0030] Further, obtain the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area, and comprehensively analyze to obtain the comprehensive complexity index of the predicted ocean area. The specific steps include: obtaining the terrain parameters of the predicted ocean area, where the terrain parameters of the predicted ocean area include the average seabed slope, the range of seabed terrain height, the average thickness of the seabed rock layer, and the average hardness of the seabed rock layer; obtaining the water flow fluctuation parameters of the predicted ocean area, where the water flow fluctuation parameters of the predicted ocean area include the maximum water flow velocity, the range of water flow velocity, and the turbulence intensity at each screening point within a preset time period; obtaining the preset terrain reference set and water flow fluctuation reference set in the database, and comparing them with the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area respectively to obtain the comprehensive complexity index of the predicted ocean area; the comprehensive complexity index of the predicted ocean area is used to characterize the complexity of the predicted ocean area; the terrain reference set includes the slope reference value, the range reference value of terrain height, the reference value of the thickness of the seabed rock layer, and the reference value of the hardness of the seabed rock layer; the water flow fluctuation reference set includes the water flow velocity reference value, the range reference value of water flow velocity, and the turbulence intensity reference value.

[0031] In this embodiment, by analyzing the seabed terrain and water flow fluctuation parameters, it can more detailedly reflect the geological and hydrological environment of the ocean area, reduce the errors caused by ignoring these detailed factors in traditional measurement methods, not only improve the accuracy of data, but also provide a more targeted error correction scheme according to the characteristics of different ocean areas. By combining multiple key parameters and comparing them with the reference set in the database, the comprehensive complexity index of the ocean area is obtained, effectively quantifying the complexity of the ocean area and making the analysis of marine gravity data more efficient. Combining the predicted seabed terrain and water flow fluctuation parameters enables this method to flexibly respond to changes under different regions, different seasons, and different tides. It has strong adaptability to the compensation of marine gravity measurement errors in complex environments and can be widely applied to diverse marine survey and research projects.

[0032] It should be noted that the average seabed slope, the average hardness of the seabed rock layer, the seabed terrain height, and the average thickness of the seabed rock layer can be obtained by querying relevant data in the geological survey bureau. The water flow velocity and turbulence intensity can be obtained by querying relevant data in the ocean management department. The range of water flow velocity can be obtained by calculating the difference between the maximum and minimum values of the water flow velocity.

[0033] It should also be noted that by comprehensively considering complex indicators, the terrain and water flow characteristics of ocean regions can be accurately described, providing a scientific basis for subsequent correction of gravity measurement errors. It can reflect the multi-dimensional complexity of the ocean environment, especially in regions with complex terrain and water flow fluctuations, improving the credibility of ocean gravity measurement data. The introduction of comprehensive complex indicators enables ocean gravity measurement to implement targeted solutions according to specific ocean environmental conditions, achieving precise analysis of ocean gravity and ensuring that the resources invested during measurement can fully conform to the actual characteristics of the ocean, providing a reliable guarantee for the effective utilization of resources.

[0034] Furthermore, for predicting the comprehensive complex indicator of an ocean region, the specific analysis steps are as follows: Analyze based on the terrain parameters and terrain reference set of the predicted ocean region to obtain the terrain complexity indicator of the predicted ocean region; Analyze based on the water flow fluctuation parameters and water flow fluctuation reference set of the predicted ocean region to obtain the water flow fluctuation complexity indicator of the predicted ocean region; Analyze based on the terrain complexity indicator and water flow fluctuation complexity indicator of the predicted ocean region to obtain the comprehensive complex indicator of the predicted ocean region; The terrain complexity indicator of the predicted ocean region is used to characterize the terrain complexity degree of the predicted ocean region; The water flow fluctuation complexity indicator of the predicted ocean region is used to characterize the water flow fluctuation complexity degree of the predicted ocean region.

[0035] In this embodiment, it should be noted that by analyzing the terrain parameters of the predicted ocean region to obtain the terrain complexity indicator of the predicted ocean region, the mutual influence relationships among these parameters are considered. For example: Areas with a larger seabed slope usually have a larger range of terrain height differences because a larger slope means greater undulations on the seabed, resulting in a larger change in terrain height, indicating that the terrain of this ocean region is complex, leading to a greater water flow velocity and more intense water flow. Therefore, the impact during the measurement of ocean gravitational acceleration will be more severe, resulting in larger errors. The thickness of the seabed rock layer affects the stability of the seabed terrain. A thicker rock layer will suppress the slope change of the seabed, making the slope gentler. While a thin rock layer leads to a steeper slope change, causing larger terrain undulations. A harder rock layer can resist erosion and sedimentation, thus forming a steeper terrain, resulting in a larger range of terrain height differences. While a soft rock layer is prone to sedimentation or erosion, forming a flatter terrain with a smaller range of terrain height differences.

[0036] The complex index of water flow fluctuations in the predicted marine area is obtained by analyzing the water flow fluctuation parameters in the predicted marine area, taking into account the mutual influence relationships among these parameters. For example, in areas with a relatively high water flow velocity, the water flow fluctuations are usually more intense, so the range of water flow velocity will increase. Especially in areas with obvious tidal changes, the maximum water flow velocity and the range of water flow velocity usually show a positive correlation. The turbulence intensity is usually more obvious in areas with a relatively high water flow velocity. The greater the water flow velocity, the stronger the turbulence phenomenon, and the turbulence intensity increases accordingly. In areas with a higher turbulence intensity, the changes in water flow are faster, resulting in a larger range of water flow velocity. The increase in the turbulence intensity indicates an increase in the instability of the water flow, which in turn leads to an increase in the range of velocity.

[0037] The terrain complexity index can accurately describe the terrain changes in the marine area through the quantitative analysis of the average seabed slope, the range of terrain height, the rock layer thickness, and the rock layer hardness. Through this index, the terrain undulations and their complexity on the seabed can be more clearly identified, providing more accurate basic data for subsequent marine gravity measurements and error compensation. In marine gravity measurements, the undulations of the terrain directly affect the accuracy of the measurement results. Through the terrain complexity index, the subtle changes in the seabed terrain can be analyzed in depth. During the seabed survey process, through the terrain complexity index, the key measurement areas can be selected more efficiently. This index helps researchers identify areas with significant terrain changes, providing data support for accurately positioning gravity measurement points, selecting the best sampling locations, and formulating reasonable exploration plans, thereby improving the measurement efficiency and quality. The terrain complexity degrees of different marine areas vary greatly. After obtaining the terrain complexity index, customized analysis and compensation can be carried out according to the specific characteristics of the area. For example, in areas with a relatively large seabed slope, the terrain complexity index can provide more guiding information to help adjust the measurement strategy and improve the adaptability of the measurement strategy in complex environments.

[0038] By analyzing the parameters of water flow fluctuations, the complex characteristics of the marine area can be comprehensively and integrally reflected. It can not only provide multi-dimensional data on the seabed geology and hydrographic environment, but also provide a unified characterization of the characteristics of the entire marine area, helping to quickly identify the complexity degrees of different sea areas, providing a quantitative basis for gravity measurement error correction, and also helping to reduce the error impact caused by the neglect of a single factor. Especially when the terrain complexity and water flow fluctuations in the marine area are significant, the comprehensive complex index can conduct more refined error revisions through the unified analysis of the two.

[0039] The method for obtaining the terrain complexity index of the predicted marine area is as follows:

[0040] ;

[0041] In the formula, represents the terrain complexity index of the predicted marine area, represents the average slope of the seabed, represents the slope reference value, represents the range of the seabed terrain height, represents the reference value of the terrain height range, represents the average thickness of the seabed rock stratum, represents the reference value of the seabed rock stratum thickness, represents the average hardness of the seabed rock stratum, represents the reference value of the seabed rock stratum hardness, where e represents the natural constant, represents the seabed slope influence coefficient, represents the seabed terrain influence coefficient, represents the seabed rock stratum thickness influence coefficient, represents the seabed rock stratum hardness influence coefficient.

[0042] The seabed slope influence coefficient, the seabed terrain influence coefficient, the seabed rock stratum thickness influence coefficient, and the seabed rock stratum hardness influence coefficient can be obtained from the database. For example: obtain the average slope of the seabed stored in the database, and construct a seabed slope mapping set by pairing the average slope of the seabed with the corresponding seabed slope influence coefficient. There is a one-to-one or many-to-one correspondence in this seabed slope mapping set. By inputting the real-time average slope of the seabed into the mapping set, the seabed slope influence coefficient corresponding to this average slope of the seabed can be obtained. Other influence coefficients, such as the seabed terrain influence coefficient, the seabed rock stratum thickness influence coefficient, and the seabed rock stratum hardness influence coefficient, can be obtained in the same way through their corresponding mapping sets. For example, the seabed terrain influence coefficient needs to be obtained from the seabed terrain mapping set, the seabed rock stratum thickness influence coefficient needs to be obtained from the seabed rock stratum thickness mapping set, and the seabed rock stratum hardness influence coefficient needs to be obtained from the seabed rock stratum hardness mapping set. It should be noted that the construction methods of the seabed terrain mapping set, the seabed rock stratum thickness mapping set, and the seabed rock stratum hardness mapping set are the same as that of the seabed slope mapping set.

[0043] Obtain the complex index of water flow fluctuation in the predicted ocean area. The specific method is as follows:

[0044] ;

[0045] In the formula, represents the complex index of water flow fluctuation in the predicted ocean area, represents the maximum water flow velocity at the i-th screening point, where i represents the number of the screening point, , represents the total number of screening points, represents the water flow velocity reference value, represents the range of water flow velocity at the i-th screening point, represents the reference value of the water flow velocity range, represents the turbulence intensity at the i-th screening point, represents the reference value of turbulence intensity, represents the influence coefficient of water flow velocity, represents the influence coefficient of the range of water flow velocity, represents the influence coefficient of turbulence intensity.

[0046] The reference values of slope, the range of terrain height, the reference value of seabed rock layer thickness, and the reference value of seabed rock layer hardness are obtained by extraction from the database. The reference value of water flow velocity, the reference value of the range of water flow velocity, and the reference value of turbulence intensity can be obtained by extraction from the database.

[0047] It should be noted that the influence coefficient of water flow velocity, the reference value of the range of water flow velocity, and the reference value of turbulence intensity can be obtained by extraction from the database. The specific method is as follows: By obtaining the preset water flow velocity in the database and the corresponding influence coefficient, a water flow velocity mapping set is constructed, in which there is a one-to-one or many-to-one correspondence. By inputting the real-time water flow velocity into the mapping set, the influence coefficient of water flow velocity can be obtained. Other influence coefficients, such as the influence coefficient of the range of water flow velocity and the influence coefficient of turbulence intensity, can be obtained by constructing their corresponding mapping sets in the same way. For example, the influence coefficient of the range of water flow velocity needs to be obtained from the mapping set of the range of water flow velocity, and the influence coefficient of turbulence intensity needs to be obtained from the mapping set of turbulence intensity. It should be noted that the mapping sets of the range of water flow velocity and turbulence intensity are constructed in the same way as the water flow velocity mapping set.

[0048] The comprehensive complexity index of the predicted ocean area is obtained, and the specific method is as follows:

[0049] ;

[0050] In the formula, represents the comprehensive complexity index of the predicted ocean area, represents the terrain complexity index of the predicted ocean area, represents the water flow fluctuation complexity index of the predicted ocean area.

[0051] Furthermore, based on the analysis of the comprehensive complexity index of the predicted ocean area, an ocean gravity measurement constraint parameter set is obtained. The specific steps include: obtaining the preset comprehensive complexity index intervals in the database and the corresponding ocean gravity measurement constraint reference parameter sets, and comparing them with the comprehensive complexity index of the predicted ocean area. If the comprehensive complexity index of the predicted ocean area is within a certain preset comprehensive complexity index interval, then obtain the ocean gravity measurement constraint reference parameter set corresponding to this comprehensive complexity index interval as the ocean gravity measurement constraint parameter set; the ocean gravity measurement constraint parameter set includes the number of ocean gravimeters deployed and the measurement constraint period.

[0052] In this embodiment, the larger the comprehensive complexity index, the larger the corresponding deployment quantity and the longer the constraint period. It should be noted that the marine gravity measurement constraint parameter set includes the deployment quantity of marine gravimeters and the measurement constraint period, where the measurement constraint period refers to the duration of the test.

[0053] By performing interval analysis on the comprehensive complexity index of the marine area and combining it with the corresponding marine gravity measurement constraint reference parameter set, the constraint conditions during the marine gravity measurement can be controlled more precisely. Matching the complexity index of the marine area to be measured with the preset reference parameter set can effectively and flexibly adjust the constraint conditions of the marine gravity measurement for areas with different complexities, thereby improving the measurement accuracy. Moreover, it can dynamically adjust the constraint parameters of the marine gravity measurement according to the actual conditions of different marine areas, avoiding the limitations of the static measurement mode. In a complex marine environment, the comprehensive complexity index interval provides personalized constraint parameters for each area, enhancing the adaptability of data processing. Especially in areas with large environmental changes, it can effectively compensate for the errors in marine gravity measurement. Through the optimization of the deployment quantity of marine gravimeters and the measurement constraint period, the measurement resources can be reasonably allocated to ensure the comprehensiveness and efficiency of the marine gravity measurement. According to different intervals of the comprehensive complexity index, the appropriate deployment quantity of gravimeters and the measurement period are automatically selected, avoiding over-configuration or under-configuration, and maximizing the utilization efficiency of resources.

[0054] Through automated parameter matching and selection, the need for human intervention is reduced. In traditional marine gravity measurement, the selection of measurement constraint parameters usually relies on the experience of operators. However, in this invention, through the preset database, the appropriate constraint parameters can be quickly and accurately selected for each marine area, simplifying the operation process and enhancing the automation level and reliability. Through the automatic matching of the comprehensive complexity index and the constraint parameter set, efficient gravity measurement can be achieved within a large range of marine areas. Different areas obtain corresponding constraint parameter sets according to their complexity levels. The automated process reduces the complexity of manual selection, significantly improving the efficiency and coverage of marine gravity measurement within a large range of areas. This application can monitor and adjust the marine gravity measurement constraint parameter set in real time, and dynamically optimize the measurement parameters according to environmental changes and real-time data. For example, under the influence of marine tide changes, climate variations, or other external factors, it can automatically adjust the marine gravity measurement constraint reference parameter set through the obtained comprehensive complexity index interval to ensure that the measurement data can adapt to the current environment.

[0055] Further, ocean gravity measurement is carried out based on the ocean gravity measurement constraint parameter set to obtain an ocean gravity data set, and an ocean gravity difference index is analyzed. The specific steps include: arranging ocean gravimeters based on the ocean gravity measurement constraint parameter set, thereby carrying out ocean gravity measurement to obtain an ocean gravity data set. The ocean gravity data set includes the gravitational acceleration measured by each ocean gravimeter each time, as well as the central distribution distance and vertical distribution height of each gravity measuring instrument. An ocean gravity fitting data set is obtained and analyzed with the ocean gravity data set to obtain an ocean gravity difference index. The ocean gravity fitting data set includes the gravitational acceleration fitting value, the central distribution distance fitting value, and the vertical distribution height fitting value. The ocean gravity difference index is used to characterize the measurement difference degree of the ocean gravimeter.

[0056] In this embodiment, it should be noted that the ocean gravity fitting data set includes the gravitational acceleration fitting value, the central distribution distance fitting value, and the vertical distribution height fitting value. Among them, the gravitational acceleration fitting value can be obtained by averaging the gravitational acceleration measured by each ocean gravimeter each time. The gravitational acceleration of each ocean gravimeter is averaged to obtain the average gravitational acceleration of each ocean gravimeter, and then the average gravitational acceleration of each ocean gravimeter measured each time is averaged to obtain the gravitational acceleration fitting value. The central distribution distance fitting value refers to the average value of the central distribution distances measured by each gravity measuring instrument, and the vertical distribution height fitting value refers to the average value of the vertical distribution heights measured by each gravity measuring instrument.

[0057] The gravitational acceleration can be measured by an absolute gravimeter. The central distribution distance refers to the distance between the position where each ocean gravimeter is arranged and the central ocean gravimeter, and can be measured by positioning with a GPS positioning system and then measuring. The vertical distribution height can be measured by an electronic level. The vertical distribution height refers to the vertical height of the gravity measuring instrument from the sea level.

[0058] Analyzing the ocean gravity data set to obtain the ocean gravity difference index takes into account the mutual influence relationship between these parameters. For example, the gravitational acceleration directly determines the gravity value at each measurement point, but it is affected by the position of the measuring instrument (i.e., the central distribution distance) and the height change. The closer the position of the gravimeter is to the gravity source, the more accurate the measurement of the gravitational acceleration. Therefore, the shorter the central distribution distance, the more stable and accurate the measured gravitational acceleration value usually is. In addition, the change in the vertical distribution height also affects the measurement result. Due to the inhomogeneity of the earth's gravity field, with the height change, the measurement points at higher positions will have lower gravitational acceleration. Therefore, the height difference in the vertical distribution needs to be accurately measured and corrected to ensure the accuracy of the data.

[0059] By analyzing the mutual relationship among gravitational acceleration, central distribution distance, and vertical distribution height, the errors caused by measurement position and height differences can be effectively reduced. Due to the complex marine environment, gravity measurement is often affected by various factors. By comprehensively considering the mutual relationship between gravitational acceleration and position, as well as vertical height, the errors caused by a single factor can be reduced, ensuring the stability and consistency of measurement data. The layout strategy of marine gravity measurement can be optimized. By reasonably planning the position, layout, and height differences of measurement instruments, the interference factors during the measurement process can be reduced, ensuring the efficient completion of measurement work in the changing marine environment, thereby optimizing the utilization rate of measurement resources. For example, by adjusting the measurement method according to the height difference and distribution distance of measurement points, possible error sources can be predicted in advance, and targeted error correction can be carried out. This process of prediction and correction improves the efficiency and accuracy of error compensation.

[0060] The marine gravity difference index is obtained, and the specific method is as follows:

[0061] ;

[0062] In the formula, represents the marine gravity difference index, represents the gravitational acceleration of the k-th measurement of the j-th marine gravimeter, j represents the number of the marine gravimeter, , represents the total number of marine gravimeters, k represents the number of the measurement times, , represents the total number of measurement times, represents the fitted value of gravitational acceleration, represents the central distribution distance of the j-th gravity measuring instrument, represents the fitted value of the central distribution distance, represents the vertical distribution height of the j-th gravity measuring instrument, represents the fitted value of the vertical distribution height, represents the influence coefficient of gravitational acceleration, represents the influence coefficient of the central distribution distance, represents the influence coefficient of the vertical distribution height.

[0063] It should be noted that the gravitational acceleration influence coefficient, the central distribution distance influence coefficient, and the vertical distribution height influence coefficient can be obtained from a database. For example, a gravitational acceleration mapping set is constructed by obtaining the preset gravitational acceleration in the database and the corresponding influence coefficient. There is a one-to-one or many-to-one correspondence in the gravitational acceleration mapping set. By inputting the real-time gravitational acceleration into the mapping set, the gravitational acceleration influence coefficient can be obtained. Other influence coefficients, such as the central distribution distance influence coefficient and the vertical distribution height influence coefficient, can be obtained in the same way through their corresponding mapping sets. For example, the central distribution distance influence coefficient needs to be obtained in the central distribution distance mapping set, and the vertical distribution height influence coefficient needs to be obtained in the vertical distribution height mapping set. It should be noted that the construction methods of the central distribution distance mapping set and the vertical distribution height mapping set are the same as that of the gravitational acceleration mapping set.

[0064] Furthermore, the marine gravity revision coefficient is obtained through matching. The specific steps include: obtaining the preset marine gravity difference index intervals and the corresponding compensation reference factors in the database; comparing the marine gravity difference index with each marine gravity difference index interval. If the marine gravity difference index is within a certain preset marine gravity difference index interval, the corresponding compensation reference factor is obtained as the marine gravity revision coefficient. The marine gravity revision coefficient is used to revise the marine gravity.

[0065] In this embodiment, it should be noted that the larger the marine gravity difference index, the larger the marine gravity revision coefficient. By accurately matching the marine gravity difference index with the preset interval to obtain the revision coefficient, the accuracy and reliability of marine gravity measurement data are improved. In this process, the acquisition of the revision coefficient not only performs customized compensation for specific difference indexes, but also effectively ensures that in a complex and changeable marine environment, data correction can accurately adapt to the actual measurement conditions, enabling the result of each marine gravity measurement to dynamically adjust the correction factor according to the real-time difference index, improving the flexibility and accuracy of error compensation. The automated matching process optimizes the data processing flow, avoids cumbersome manual calculations and judgments, shortens the data correction cycle, and provides efficient data support for large-scale marine gravity measurements. On this basis, the corrected data can be more accurately fused and comprehensively analyzed, improving the accuracy and reliability of subsequent processing steps. Especially in data fusion and multi-source information integration, the corrected data promotes the accuracy of the analysis results.

[0066] Further, input the ocean tide parameters into the ocean tide impact prediction model to obtain the ocean tide impact index, and then match the ocean tide revision coefficient. The specific steps are as follows: Obtain the ocean tide parameters, which include the tide amplitude, the maximum tidal current velocity, and the tidal water level change rate in the predicted ocean area during the measurement constraint period; input the ocean tide parameters into the ocean tide impact prediction model to obtain the ocean tide impact index; the ocean tide impact index is used to characterize the impact degree of ocean tides; obtain each preset ocean tide impact index interval and the corresponding ocean tide reference revision coefficient in the database, and compare them with the ocean tide impact index. If the ocean tide impact index is within a certain ocean tide impact index interval, obtain the ocean tide reference revision coefficient corresponding to this ocean tide impact index interval as the ocean tide revision coefficient. The ocean tide revision coefficient is used to reduce the measurement impact of ocean tides on ocean gravitational acceleration.

[0067] In this embodiment, it should be noted that the tide amplitude refers to the vertical distance between the lowest tide level and the highest tide level in the tidal phenomenon, that is, the maximum fluctuation value of the tidal wave, which can be measured by a tide gauge (such as a tide recorder). The tide recorder determines the tide amplitude by recording the change in water level. The maximum tidal current velocity refers to the maximum value of the water flow velocity within a tidal cycle. The maximum tidal current velocity can be obtained by measuring the flow velocity with a flow velocity instrument (such as an ADCP, an acoustic Doppler current profiler). The tidal water level change rate represents the speed of water level change, which can be obtained through continuous water level measurement. The common device is a water level recorder (such as a tide recorder).

[0068] Through the comprehensive analysis of the tide amplitude, the maximum tidal current velocity, and the tidal water level change rate, accurately evaluate the impact degree of ocean tides on the measurement results. The dynamic characteristics of tides determine whether the error correction in ocean gravity measurement is accurate enough. Combining with the prediction model for revision not only ensures the accuracy of ocean gravity measurement but also improves the adaptability to tidal changes, making the error more flexible and accurate. This process reduces the interference of error sources on the measurement results, thereby improving the reliability of ocean measurement data. By comprehensively grasping the impact of tides, the compensation method can dynamically respond to tidal changes, effectively improve the quality of ocean gravity measurement data, and promote the progress of ocean science research and resource exploration fields.

[0069] Further, the ocean tide impact prediction model is specifically as follows:

[0070] ;

[0071] In the formula, represents the ocean tide impact index, represents the tide amplitude in the predicted ocean area during the measurement constraint period, represents the unit tidal amplitude influence factor, represents the maximum tidal current velocity in the predicted ocean area during the measurement constraint period, represents the unit maximum tidal current velocity influence factor, represents the rate of change of the tidal water level in the predicted ocean area during the measurement constraint period, represents the unit rate of change of tidal water level influence factor.

[0072] In this embodiment, the ocean tide influence index is obtained by analyzing ocean tide parameters, taking into account the mutual influence relationships between these parameters. For example, the tidal amplitude determines the maximum height change of the water level within the tidal period and is directly related to the flow velocity of the water. When the tidal amplitude increases, the fluctuation range of the water level expands, and the flow velocity of the water also increases accordingly. Therefore, there is a positive correlation between the maximum tidal current velocity and the tidal amplitude. The rate of change of the tidal water level is closely related to the tidal amplitude and the maximum tidal current velocity because the rate of change of the tidal water level is affected by the magnitude of the tidal amplitude, and there are different rates between high tide and low tide. In summary, the tidal amplitude, the maximum tidal current velocity, and the rate of change of the tidal water level are interdependent and interact with each other, and they are causally related to each other through physical relationships. Changes in the tidal amplitude and the maximum flow velocity usually directly lead to changes in the rate of change of the water level.

[0073] It should be noted that the unit tidal amplitude influence factor, the unit maximum tidal current velocity influence factor, and the unit rate of change of tidal water level influence factor can be obtained through the database. The unit tidal amplitude influence factor represents the degree of influence of each unit tidal amplitude on the ocean tide. The unit maximum tidal current velocity influence factor represents the degree of influence of each unit maximum tidal current velocity on the ocean tide. The unit rate of change of tidal water level influence factor represents the degree of influence of each unit rate of change of tidal water level on the ocean tide.

[0074] It should also be noted that the unit tidal amplitude influence factor can be obtained by constructing a tidal amplitude mapping set from the tidal amplitude stored in the database and the corresponding influence factor. There is a one-to-one or many-to-one correspondence in the tidal amplitude mapping set. By inputting the real-time tidal amplitude into the tidal amplitude mapping set, the unit tidal amplitude influence factor can be obtained. Other influence coefficients such as the unit maximum tidal current velocity influence factor and the unit rate of change of tidal water level influence factor can be obtained in the same way by constructing their corresponding mapping sets. For example, the unit maximum tidal current velocity influence factor needs to be obtained from the tidal current velocity mapping set, and the unit rate of change of tidal water level influence factor needs to be obtained from the tidal water level change rate mapping set. It should be noted that the construction methods of the tidal current velocity mapping set and the tidal water level change rate mapping set are the same as that of the tidal amplitude mapping set.

[0075] Further, a marine gravity correction dataset is obtained based on the marine gravity error revision coefficient and the marine gravity dataset. The specific steps include: extracting the gravitational acceleration measured by each marine gravimeter in the marine gravity dataset for each measurement, and performing discrete mean processing to obtain a specified gravitational acceleration; based on the marine gravity error revision coefficient, analyzing with the marine gravity dataset to obtain a gravitational acceleration correction adjustment value, and combining the specified gravitational acceleration to construct a specified gravitational acceleration interval for the predicted marine area; jointly recording the specified gravitational acceleration and the specified gravitational acceleration interval of the predicted marine area as the marine gravity correction dataset.

[0076] By analyzing the marine gravity error revision coefficient and the marine gravity dataset to obtain the marine gravity correction dataset, the gravity measurement errors caused by environmental factors, terrain factors, etc. can be effectively eliminated, thereby improving the accuracy and reliability of marine gravity data.

[0077] It should be noted that when extracting the gravitational acceleration measured by each marine gravimeter in the marine gravity dataset for each measurement and performing discrete mean processing to obtain a specified gravitational acceleration, the discrete mean processing refers to obtaining the reference mean of the gravitational acceleration measured by each marine gravimeter by removing the maximum and minimum values of the gravitational acceleration measured by each marine gravimeter and taking the average, and removing the maximum and minimum values of all the data obtained from each measurement and then taking the average, that is, obtaining the discrete mean.

[0078] As Figure 2 shown, it is a schematic diagram of the modules of the marine gravity measurement error compensation system provided by the embodiment of the present application. The marine gravity measurement error compensation system provided by the embodiment of the present application includes: a comprehensive complex analysis module, a constraint determination module, a revision coefficient evaluation module, and a correction execution module; among them, the comprehensive complex analysis module is used to obtain the terrain parameters of the predicted marine area and the water flow fluctuation parameters of the predicted marine area, and comprehensively analyze to obtain the comprehensive complex index of the predicted marine area; the constraint determination module is used to analyze based on the comprehensive complex index of the predicted marine area to obtain a set of marine gravity measurement constraint parameters; the revision coefficient evaluation module is used to perform marine gravity measurement based on the set of marine gravity measurement constraint parameters to obtain a marine gravity dataset, analyze to obtain a marine gravity difference index, thereby matching to obtain a marine gravity revision coefficient, synchronously obtaining marine tide parameters and a preset marine tide influence prediction model, and inputting the marine tide parameters into the marine tide influence prediction model to obtain a marine tide influence index, thereby matching to obtain a marine tide revision coefficient; the correction execution module is used to analyze based on the marine tide revision coefficient and the marine gravity revision coefficient to obtain a marine gravity error revision coefficient, and analyze based on the marine gravity error revision coefficient and the marine gravity dataset to obtain a marine gravity correction dataset.

[0079] In summary, in this embodiment, by obtaining the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area, and comprehensively analyzing to obtain the comprehensive complexity index of the predicted ocean area, the ocean gravity measurement constraint parameter set is obtained, thereby realizing the accurate analysis of ocean gravity and effectively solving the problem of inaccurate ocean gravity measurement caused by complex seabed terrain and tidal fluctuation interference in the prior art.

[0080] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0082] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0084] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once they learn of the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present invention.

[0085] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. Method for compensating marine gravity measurement error, characterized in that, It includes the following steps: Obtain the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area, and comprehensively analyze to obtain the comprehensive complexity index of the predicted ocean area; Based on the analysis of the comprehensive complexity index of the predicted ocean area, obtain the ocean gravity measurement constraint parameter set; Based on the ocean gravity measurement constraint parameter set, conduct ocean gravity measurement to obtain the ocean gravity data set, analyze to obtain the ocean gravity difference index, thereby match to obtain the ocean gravity revision coefficient, synchronously obtain the ocean tide parameters and the preset ocean tide influence prediction model, and input the ocean tide parameters into the ocean tide influence prediction model to obtain the ocean tide influence index, thereby match to obtain the ocean tide revision coefficient; Based on the analysis of the ocean tide revision coefficient and the ocean gravity revision coefficient, obtain the ocean gravity error revision coefficient, and based on the ocean gravity error revision coefficient and the ocean gravity data set, analyze to obtain the ocean gravity correction data set; The specific steps of the ocean gravity measurement based on the ocean gravity measurement constraint parameter set to obtain the ocean gravity data set and analyze to obtain the ocean gravity difference index include: Based on the ocean gravity measurement constraint parameter set, arrange the ocean gravimeters, thereby conduct ocean gravity measurement to obtain the ocean gravity data set, and the ocean gravity data set includes the gravitational acceleration measured by each ocean gravimeter each time and the central distribution distance and vertical distribution height of each gravity measuring instrument; Obtain the ocean gravity fitting data set, and analyze it with the ocean gravity data set to obtain the ocean gravity difference index; The ocean gravity fitting data set includes the gravitational acceleration fitting value, the central distribution distance fitting value, and the vertical distribution height fitting value; The ocean gravity difference index is used to characterize the measurement difference degree of the ocean gravimeter.

2. The marine gravity measurement error compensation method according to claim 1, wherein: The specific steps of obtaining the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area, and comprehensively analyzing to obtain the comprehensive complexity index of the predicted ocean area include: Obtain the terrain parameters of the predicted ocean area, and the terrain parameters of the predicted ocean area include the average seabed slope, the seabed terrain height range, the average seabed rock layer thickness, and the average seabed rock layer hardness; Obtain the water flow fluctuation parameters of the predicted ocean area, and the water flow fluctuation parameters of the predicted ocean area include the maximum water flow velocity, the water flow velocity range, and the turbulence intensity at each screening point within a preset time period; Obtain the preset terrain reference set and water flow fluctuation reference set in the database, and compare them with the terrain parameters of the predicted ocean area and the water flow fluctuation parameters of the predicted ocean area respectively to obtain the comprehensive complexity index of the predicted ocean area; The comprehensive complexity index of the predicted ocean area is used to characterize the complexity degree of the predicted ocean area; The terrain reference set includes the slope reference value, the terrain height range reference value, the seabed rock layer thickness reference value, and the seabed rock layer hardness reference value; The water flow fluctuation reference set includes the water flow velocity reference value, the water flow velocity range reference value, and the turbulence intensity reference value.

3. The marine gravity measurement error compensation method according to claim 2, characterized in that: The specific analysis steps of the comprehensive complexity index of the predicted ocean area include: Analyze based on the terrain parameters and terrain reference set of the predicted ocean area to obtain the terrain complexity index of the predicted ocean area; Analyze based on the water flow fluctuation parameters and water flow fluctuation reference set of the predicted ocean area to obtain the water flow fluctuation complexity index of the predicted ocean area; Analyze based on the terrain complexity index of the predicted ocean area and the water flow fluctuation complexity index of the predicted ocean area to obtain the comprehensive complexity index of the predicted ocean area; The terrain complexity index of the predicted ocean area is used to characterize the terrain complexity degree of the predicted ocean area; The water flow fluctuation complexity index of the predicted ocean area is used to characterize the water flow fluctuation complexity degree of the predicted ocean area.

4. The marine gravity measurement error compensation method according to claim 1, characterized in that: Based on the analysis of the comprehensive complexity index of the predicted ocean area, obtain the marine gravity measurement constraint parameter set. The specific steps include: Obtain each preset comprehensive complexity index interval in the database and the corresponding marine gravity measurement constraint reference parameter set for each comprehensive complexity index interval, and compare with the comprehensive complexity index of the predicted ocean area. If the comprehensive complexity index of the predicted ocean area is within a certain preset comprehensive complexity index interval, then obtain the marine gravity measurement constraint reference parameter set corresponding to this comprehensive complexity index interval as the marine gravity measurement constraint parameter set; The marine gravity measurement constraint parameter set includes the number of marine gravimeters arranged and the measurement constraint period.

5. The marine gravity measurement error compensation method according to claim 1, characterized in that: The specific steps for matching to obtain the marine gravity revision coefficient include: Obtain each preset marine gravity difference index interval in the database and the corresponding compensation reference factor for each marine gravity difference index interval; Based on the marine gravity difference index and compare with each marine gravity difference index interval. If the marine gravity difference index is within a certain preset marine gravity difference index interval, then obtain the compensation reference factor corresponding to this interval as the marine gravity revision coefficient; The marine gravity revision coefficient is used to revise the marine gravity.

6. The marine gravity measurement error compensation method according to claim 1, characterized in that: The specific steps for inputting the marine tide parameters into the marine tide influence prediction model to obtain the marine tide influence index and thereby matching to obtain the marine tide revision coefficient include: Obtain the marine tide parameters, where the marine tide parameters include the tide amplitude, the maximum tidal velocity, and the tidal water level change rate of the predicted ocean area during the measurement constraint period; Input the marine tide parameters into the marine tide influence prediction model to obtain the marine tide influence index; The marine tide influence index is used to characterize the influence degree of the marine tide; Obtain each preset marine tide influence index interval in the database and the corresponding marine tide reference revision coefficient for each marine tide influence index interval, and compare with the marine tide influence index. If the marine tide influence index is within a certain marine tide influence index interval, then obtain the marine tide reference revision coefficient corresponding to this marine tide influence index interval as the marine tide revision coefficient. The marine tide revision coefficient is used to reduce the measurement influence of the marine tide on the marine gravity acceleration.

7. The marine gravity measurement error compensation method according to claim 1, characterized in that: The marine tide influence prediction model is specifically: ； Wherein, represents the ocean tide influence index, represents the tidal amplitude of the predicted ocean area in the measurement constraint period, represents the unit tidal amplitude influence factor, represents the maximum tidal velocity of the predicted ocean area in the measurement constraint period, represents the unit maximum tidal velocity influence factor, represents the tidal water level change rate of the predicted ocean area in the measurement constraint period, represents the unit tidal water level change rate influence factor.

8. The marine gravity measurement error compensation method according to claim 1, characterized in that: The specific steps for analyzing based on the marine gravity error revision coefficient and the marine gravity data set to obtain the marine gravity correction data set include: Extract the gravitational acceleration of each measurement of each marine gravimeter in the marine gravity dataset, and perform discrete mean processing to obtain the specified gravitational acceleration; Based on the marine gravity error revision coefficient, analyze it with the marine gravity dataset to obtain the gravitational acceleration correction adjustment value, and combine it with the specified gravitational acceleration to construct the specified gravitational acceleration interval of the predicted marine area; Jointly record the specified gravitational acceleration and the specified gravitational acceleration interval of the predicted marine area as the marine gravity correction dataset.

9. A system applying the marine gravity measurement error compensation method according to any one of claims 1-8, characterized in that, Include: Comprehensive complex analysis module, constraint determination module, revision coefficient evaluation module, and correction execution module; Among them, the comprehensive complex analysis module is used to obtain the terrain parameters of the predicted marine area and the water flow fluctuation parameters of the predicted marine area, and comprehensively analyze to obtain the comprehensive complex index of the predicted marine area; The constraint determination module is used to analyze based on the comprehensive complex index of the predicted marine area to obtain the marine gravity measurement constraint parameter set; The revision coefficient evaluation module is used to perform marine gravity measurement based on the marine gravity measurement constraint parameter set, obtain the marine gravity dataset, analyze to obtain the marine gravity difference index, thereby matching the marine gravity revision coefficient, synchronously obtain the marine tide parameters and the preset marine tide influence prediction model, and input the marine tide parameters into the marine tide influence prediction model to obtain the marine tide influence index, thereby matching the marine tide revision coefficient; The correction execution module is used to analyze based on the marine tide revision coefficient and the marine gravity revision coefficient to obtain the marine gravity error revision coefficient, and analyze based on the marine gravity error revision coefficient and the marine gravity dataset to obtain the marine gravity correction dataset.

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