A gravity inversion accuracy evaluation system and method considering the self-noise of shipborne measurements

Abstract

The present application provides a gravity inversion accuracy evaluation system and method considering the self-noise of shipborne measurements. The system includes: a shipborne gravity data verification module, which is used to refine the shipborne gravity data, then use the shipborne gravity data to verify the altimetry gravity inversion product to obtain the shipborne verification accuracy of the altimetry gravity inversion product, and use the shipborne gravity data to verify the gravity field model to obtain the shipborne verification accuracy of the gravity field model; a global gravity field model comparison module, which is used to intercept the global gravity field model for comparison to obtain the gravity field model comparison accuracy of the altimetry gravity inversion product; a gravity inversion accuracy evaluation module, which is used to jointly calculate the self-noise of the shipborne verification data and deduct the shipborne self-noise to obtain the accurate satellite altimetry gravity inversion accuracy. The advantages of the present application are: it can effectively remove the influence of the self-noise of shipborne gravity data on the altimetry gravity inversion accuracy and evaluate the accurate altimetry gravity inversion accuracy.

Description

Technical Field

[0001] This application belongs to the field of marine remote sensing mapping, and specifically relates to a gravity inversion accuracy evaluation system and method considering the self-noise of shipborne measurement. Background Art

[0002] The radar altimeter is an important active microwave remote sensor carried on marine remote sensing satellites. It obtains marine observation data such as sea surface height (SSH), significant wave height, and wind speed by transmitting radar pulse signals to the sea surface and receiving echo signals. By extracting gravity-related parameters such as the marine geoid and deflection of the vertical from satellite altimeter SSH data, the marine gravity field can be further inverted. Compared with traditional shipborne gravity measurement methods, the satellite altimeter can complete the workload of the past century in just a few months, with incomparable superiority. Compared with gravity satellite observations, the satellite altimeter can obtain the short-wave marine gravity field globally and is currently the only means to obtain the globally covered short-wave gravity field. Therefore, the satellite altimeter is currently the main means to obtain a high-precision global marine gravity field.

[0003] Currently, the main methods for evaluating the accuracy of satellite altimetry-derived marine gravity field products are verification with shipborne gravity data and comparison with global gravity field models. Among them, verification with shipborne gravity data has become the most commonly used method for evaluating the accuracy of satellite altimetry gravity inversion because it uses external measured data. The National Centers for Environmental Information (NCEI) of the National Oceanic and Atmospheric Administration (NOAA) of the United States provides shipborne gravity data globally, which is a good data source for verifying the gravity inversion accuracy of satellite altimeters. To avoid the influence of noise and errors in shipborne gravity data on the evaluation accuracy, these shipborne gravity data from different years, different ships, different measurement devices, etc. are usually preprocessed before use to improve the accuracy, but the shipborne data itself still inevitably has noise.

[0004] In the early stage when satellite altimetry gravity inversion was not very accurate, the noise of shipborne gravity data itself was much smaller than the noise of the inverted gravity field, and this influence could be ignored. However, with the gradual improvement of the accuracy of satellite altimeter data and the gradual refinement of the inversion process, the accuracy of the altimetry-derived marine gravity field has also been greatly improved, gradually approaching 1 mGal from dozens of mGal, while the noise of shipborne gravity data itself is also at the mGal level. Therefore, this method of verifying shipborne gravity data by ignoring the self-noise of shipborne measurement is no longer suitable for evaluating the gravity inversion of satellite altimetry with current accuracy. Summary of the Invention

[0005] The purpose of this application is to overcome the defect that the existing accuracy evaluation method for verifying shipborne gravity data ignores the self-noise of shipborne measurement and is difficult to evaluate the accurate gravity inversion accuracy of satellite altimetry.

[0006] To achieve the above object, the present application proposes a gravity inversion accuracy evaluation system considering the shipborne measurement's own noise, and the system includes:

[0007] A shipborne gravity data verification module, which is used to refine the shipborne gravity data, then use the shipborne gravity data to verify the altimetry gravity inversion product, calculate the root mean square error between the two, obtain the shipborne verification accuracy of the altimetry gravity inversion product, and at the same time use the shipborne gravity data to verify the gravity field model to obtain the shipborne verification accuracy of the gravity field model;

[0008] A global gravity field model comparison module, which is used to intercept the global gravity field model according to the longitude and latitude range of the altimetry inversion sea area for comparison, and calculate the root mean square error between the gravity field model and the altimetry gravity inversion product in combination with the land-sea mask information to obtain the gravity field model comparison accuracy of the altimetry gravity inversion product;

[0009] A gravity inversion accuracy evaluation module, which is used to jointly calculate the gravity field model comparison accuracy, the shipborne verification accuracy of the altimetry gravity inversion product, and the shipborne verification accuracy of the gravity field model, calculate the own noise of the shipborne verification data, and then deduct the shipborne measurement's own noise to obtain the accurate satellite altimetry gravity inversion accuracy.

[0010] As an improvement of the above system, the processing process of the shipborne gravity data verification module includes:

[0011] Step A1: Perform long-wave error correction and reference unification according to the survey line time, longitude and latitude, and the residual value range information of the model gravity to suppress noise, and obtain refined shipborne gravity data;

[0012] Step A2: Interpolate the altimetry gravity inversion product to the corresponding position of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the two, and obtain the shipborne verification accuracy of the altimetry gravity inversion product :

[0013]

[0014] Among them, is the number of points of the shipborne verification data; is the gravity value corresponding to the th point of the shipborne verification data; is the gravity value interpolated from the th point of the altimetry gravity inversion product.

[0015] Step A3: Interpolate the gravity field model to the corresponding position of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the two, and obtain the shipborne verification accuracy of the gravity field model :

[0016]

[0017] Among them, is the gravity value obtained by interpolating the point of the gravity field model.

[0018] As an improvement of the above system, the processing process of the global gravity field model comparison module includes:

[0019] Step B1: Intercept the gravity field model of the altimetry inversion sea area from the global gravity field model according to the latitude and longitude range of the altimetry gravity inversion product for comparison;

[0020] Step B2: Interpolate the altimetry gravity inversion product to the corresponding position of the altimetry inversion sea area gravity field model by using the latitude and longitude information, and calculate the root mean square error between the two by combining the land-sea mask information to obtain the comparison accuracy of the altimetry gravity inversion product and the gravity field model :

[0021]

[0022] Among them, is the number of points of the altimetry inversion sea area gravity field model; is the gravity value corresponding to the point of the inversion sea area gravity field model; is the gravity value obtained by interpolating the point of the altimetry gravity inversion product; is the land-sea mask value of the th point.

[0023] As an improvement of the above system, the processing process of the gravity inversion accuracy evaluation module includes:

[0024] Step C1: Jointly solve the comparison accuracy of the altimetry gravity inversion product, the ship measurement verification accuracy, and the ship measurement verification accuracy of the gravity field model to calculate the self-noise

[0025]

[0026] of the ship measurement verification data; :

[0027] .

[0028] This application also provides a gravity inversion accuracy evaluation method considering the self-noise of ship measurement, which is implemented based on the above system and includes:

[0029] Step 1: Perform long-wave error correction and datum unification processing on the shipborne gravity data to suppress noise, and obtain refined shipborne gravity data.

[0030] Step 2: Interpolate the altimetry gravity to the corresponding positions of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the altimetry gravity and the shipborne gravity, and obtain the shipborne verification accuracy of the altimetry gravity inversion product. ;

[0031] Step 3: Interpolate the gravity field model to the corresponding positions of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the gravity field model and the shipborne gravity, and obtain the shipborne verification accuracy of the gravity field model. ;

[0032] Step 4: Intercept the gravity field model of the altimetry inversion sea area from the global gravity field model according to the longitude and latitude range of the altimetry gravity inversion product for comparison.

[0033] Step 5: Interpolate the altimetry gravity inversion product to the corresponding positions of the altimetry inversion sea area gravity field model using the longitude and latitude information, and calculate the root mean square error between the two by combining the land-sea mask information, to obtain the comparison accuracy between the altimetry gravity inversion product and the gravity field model. ;

[0034] Step 6: Jointly solve the comparison accuracy of the gravity field model of the altimetry gravity inversion product, the shipborne verification accuracy, and the shipborne verification accuracy of the gravity field model, and calculate the self-noise of the shipborne verification data. ;

[0035] Step 7: Deduct the shipborne self-noise from the shipborne verification accuracy of the altimetry gravity inversion product to obtain the accurate satellite altimetry gravity inversion accuracy. .

[0036] Compared with the prior art, the advantages of this application are as follows:

[0037] 1. This application establishes a satellite altimetry gravity inversion accuracy evaluation system considering shipborne self-noise.

[0038] 2. The satellite altimetry gravity inversion accuracy evaluation method proposed in this application can effectively remove the influence of the self-noise of the shipborne gravity data on the altimetry gravity inversion accuracy through the cross-verification of the shipborne gravity data, the global gravity field model, and the altimetry gravity inversion product, and evaluate the accurate altimetry gravity inversion accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 The figure shows the structural diagram of a satellite altimetry gravity inversion accuracy evaluation system considering shipborne self-noise;

[0040] Figure 2 The figure shows a flowchart of a method for evaluating the accuracy of satellite altimetry gravity inversion considering the self-noise of shipborne measurements. Specific implementation manners

[0041] The technical solution of the present application will be described in detail below with reference to the accompanying drawings.

[0042] The system and method for evaluating the accuracy of satellite altimetry gravity inversion considering the self-noise of shipborne measurements proposed in the present application are applicable not only to radar altimeters but also to laser altimeters. By jointly cross-verifying shipborne gravity data, global gravity field models, and altimetry gravity inversion products, the influence of the self-noise of shipborne gravity data on the evaluation of the accuracy of altimetry gravity inversion can be effectively removed, and accurate altimetry gravity inversion accuracy can be obtained.

[0043] Example 1

[0044] As Figure 1 shown, the present application proposes a system for evaluating the accuracy of satellite altimetry gravity inversion considering the self-noise of shipborne measurements, including a shipborne gravity data verification module, a global gravity field model comparison module, and a gravity inversion accuracy evaluation module.

[0045] The design of each module is as follows:

[0046] 1. Shipborne gravity data verification module: After refining the shipborne gravity data, it uses the shipborne gravity data to verify the altimetry gravity inversion product, calculates the root mean square error between the two, and obtains the shipborne verification accuracy of the altimetry gravity inversion product. At the same time, it uses the shipborne gravity data to verify the gravity field model and obtains the shipborne verification accuracy of the gravity field model;

[0047] The processing process of the shipborne gravity data verification module includes:

[0048] Step 1: Refinement processing of shipborne gravity data; performing long-wave error correction and datum unification according to information such as the time of the survey line, longitude and latitude, and the residual value range from the model gravity to suppress noise, and obtaining refined shipborne gravity data;

[0049] Step 2: Calculation of altimetry-shipborne verification accuracy; interpolating the altimetry gravity inversion product to the position corresponding to the shipborne gravity using longitude and latitude information, and calculating the root mean square error between the two to obtain the shipborne verification accuracy of the altimetry gravity inversion product:

[0050]

[0051] where is the number of points of the shipborne verification data; is the gravity value corresponding to the th point of the shipborne verification data; is the Gravity values obtained by point interpolation.

[0052] Step 3: Model - ship measurement verification accuracy calculation; Interpolate the gravity field model to the corresponding positions of the ship - measured gravity using longitude and latitude information, calculate the root - mean - square error between the two, and obtain the ship - measurement verification accuracy of the gravity field model:

[0053]

[0054] where is the number of points of the ship - measurement verification data; is the gravity value corresponding to the - th point of the ship - measurement verification data; is the gravity value obtained by interpolating the - th point of the gravity field model.

[0055] 2. Global gravity field model comparison module: Used to intercept the global gravity field model according to the longitude and latitude range of the altimetry - derived sea area for comparison, and calculate the root - mean - square error between the gravity field model and the altimetry gravity inversion product in combination with land - sea mask information to obtain the gravity field model comparison accuracy of the altimetry gravity inversion product;

[0056] The processing process of the global gravity field model comparison module includes:

[0057] Step 1: Interception of the altimetry - derived sea area model; Intercept the gravity field model of the altimetry - derived sea area from the global gravity field model according to the longitude and latitude range of the altimetry gravity inversion product for comparison;

[0058] Step 2: Calculation of altimetry - model comparison accuracy; Interpolate the altimetry gravity inversion product to the corresponding positions of the gravity field model of the altimetry - derived sea area using longitude and latitude information, and calculate the root - mean - square error between the two in combination with land - sea mask information to obtain the comparison accuracy between the altimetry gravity inversion product and the gravity field model:

[0059]

[0060] where is the number of points of the gravity field model of the altimetry - derived sea area; is the gravity value corresponding to the - th point of the gravity field model of the inversion sea area; is the gravity value obtained by interpolating the - th point of the altimetry gravity inversion product; is the land - sea mask value of the - th point, 0 for land and 1 for sea.

[0061] 3. Gravity Inversion Accuracy Evaluation Module: It is used to calculate by combining the accuracy of comparing the gravity field models of collinear altimetry gravity inversion products, the shipborne measurement verification accuracy, and the shipborne measurement verification accuracy of the gravity field model, calculate the self-noise of the shipborne measurement verification data, and then deduct the shipborne self-noise to obtain the accurate satellite altimetry gravity inversion accuracy;

[0062] The processing process of the gravity inversion accuracy evaluation module includes:

[0063] Step 1: Cross-validation combined calculation; Calculate by combining the accuracy of comparing the gravity field models of collinear altimetry gravity inversion products, the shipborne measurement verification accuracy, and the shipborne measurement verification accuracy of the gravity field model, and calculate the self-noise of the shipborne measurement verification data ;

[0064]

[0065] Step 2: Deduction of shipborne self-noise; Deduct the shipborne self-noise from the shipborne measurement verification accuracy of the altimetry gravity inversion product to obtain the accurate satellite altimetry gravity inversion accuracy :

[0066]

[0067] Embodiment 2

[0068] As Figure 2 shown, the present application also proposes a method for evaluating the satellite altimetry gravity inversion accuracy considering the shipborne self-noise, which is implemented based on the above system and includes:

[0069] Step 1) Perform long-wave error correction and reference unification processing on the shipborne gravity data to suppress noise, and obtain refined shipborne gravity data;

[0070] Step 2) Interpolate the altimetry gravity to the corresponding position of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the altimetry gravity and the shipborne gravity, and obtain the shipborne measurement verification accuracy of the altimetry gravity inversion product ;

[0071] Step 3) Interpolate the gravity field model to the corresponding position of the shipborne gravity using the longitude and latitude information, calculate the root mean square error between the gravity field model and the shipborne gravity, and obtain the shipborne measurement verification accuracy of the gravity field model ;

[0072] Step 4) Intercept the gravity field model of the altimetry inversion sea area from the global gravity field model according to the longitude and latitude range of the altimetry gravity inversion product for comparison;

[0073] Step 5) Interpolate the altimetry gravity inversion product to the corresponding position of the altimetry inversion sea area gravity field model using the latitude and longitude information, and calculate the root mean square error between the two in combination with the land-sea mask information to obtain the comparison accuracy between the altimetry gravity inversion product and the gravity field model ;

[0074] Step 6) Solve by combining the comparison accuracy of the gravity field model of the altimetry gravity inversion product, the shipborne measurement verification accuracy of the altimetry gravity inversion product, and the shipborne measurement verification accuracy of the gravity field model, and calculate the self-noise of the shipborne measurement verification data ;

[0075] Step 7) Deduct the shipborne self-noise from the shipborne measurement verification accuracy of the altimetry gravity inversion product to obtain the accurate satellite altimetry gravity inversion accuracy .

[0076] This application can also provide a computer device, including: at least one processor, a memory, at least one network interface, and a user interface. Each component in the device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus, and a status signal bus

[0077] Among them, the user interface can include a display, a keyboard, or a pointing device. For example, a mouse, a trackball, a touchpad, or a touch screen, etc

[0078] It can be understood that the memory in the disclosed embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM). The memories described herein are intended to include, but are not limited to, these and any other suitable types of memories.

[0079] In some embodiments, the memory stores the following elements, executable modules or data structures, or subsets or extended sets thereof: an operating system and application programs.

[0080] Among them, the operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., and is used to implement various basic services and handle hardware-based tasks. The application programs include various application programs, such as a media player and a browser, etc., and are used to implement various application services. The program for implementing the method of the disclosed embodiments of the present application can be included in the application programs.

[0081] In the above embodiments, by calling the programs or instructions stored in the memory, specifically, the programs or instructions stored in the application programs, the processor is configured to:

[0082] Execute the steps of the above method.

[0083] The above method can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with the ability to process signals. During implementation, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor or instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute each of the above disclosed methods, steps, and logic block diagrams. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Combining the steps of the above disclosed method can be directly embodied as being completed by the execution of a hardware decoding processor, or completed by the combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0084] It can be understood that these embodiments described in the present application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0085] For software implementation, the techniques of the present application can be implemented by executing the functional modules of the present application (such as procedures, functions, etc.). The software code can be stored in the memory and executed by the processor. The memory can be implemented inside or outside the processor.

[0086] The present application may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, the various steps in the above method embodiments can be implemented.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the embodiments, those of ordinary skill in the art should understand that any modification or equivalent replacement of the technical solutions of the present application does not depart from the spirit and scope of the technical solutions of the present application, and they should all be covered within the scope of the claims of the present application.

Claims

1. A gravity inversion accuracy assessment system taking into account the ship's own noise, characterized by: The system comprises: The ship-surveyed gravity data verification module is used to refine the ship-surveyed gravity data and then use the ship-surveyed gravity data to verify the altimetry gravity inversion product. The root mean square error between the two is calculated to obtain the ship-surveyed verification accuracy of the altimetry gravity inversion product. At the same time, the ship-surveyed gravity data is used to verify the gravity field model to obtain the ship-surveyed verification accuracy of the gravity field model. The global gravity field model comparison module is used to intercept the global gravity field model according to the latitude and longitude range of the altimetry inversion sea area for comparison, and calculate the root mean square error between the gravity field model and the altimetry gravity inversion product by combining the sea and land mask information to obtain the comparative accuracy of the gravity field model of the altimetry gravity inversion product; and The gravity inversion accuracy assessment module is used to jointly solve the gravity field model comparison accuracy, ship-measurement verification accuracy and ship-measurement verification accuracy of the gravity field model of the altimetry gravity inversion product, calculate the self-noise of the ship-measurement verification data, and then deduct the ship-measurement self-noise to obtain the accurate satellite altimetry gravity inversion accuracy.

2. The gravity inversion accuracy assessment system taking into account the ship's own noise according to claim 1 is characterized in that: The processing process of the ship-measured gravity data verification module includes: Step A1: Perform long-wave error correction and benchmark unification based on the survey line time, longitude and latitude, and the range of residual values with the model gravity to suppress noise, and obtain refined ship-surveyed gravity data; Step A2: Use the latitude and longitude information to interpolate the altimetry gravity inversion product to the corresponding position of the ship-measured gravity, calculate the root mean square error between the two, and obtain the ship-measured verification accuracy of the altimetry gravity inversion product : ； in, The number of points for ship measurement verification data; Verification data for ship test The gravity value corresponding to the point; For altimetry gravity inversion product Gravity value obtained by point interpolation; Step A3: Use the latitude and longitude information to interpolate the gravity field model to the corresponding position of the ship-measured gravity, calculate the root mean square error between the two, and obtain the ship-measured verification accuracy of the gravity field model : ； in, The gravity field model The gravity value obtained by point interpolation.

3. The gravity inversion accuracy assessment system taking into account the ship's own noise according to claim 1 is characterized in that: The processing process of the global gravity field model comparison module includes: Step B1: According to the latitude and longitude range of the altimetry gravity inversion product, the gravity field model of the altimetry inversion sea area is intercepted from the global gravity field model for comparison; Step B2: Use the latitude and longitude information to interpolate the altimetry gravity inversion product to the corresponding position of the altimetry inversion sea area gravity field model, and calculate the root mean square error between the two in combination with the sea and land mask information to obtain the comparative accuracy of the altimetry gravity inversion product and the gravity field model. : ； in, The number of points of the gravity field model of the sea area for altimetry inversion; To invert the ocean gravity field model The gravity value corresponding to the point; For altimetry gravity inversion product Gravity value obtained by point interpolation; For the The land and sea mask value of each point.

4. The gravity inversion accuracy assessment system taking into account the ship's own noise according to claim 1 is characterized in that: The processing process of the gravity inversion accuracy assessment module includes: Step C1: Comparison of the accuracy of gravity field models of combined altimetry gravity inversion products , ship measurement verification accuracy and ship-based verification accuracy of gravity field models Perform calculations to calculate the self-noise of the ship test verification data ; ； Step C2: Deduct the ship noise from the ship verification accuracy of the altimetry gravity inversion product to obtain the accurate satellite altimetry gravity inversion accuracy. : 。 5. A method for evaluating gravity inversion accuracy taking into account ship noise, implemented based on the system of any one of claims 1 to 4, comprising: Step 1: Perform long-wave error correction and benchmark unification on the ship-measured gravity data to suppress noise and obtain refined ship-measured gravity data; Step 2: Use the latitude and longitude information to interpolate the altimetry gravity to the corresponding position of the ship-measured gravity, calculate the root mean square error between the altimetry gravity and the ship-measured gravity, and obtain the ship-measured verification accuracy of the altimetry gravity inversion product ; Step 3: Use the longitude and latitude information to interpolate the gravity field model to the corresponding position of the ship-measured gravity, calculate the root mean square error between the gravity field model and the ship-measured gravity, and obtain the ship-measured verification accuracy of the gravity field model. ; Step 4: According to the latitude and longitude range of the altimetry gravity inversion product, the gravity field model of the altimetry inversion sea area is intercepted from the global gravity field model for comparison; Step 5: Use the latitude and longitude information to interpolate the altimetry gravity inversion product to the corresponding position of the altimetry inversion sea area gravity field model, and calculate the root mean square error between the two in combination with the sea and land mask information to obtain the comparative accuracy of the altimetry gravity inversion product and the gravity field model. ; Step 6: Combine the gravity field model comparison accuracy of the altimetry gravity inversion product, the ship-measurement verification accuracy, and the ship-measurement verification accuracy of the gravity field model to calculate the self-noise of the ship-measurement verification data. ; Step 7: Deduct the ship noise from the ship verification accuracy of the altimetry gravity inversion product to obtain the accurate satellite altimetry gravity inversion accuracy. .

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