Gravity field evaluation method and system based on spherical harmonic domain recursion and structured matrix blocks

Abstract

The application relates to the technical field of planetary gravity field evaluation. The application discloses a gravity field evaluation method and system based on spherical harmonic spectrum domain recursion and structured matrix blocks, which can efficiently complete error propagation calculation at each order under the condition of limited computing resources. The method comprises the following steps: acquiring a target covariance matrix and a latitude and longitude calculation grid; dividing the latitude and longitude calculation grid into multiple latitude batches; performing row and column slicing processing on the target covariance matrix to obtain multiple target slices; using a spectrum domain recursive error propagation calculation method to calculate and process the target covariance matrix or the multiple target slices at each order in all spherical harmonic orders of each latitude batch to obtain a non-central term radial acceleration theoretical signal value, an actual signal value, an error value, a cumulative signal value and a cumulative error value corresponding to each spherical harmonic order; and evaluating the gravity field of a target planet based on all the non-central term radial acceleration theoretical signal values, the actual signal values, the error values, the cumulative signal values and the cumulative error values.

Description

Technical Field

[0001] This application relates to the field of planetary gravitational field assessment technology. More specifically, this application relates to a gravitational field assessment method and system based on spherical harmonic spectral domain recursion and structured matrix blocks. Background Technology

[0002] Traditional methods for assessing gravity fields refer to conventional planetary gravity field assessment methods. These methods only use the spherical harmonic coefficients and coefficient errors of the gravity field model to calculate the global signal strength and error strength of the model. This method does not use the complete covariance matrix to calculate the global signal strength and error strength of the gravity field model. Therefore, when dealing with higher-order gravity field models, traditional methods suffer from low computational efficiency, high resource consumption, and long computation cycles, becoming a significant bottleneck restricting the assessment of higher-order gravity field models. Summary of the Invention

[0003] The purpose of this application is to provide a method and system for evaluating gravity fields based on spherical harmonic spectral domain recursion and structured matrix blocks, which can efficiently complete the successive error propagation calculation under limited computational resources. This application is mainly achieved through the following technical solutions: A first aspect of this application provides a method for evaluating a gravity field based on spherical harmonic spectral domain recursion and structured matrix blocks, including: Obtain the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet; The latitude and longitude calculation grid is divided into multiple latitude batches along the latitudinal direction; The target covariance matrix is ​​divided into rows and columns to obtain multiple target slices; The target covariance matrix or the multiple target slices are calculated sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method. This yields the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch. The gravitational field of the target planet is evaluated based on the theoretical, actual, error, cumulative, and cumulative error values ​​of the radial acceleration of all non-central terms.

[0004] According to one embodiment of this application, after calculating the target covariance matrix or the multiple target slices sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: The cumulative error values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the cumulative error value fusion result. The theoretical signal values ​​of radial acceleration of non-central terms corresponding to all spherical harmonic orders in all latitudinal batches are spliced ​​to obtain the theoretical signal value fusion result. The actual signal values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the actual signal value fusion result. The error values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the error value fusion result. The cumulative signal values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the cumulative signal value fusion result. The cumulative error value fusion result, the theoretical signal value fusion result, the actual signal value fusion result, the error value fusion result, and the cumulative signal value fusion result are displayed.

[0005] According to one embodiment of this application, the step of obtaining the target covariance matrix includes: Obtain the model file; The target covariance matrix is ​​generated based on the compressed upper triangular covariance data of the model file.

[0006] According to one embodiment of this application, the step of obtaining the latitude and longitude calculation grid includes: generating the latitude and longitude calculation grid according to a preset latitude and longitude range and a preset latitude and longitude interval.

[0007] According to one embodiment of this application, after calculating the target covariance matrix or the multiple target slices sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: Determine whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value of the non-central term corresponding to the target spherical harmonic order is greater than a preset value. If so, record the target spherical harmonic order as the order strength value. The target spherical harmonic order is any one of the spherical harmonic orders.

[0008] According to one embodiment of this application, after determining whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value corresponding to the target spherical harmonic order is greater than a preset value, and if so, recording the target spherical harmonic order as an order strength value, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: All order strength values ​​are concatenated to obtain the order strength value fusion result; The order strength value fusion result is then displayed.

[0009] According to one embodiment of this application, the step of performing row and column slicing on the target covariance matrix to obtain multiple target slices includes: Get the memory size, video memory size, number of columns in the slice, and number of rows in the temporary slice; The target covariance matrix is ​​divided into rows and columns based on the memory size data, the video memory size data, the number of slice columns, and the number of temporary slice rows and blocks to obtain the multiple target slices.

[0010] A second aspect of this application provides a gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks, including: The data acquisition module is used to acquire the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet; The grid partitioning module is used to divide the latitude and longitude calculation grid into multiple latitude batches along the latitude direction; The slicing module is used to perform row and column slicing on the target covariance matrix to obtain multiple target slices; The calculation module is used to calculate the target covariance matrix or the multiple target slices in each latitude batch in all spherical harmonic orders by using the spectral domain recursive error propagation calculation method, and to obtain the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch; The evaluation module is used to evaluate the gravitational field of the target planet based on the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the radial acceleration of all non-central terms.

[0011] According to one embodiment of this application, the data acquisition module includes a graphical interaction module, a matrix construction module, and a grid acquisition module. The graphical interaction module is used to acquire a model file; the matrix construction module is used to generate the target covariance matrix based on the compressed upper triangular covariance data of the model file; and the grid acquisition module is used to acquire the latitude and longitude calculation grid.

[0012] According to one embodiment of this application, the grid acquisition module is further configured to generate the latitude and longitude calculation grid based on a preset latitude and longitude range and a preset latitude and longitude interval.

[0013] The beneficial effects of the embodiments of this application include: This application embodiment obtains the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet; divides the latitude / longitude calculation grid into multiple latitude batches along the latitude direction; performs row and column slicing processing on the target covariance matrix to obtain multiple target slices; uses a spectral domain recursive error propagation calculation method to calculate the target covariance matrix or the multiple target slices order by order in all spherical harmonic orders of each latitude batch, obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch; and evaluates the gravitational field of the target planet based on all non-central radial acceleration theoretical signal values, actual signal values, error values, cumulative signal values, and cumulative error values. Compared with the existing technology that only uses the spherical harmonic coefficients of the gravity field model to calculate the global signal strength and error strength of the gravity field model, this application embodiment introduces a spectral domain recursive error propagation calculation method and matrix slicing method, which can efficiently complete the order-by-order error propagation calculation under limited computing resources. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of this application or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 The flowcharts for some embodiments of the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks of this application are shown below. Figure 2 The flowcharts are shown in some of the embodiments of the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks of this application; Figure 3 The flowcharts are shown in some of the embodiments of the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks of this application; Figure 4 This is a block diagram illustrating the principle of the gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks in some embodiments of this application. Figure 5 This is a block diagram illustrating the principle of the gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks in some other embodiments of this application. Figure 6 This is a reference diagram of the order intensity mesh diagram in some embodiments of this application; Figure 7 This is a reference diagram of the cumulative actual signal grid diagram in some embodiments of this application; Figure 8This is a reference diagram of the single-order signal mesh diagram in some embodiments of this application; Figure 9 This is a reference diagram of the single-order error map mesh diagram in some embodiments of this application; Figure 10 This is a schematic block diagram of the terminal device of this application in some embodiments. Detailed Implementation

[0016] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0017] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0018] The terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0019] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are expressly listed, but may include other steps or units that are not expressly listed or that are inherent to such process, method, product, or apparatus.

[0020] The terms "gravitational field model" or "planetary gravitational field model" refer to fundamental data crucial for studying the internal structure, density distribution, and evolution of planets. Planetary gravitational fields are expressed using spherical harmonic function expansions, and their core consists of two parts: spherical harmonic coefficients and a covariance matrix. The spherical harmonic coefficients describe the parameters of the gravitational field signal itself through spherical harmonic functions; the covariance matrix describes the uncertainties in the parameters of the gravitational field spherical harmonic model and the correlations between these parameters. The covariance matrix is ​​not only enormous but also crucial data for error propagation calculations.

[0021] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used in this application includes any and all combinations of one or more of the associated listed items.

[0022] The specific embodiments of this application will be further described below with reference to the accompanying drawings.

[0023] refer to Figure 1 The diagram shown is a flowchart of a gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks, provided in the first aspect of this application. Figure 1 The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks includes the following steps S1, S2, S3, S4 and S5.

[0024] S1. Obtain the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet.

[0025] The target planet can be the Moon, Mars, or Earth.

[0026] Furthermore, the step of obtaining the target covariance matrix includes: obtaining a model file; and generating the target covariance matrix based on the compressed upper triangular covariance data of the model file.

[0027] Furthermore, the target covariance matrix It can be represented as: ; in, It is the autocovariance matrix of the second-order spherical harmonic coefficients; It is the first The cross-covariance block matrix of the first and second order spherical harmonic coefficients; It is the second order, the... The cross-covariance block matrix of the spherical harmonic coefficients; yes The autocovariance matrix of the spherical harmonic coefficients.

[0028] In other implementations, for grid points Reference radius Below, the cumulative non-central terms of radial acceleration spherical harmonics from order 2 to n. This can be expressed as: ; in, It is the gravitational constant; It is the mass of the target planet; Associative Legendre function; These are the spherical harmonic coefficients of the cosine term gravitational field; These are the spherical harmonic coefficients of the gravitational field in the sinusoidal term; For the strong.

[0029] right Find the spherical harmonic coefficients , Partial derivatives yield: ; in, It is an associated Legendre function; It is longitude; It refers to the number of times; These are the spherical harmonic coefficients of the gravity field model; These are the spherical harmonic coefficients of the gravity field model.

[0030] Furthermore, the step of obtaining the latitude and longitude calculation grid includes: generating the latitude and longitude calculation grid according to a preset latitude and longitude range and a preset latitude and longitude interval.

[0031] The specific values ​​of the preset latitude and longitude range and the preset latitude and longitude interval can be set by those skilled in the art according to actual needs.

[0032] Further, the step of generating the latitude and longitude calculation grid based on the preset latitude and longitude interval and the preset latitude and longitude interval may include: iteratively generating a one-dimensional longitude coordinate array covering the complete longitude interval in the preset latitude and longitude interval based on the starting longitude value in the preset latitude and longitude interval and the longitude interval in the preset latitude and longitude interval; iteratively generating a one-dimensional latitude coordinate array covering the complete latitude interval in the preset latitude and longitude interval based on the starting latitude value in the preset latitude and longitude interval and the latitude interval in the preset latitude and longitude interval; pairing the one-dimensional longitude coordinate array and the one-dimensional latitude coordinate array by performing a Cartesian product, and combining the longitude values ​​and latitude values ​​one group at a time to obtain multiple grid node coordinates; and integrating all grid node coordinates to form the latitude and longitude calculation grid.

[0033] The latitude and longitude grid points of the latitude and longitude calculation grid In the The variance of the non-central term radial acceleration of order It can be equivalently expanded as: ; in, Latitude and longitude grid points In the The first design quantity corresponding to the harmonic order of a sphere; Latitude and longitude grid points In the The incremental contribution of the first design quantity corresponding to each harmonic order; Represents transpose; It is the target covariance matrix; Latitude and longitude grid points In the The variance of the radial acceleration of the non-central term of the order.

[0034] S2. Divide the latitude and longitude calculation grid into multiple latitude batches along the latitude direction.

[0035] The implementation of step S2 can reduce the scale of a single computation.

[0036] S3. Perform row and column slicing on the target covariance matrix to obtain multiple target slices. The slice partitioning process can refer to... Figure 2 and Figure 3 As shown.

[0037] The implementation of the S3 step significantly reduces memory usage and disk random access pressure, thus overcoming the bottleneck problem of traditional methods being limited by hardware resources in the calculation of high-order gravity field models.

[0038] Further, step S3 includes: acquiring memory size data, video memory size data, number of slice columns, and number of temporary slice rows and blocks; performing row and column slicing processing on the target covariance matrix based on the memory size data, the video memory size data, the number of slice columns, and the number of temporary slice rows and blocks to obtain the multiple target slices.

[0039] The number of rows in the temporary slice refers to the number of matrix block rows loaded into memory in a single process during slicing, in order to avoid excessive memory usage.

[0040] The multiple target slices can store self-covariance matrix blocks and global coupling matrix blocks, forming multiple slice files divided by order. This enables spectral domain recursive error propagation calculations even when memory resources are insufficient to load the complete covariance matrix. The multiple slice files can be multiple binary slice files, each storing the covariance data corresponding to one or more spherical harmonic orders in row-major order. The number of spherical harmonic orders contained in each slice file can be set by the interactive interface parameters or automatically determined based on available memory, video memory, and computation batch size. For any spherical harmonic order, the slice file includes a covariance submatrix between parameters of that order, and a coupling covariance matrix block between that order parameter and all effective model parameters. Therefore, during recursive error propagation, only the covariance slices required for the current calculation need to be loaded, without loading the entire covariance matrix, thus significantly reducing runtime memory requirements.

[0041] For example, assuming that the embodiments of this application include slices of parameters of order a to b, the mathematical expression of the self-covariance matrix block is: The global coupling matrix block (i.e., the parameter block of order 2 to n) and to The mathematical expression for the covariance matrix block of the order parameter coupling is: ;in, It is the first The autocovariance matrix block of the spherical harmonic coefficients; It is the first Rank and number Submatrix blocks of spherical harmonic coefficients; It is the first Rank and number Submatrix blocks of spherical harmonic coefficients; It is the first The autocovariance matrix block of the spherical harmonic coefficients; It is the second order and the... Submatrix blocks of spherical harmonic coefficients; It is the second order and the... Submatrix blocks of spherical harmonic coefficients; It is the first Rank and number Submatrix blocks of spherical harmonic coefficients; It is the first Rank and number A submatrix block of spherical harmonic coefficients.

[0042] Furthermore, the first Step The covariance submatrix is ​​represented as: ; in, , It is the first The total number of spherical harmonic coefficients; It is the first The autocovariance of the second-order spherical harmonic coefficients; It is the first Within the first rank Components and the first Covariance sub-blocks of components; It is the first Within the first rank Components and the first Covariance sub-blocks of components; It is the first Rank Autocovariance of the sub-spherical harmonic coefficients.

[0043] Furthermore, the first Order parameters and to The block representation of the covariance matrix of the first-order parameter coupling is as follows: ;in, yes Order parameters and A block of covariance matrices coupled with order parameters; yes Order parameters and A block of covariance matrices coupled with order parameters; yes Order parameters and A block of covariance matrices coupled with order parameters.

[0044] In other implementations, an internal covariance block and a cross-covariance block between each slice and all retained parameters may also be generated.

[0045] By using slicing techniques, the embodiments of this application can achieve block-based computation and breakpoint continuation under large-scale covariance matrix conditions, avoiding repeated computations caused by interruptions, thereby improving overall computational efficiency and system robustness.

[0046] S4. Using the spectral domain recursive error propagation calculation method, the target covariance matrix or the multiple target slices are calculated and processed sequentially in all spherical harmonic orders of each latitude batch to obtain the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch.

[0047] It should be understood that for each latitudinal batch, the spectral domain recursive calculation is performed sequentially in ascending order of spherical harmonic order.

[0048] S5. Evaluate the gravitational field of the target planet based on the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the radial acceleration of all non-central terms.

[0049] Through the above implementation methods, the embodiments of this application introduce a spectral domain recursive error propagation calculation method and a matrix slicing method, which can efficiently complete the successive error propagation calculation under limited computing resources.

[0050] In some implementations, when step S4 is "using the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of the radial acceleration of the non-central term corresponding to each spherical harmonic order in each latitude batch", before performing the spectral domain recursive calculation step by step in ascending order of spherical harmonic order, the first design quantity (i.e., the radial acceleration partial derivative of the spherical harmonic coefficients of each grid point) corresponding to each spherical harmonic order in each latitude batch can be constructed first, and the first cumulative error and the first strong recording variable can be initialized.

[0051] Furthermore, when the target covariance matrix is ​​calculated step by step, the calculation formula for the first design quantity corresponding to each spherical harmonic order in each dimensional batch can be expressed as: ; in, It is the first in each latitude batch The first design quantity corresponding to the harmonic order of a sphere; It is the first partial derivative of the transpose of the radial acceleration of the non-central term corresponding to the second spherical harmonic order in each latitudinal batch with respect to the spherical harmonic coefficient of the gravitational field corresponding to the second spherical harmonic order in each latitudinal batch. It is the first in each latitude batch The transpose of the non-central radial acceleration corresponding to each spherical harmonic order corresponds to the first term in each latitudinal batch. The first partial derivative of the spherical harmonic coefficients of the gravitational field corresponding to each spherical harmonic order; It is the state increment vector corresponding to the second spherical harmonic order in each dimensional batch; It is the first in each latitude batch The state increment vector corresponding to each spherical harmonic order.

[0052] It should be understood that in each batch at each latitude, the first... The state increment vector corresponding to each spherical harmonic order can be understood as the state increment vector of the th dimensional batch in each dimensional batch. A column vector consisting of the partial derivatives of all spherical harmonic coefficients corresponding to each spherical harmonic order.

[0053] The first design quantity corresponding to each spherical harmonic order in each latitude batch can be understood as the partial derivative of the radial acceleration of the non-central term with respect to the spherical harmonic coefficients of the gravitational field, from 2 to... The design vector is composed of elements of order.

[0054] Further, the step of using the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch, includes: using a first preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch; using a second preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value of the non-central radial acceleration corresponding to each spherical harmonic order in ... The actual signal value corresponding to each spherical harmonic order in each latitude batch; the third preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; the fourth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the fifth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

[0055] Furthermore, the calculation formula for the step of using the fifth preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch is as follows: ; in, It is the first in each latitude batch The cumulative error value corresponding to each harmonic order; It is the first in each latitude batch The cumulative non-central radial acceleration corresponding to each spherical harmonic order; It is the first in each latitude batch The state increment vector corresponding to each harmonic order; yes Transpose of; It is the first in each latitude batch Auxiliary terms corresponding to the harmonic order of each sphere; It is the target covariance matrix; It is the first in each latitude batch The cumulative error value corresponding to each harmonic order; It is the first in each latitude batch The incremental contribution of each harmonic order to the variance.

[0056] Furthermore, when calculating the target covariance matrix step by step, the first [value] in each dimensional batch Auxiliary terms corresponding to the harmonic order of a sphere Defined as: ;in, It is the first of the target covariance matrix. List.

[0057] Furthermore, the first of the target covariance matrix The column expression is: ; in, It is the first of the target covariance matrix. The second-order components; It is the first of the target covariance matrix. The third-order components; It is the first of the target covariance matrix. Liede The components of the order. , yes A 3D real matrix It is 2 to Total number of spherical harmonic coefficients, It is the first to The total number of spherical harmonic coefficients of order 1.

[0058] Furthermore, the calculation formula for the step of using the first preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitudinal batch to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitudinal batch is as follows: ; in, It is the first in each latitude batch The theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order; It is the gravitational constant of the target planet; It is the mass of the target planet; It is the radius of the target planet; It is Kaula's constant; It is the order.

[0059] The Kaula theoretical signal describes the general law of gravitational field spectral power decay with order and can serve as a consistent reference standard between different regions of a planet.

[0060] Furthermore, in In this case, , Then, the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch is... The calculation formula is: .

[0061] Furthermore, when calculating the target covariance matrix step by step, if a certain signal-to-noise ratio needs to be satisfied... Then, the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch is... The calculation formula is: ; in, It's the signal-to-noise ratio.

[0062] It should be understood that, The value of can be 1. In other implementations, The value can be set by those skilled in the art according to actual needs.

[0063] From the second order (i.e., the second spherical harmonic order) to the maximum order of the model, calculate the corresponding theoretical signal strength (i.e., The theoretical signal curve is obtained and can be used for subsequent order strength determination.

[0064] Furthermore, the calculation formula for the step of using the second preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch is as follows: ; in, Grid points In the The actual signal value corresponding to each spherical harmonic order; It is an associated Legendre function; These are the spherical harmonic coefficients of the cosine term of the gravitational field; It is the number of spherical harmonic expansions in the gravitational field; It is the longitude of the target planet; It is the spherical harmonic coefficient of the sinusoidal term of the gravitational field.

[0065] When using actual signals (i.e., actual signal values), strong anomalies will display higher orders due to their larger signal size, while weak anomalies will display lower orders. This results in a mixture of varying geological signal strength, rather than simply reflecting the model's accuracy. Therefore, actual signal values ​​reflect the model's single-order gravity signal contribution and global gravity signal differences.

[0066] Furthermore, the calculation formula for the step of using the third preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch is as follows: ; in, It is the first in each latitude batch The error value corresponding to each harmonic order; It is a cumulative total of 2 to The standard deviation of the radial acceleration of the non-central term (i.e., the cumulative 2 to 1) (cumulative error of radial acceleration of non-central term). It is a cumulative total of 2 to The standard deviation of the radial acceleration of the non-central term (i.e., the cumulative 2 to 1) The cumulative error of the radial acceleration of the non-central term.

[0067] Furthermore, by calculating the target covariance matrix step by step, the cumulative 2 to... is obtained by the error propagation theorem. The variance of the radial acceleration of the non-central term is: ;in, It is the partial derivative of radial acceleration with respect to the spherical harmonic coefficients of the gravitational field. It is 2 to A vector consisting of all spherical harmonic coefficients of order 1.

[0068] Furthermore, the fourth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch, to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch (which can also be understood as the cumulative value from 2 to 1). The formula for calculating the non-central term radial acceleration spherical harmonic of order is: ; in, It is the first in each latitude batch The cumulative signal value corresponding to each harmonic order; It is an associated Legendre function; These are the spherical harmonic coefficients of the cosine term gravitational field; It is the spherical harmonic coefficient of the gravitational field of the sinusoidal term.

[0069] The method described above, which employs the steps of "calculating the target covariance matrix step by step in all spherical harmonic orders of each latitude batch using a spectral domain recursive error propagation calculation method to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch," can be called the "spherical harmonic spectral domain recursive step-by-step error propagation calculation using the complete covariance matrix" method. This method enables the reuse of already calculated results, ensuring calculation accuracy while avoiding redundant calculations, thereby significantly improving calculation efficiency.

[0070] The method of "recursive successive error propagation calculation in the spherical harmonic domain using the complete covariance matrix" stores the error in memory and reuses it in subsequent calculations. , It avoids repetitive calculations in traditional computing.

[0071] When the When the time-order error value is greater than or equal to the signal strength value, that is... hour, Let be the order strength at that point.

[0072] In some implementations, when step S4 is "using the spectral domain recursive error propagation calculation method to calculate and process the multiple target slices sequentially in all spherical harmonic orders of each latitude batch, to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch," for each latitude batch, this embodiment first constructs the second design quantity (i.e., the radial acceleration partial derivative vector of the spherical harmonic coefficients of each grid point) corresponding to that latitude batch, and initializes the second cumulative error and the second-order strong recording variable. Subsequently, each slice is processed sequentially within each latitude batch. For the current slice, recursive calculation is performed sequentially according to the order range it contains.

[0073] Further, the step of using the spectral domain recursive error propagation calculation method to calculate and process the multiple target slices step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch, includes: using the first preset algorithm to calculate and process the multiple target slices step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; using the second preset algorithm to calculate and process the multiple target slices step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in ... The actual signal value corresponding to each spherical harmonic order in each latitude batch; the third preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; the fourth preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the sixth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

[0074] Furthermore, the calculation formula for the step of using the sixth preset algorithm of the spectral domain recursive error propagation calculation method to calculate and process the multiple target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch is as follows: ; in, It is the first in each latitude batch The cumulative error value corresponding to each harmonic order; It is the first in each latitude batch The cumulative error value corresponding to each harmonic order; It is the first in each latitude batch The state increment vector corresponding to each harmonic order; Represents transpose; It is the first slice after slicing order (i.e., the first) An auxiliary term for the cumulative variance of each spherical harmonic order.

[0075] Furthermore, The calculation formula is: ;in, This line is truncated Step to The order and column are fixed as the first A cross-order cross-covariance slice matrix of order; It is the first to A column vector consisting of the partial derivatives of all spherical harmonic coefficients of order 1.

[0076] Furthermore, the first to The partial derivative vector of the order coefficients is expressed as: ;in, It is the first The first-order state increment vector; It is the first The state increment vector.

[0077] Once the cumulative variance of all orders for this slice has been calculated, the global auxiliary term update is as follows: ; in, It is used as the initial state for the recursive calculation of the next slice, and is used to update subsequent auxiliary terms; This indicates a global auxiliary item that updates all slices.

[0078] Furthermore, the calculation formula for the step "using the first preset algorithm to perform calculation processing on the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch" can follow the calculation formula for the step "using the first preset algorithm of the spectral domain recursive error propagation calculation method to perform calculation processing on the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch".

[0079] Furthermore, the calculation formula for the step "using the second preset algorithm to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch" can follow the calculation formula for the step "using the second preset algorithm of the spectral domain recursive error propagation calculation method to calculate and process the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch".

[0080] Furthermore, the calculation formula for the step "using the third preset algorithm to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch" can follow the calculation formula for the step "using the third preset algorithm of the spectral domain recursive error propagation calculation method to calculate and process the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch".

[0081] When the When the time-order error value is greater than or equal to the signal strength value, that is... hour, Let be the order strength at that point.

[0082] The above derivation describes a method for calculating the cumulative error of radial acceleration of order strength and non-central terms based on error propagation using spherical harmonic order recursion, by introducing an auxiliary term. The traditional quadratic form calculation is transformed into a spectral domain recursive form, and combined with the covariance matrix block strategy, efficient step-by-step error propagation calculation of the covariance matrix of a high-order spherical harmonic gravity field model is realized under limited memory conditions.

[0083] Furthermore, the calculation formula for the step "using the fourth preset algorithm to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch" can follow the calculation formula for "using the fourth preset algorithm of the spectral domain recursive error propagation calculation method to calculate and process the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch".

[0084] In some implementations, after step S4, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: after the target latitude batch is calculated, writing the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the radial acceleration of the non-central terms corresponding to all spherical harmonic orders of the target latitude batch into intermediate storage, and continuing to process the next latitude batch. The target latitude batch is any batch among all latitude batches, and can also be understood as the current latitude batch.

[0085] In some implementations, after step S4, the gravity field assessment method based on spherical harmonic domain recursion and structured matrix blocks further includes: splicing the cumulative error values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain a cumulative error value fusion result; splicing the theoretical signal values ​​of the non-central radial acceleration corresponding to all spherical harmonic orders in all latitudinal batches to obtain a theoretical signal value fusion result; splicing the actual signal values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain an actual signal value fusion result; splicing the error values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain an error value fusion result; splicing the cumulative signal values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain a cumulative signal value fusion result; and displaying the cumulative error value fusion result, the theoretical signal value fusion result, the actual signal value fusion result, the error value fusion result, and the cumulative signal value fusion result.

[0086] In some implementations, after step S4, the gravity field assessment method based on spherical harmonic domain recursion and structured matrix blocks further includes: determining whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value of the non-central term corresponding to the target spherical harmonic order is greater than a preset value; if so, recording the target spherical harmonic order as an order strength value, wherein the target spherical harmonic order is any one of all spherical harmonic orders.

[0087] The preset value is set to 1. In other embodiments, the specific value of the preset value can be set by those skilled in the art according to actual needs.

[0088] In some embodiments, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: assessing the gravity field of the target planet based on the order strength value.

[0089] In some implementations, after determining whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value corresponding to the target spherical harmonic order is greater than a preset value, and if so, recording the target spherical harmonic order as an order strength value, the gravity field evaluation method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: splicing all order strength values ​​to obtain an order strength value fusion result; and displaying the order strength value fusion result.

[0090] In some implementations, the target planet is The gravitational potential generated at the location The expression is: ; in, It is the reference radius of the target planet; It is the gravitational constant; It is the mass of the target planet; It is the radial distance to the target planet; It is the normalized associated Legendre function; and All are normalized spherical harmonic coefficients; It is latitude; It is longitude; It is the order; It refers to the number of times.

[0091] Take the partial derivative of the gravitational potential with respect to radial distance (i.e., the negative of the radial gravitational acceleration): ; For grid points On the reference sphere, the reference radius is Then the radial acceleration on the reference sphere is: ; The radial acceleration of the non-central term on the reference sphere is the first The mean square of order can be expressed as: ; in, It is the surface of the ball. ,get: ; The normalized associated Legendre functions are orthogonal (Colombo, 1981): ; According to Parseval's theorem for spherical harmonics (Varshalovich et al., 1988): ; ; in, These are fully normalized spherical harmonic basis functions; It is a spherical scalar field correspond Normalized spherical harmonic expansion coefficients of order; Used to distinguish physical components.

[0092] This allows the radial acceleration of the non-central term on the reference sphere to be... The mean square of order simplifies to: ; Attenuation trend of signal power spectrum curve under Kaula criterion: .

[0093] In some implementations, prior to step S1, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes reading the spherical harmonic coefficients of the gravity field model and the corresponding complete covariance matrix data, and establishing a unified index construction and order mapping relationship for the spherical harmonic coefficients.

[0094] In some implementations, embodiments of this application may introduce random sampling or Monte Carlo methods to estimate the uncertainty propagation results, in order to replace the spectral domain recursive error propagation calculation method.

[0095] In some implementations, embodiments of this application may use a method that combines frequency domain filtering or bandpass analysis to calculate errors within a specific spatial scale range, instead of the spectral domain recursive error propagation calculation method.

[0096] It should be noted that the technical effects brought about by the embodiments of this application can be explained by a comparison of time complexity. Let the maximum spherical harmonic order be N, and the covariance parameter be... The number of grid points is calculated as follows: For traditional error propagation algorithms, the complexity of calculating physical quantity errors step by step is O(n). The spectral domain recursive error propagation algorithm proposed in this application avoids the repeated calculations at each order in traditional error propagation algorithms by incrementally updating the algorithm, thus reducing the complexity to [missing information]. The speedup ratio is For example, taking a 660th-order gravity field model as an example, according to complexity analysis, the embodiments of this application can achieve a theoretical computational reduction of approximately 660 times compared to the traditional sequential independent error propagation method. However, in actual computing environments, algorithm performance is also affected by factors such as storage hierarchy access efficiency, memory bandwidth, and I / O throughput, so there is usually a certain difference between the actual runtime speedup and the theoretical value. Nevertheless, as the model size continues to increase, the embodiments of this application still have significant advantages in terms of computational efficiency and resource utilization.

[0097] In some implementations, prior to step S1, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: reading the spherical harmonic coefficients of the gravity field model and establishing a unified index construction and order mapping relationship for the spherical harmonic coefficients.

[0098] It should also be noted that, in the embodiments of this application, progress logs and status information are continuously recorded during the slice construction and calculation process. When an abnormal interruption occurs, the completed progress can be verified by reading the recovery status file, and execution can resume from the interrupted position, thereby achieving breakpoint continuation.

[0099] It should be understood that the "structured matrix" described in this article refers to matrix blocks, which is the matrix form applicable to the algorithm.

[0100] refer to Figure 4 and Figure 5 The diagram shown is a principle block diagram of a gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks, provided in the second aspect of an embodiment of this application. Figure 4 and Figure 5 The gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks includes: Data acquisition module 101 is used to acquire the target covariance matrix and latitude and longitude calculation grid corresponding to the target planet; The grid division module 102 is used to divide the latitude and longitude calculation grid into multiple latitude batches along the latitude direction; The slicing module 103 is used to perform row and column slicing on the target covariance matrix to obtain multiple target slices; The calculation module 104 is used to calculate the target covariance matrix or the multiple target slices in each latitude batch in all spherical harmonic orders by using the spectral domain recursive error propagation calculation method, so as to obtain the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch; Evaluation module 105 is used to evaluate the gravitational field of the target planet based on the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of radial acceleration of all non-central terms.

[0101] In some embodiments, the data acquisition module 101 includes a graphical interaction module, a matrix construction module, and a grid acquisition module. The graphical interaction module is used to acquire the model file (i.e., the gravity field model data file); the matrix construction module is used to generate the target covariance matrix based on the compressed upper triangular covariance data of the model file; and the grid acquisition module is used to acquire the latitude and longitude calculation grid.

[0102] The graphical interaction module is also used to receive user input parameters. These input parameters include a tag description file corresponding to the model file, the calculation order range, the latitude and longitude grid range, the latitude and longitude sampling interval, the covariance matrix reading mode, memory and video memory resource constraints, the drawing projection method, the color band enhancement parameters, and the result output parameters. The graphical interaction module is also used to perform preliminary validation of the user-input file path, numerical parameters, and switch options, and convert these parameters into unified command parameters that can be recognized by subsequent calculation modules.

[0103] In some implementations, the matrix construction module is also used to extract submatrices to be used in the calculation according to the parameter index set.

[0104] In some implementations, the matrix construction module has a complete covariance matrix mode, and the slicing module has a slicing mode. The complete covariance matrix mode generates the target covariance matrix based on the compressed upper triangular covariance data of the model file; the slicing mode divides the target covariance matrix into rows and columns based on the memory size data, the video memory size data, the number of slice columns, and the number of rows in the temporary slice blocks to obtain the multiple slices. For details, please refer to the first aspect of the embodiments of this application.

[0105] In some implementations, the grid acquisition module is further configured to generate the latitude and longitude calculation grid based on a preset latitude and longitude range and a preset latitude and longitude interval.

[0106] In some embodiments, the calculation module 104 is further configured to use a first preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch, to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; use a second preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix sequentially in all spherical harmonic orders of each latitude batch, to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch; and use a third preset algorithm of the spectral domain recursive error propagation calculation method in... The target covariance matrix is ​​calculated sequentially for each spherical harmonic order in each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch. The fourth preset algorithm of the spectral domain recursive error propagation calculation method is then used to calculate the target covariance matrix sequentially for each spherical harmonic order in each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch. Finally, the fifth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix sequentially for each spherical harmonic order in each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

[0107] In some embodiments, the calculation module 104 uses the first preset algorithm to perform calculations on the plurality of target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; uses the second preset algorithm to perform calculations on the plurality of target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch; uses the third preset algorithm to perform calculations on the plurality of target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; uses the fourth preset algorithm to perform calculations on the plurality of target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; and uses the sixth preset algorithm of the spectral domain recursive error propagation calculation method to perform calculations on the plurality of target slices sequentially in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

[0108] In some implementations, the gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks further includes a parameter identification module. This module parses the record structure and data description information in the label description file, identifying key reading parameters such as record length, header record number, name record number, spherical harmonic coefficient record number, coefficient covariance record number, parameter name length, and covariance matrix storage order. When the information provided by the label description file is complete, the system prioritizes the record parameters from the label description file; when the user explicitly specifies some parameters in the graphical interface or command parameters, the user-specified values ​​are used as the priority; when the covariance storage order is not given in the label description file, the system uses the user-specified storage order for parsing. Through the above settings, the system establishes a unified binary reading parameter structure for subsequent model data access.

[0109] In some embodiments, the gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks further includes a file reading module. This module performs binary parsing of the model file according to the record length, record number, parameter name length, and covariance matrix storage order determined by the parameter identification module. Specifically, the system first locates the model header record based on the header record number, extracting the reference radius of the target planet, the planetary gravitational constant, the maximum order of the gravity field model, the Legendre function normalization state, and the number of parameter names. Then, it reads the parameter name record according to the name record number and parameter name length to obtain the names of each spherical harmonic coefficient term and constant term. Next, it reads the spherical harmonic coefficient record according to the coefficient record number to obtain the model coefficient values ​​corresponding to each parameter name. For the covariance matrix data, the system establishes an access method for the covariance data area based on the covariance record number and covariance matrix storage order, for subsequent full matrix loading or slice-based reading.

[0110] In some embodiments, the gravity field assessment system 100 based on spherical harmonic domain recursion and structured matrix blocks further includes a preprocessing module, which is used to register all cosine and sine terms corresponding to each spherical harmonic order according to their positions in the original model parameter table to form a successive parameter mapping table.

[0111] The successive parameter mapping table records the parameter index, degree information, sine or cosine type information, and compressed matrix position for each order. During successive iterations, the calculation module can directly extract the parameter block and covariance block corresponding to the current order based on the successive parameter mapping table.

[0112] In some embodiments, the gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks further includes a calculation log module for storing the calculation process of the calculation module. The log module is also used to store the slicing process of the slicing module.

[0113] In some embodiments, the gravity field assessment system 100 based on spherical harmonic domain recursion and structured matrix blocks further includes a fusion module, used to splice the cumulative error values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain a cumulative error value fusion result; splice the theoretical signal values ​​of the non-central radial acceleration corresponding to all spherical harmonic orders in all latitudinal batches to obtain a theoretical signal value fusion result; splice the actual signal values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain an actual signal value fusion result; splice the error values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain an error value fusion result; splice the cumulative signal values ​​corresponding to all spherical harmonic orders in all latitudinal batches to obtain a cumulative signal value fusion result; and display the cumulative error value fusion result, the theoretical signal value fusion result, the actual signal value fusion result, the error value fusion result, and the cumulative signal value fusion result.

[0114] In some embodiments, the gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks further includes a plotting module, which is used to generate a single-order error map grid diagram from the fusion result of the cumulative error values, generate a theoretical signal value grid diagram from the fusion result of the theoretical signal values, generate an actual signal value grid diagram from the fusion result of the actual signal values, generate an error value grid diagram from the fusion result of the error values, generate a cumulative signal value grid diagram from the fusion result of the cumulative signal values, and generate an order intensity map from the fusion result of the order intensity values.

[0115] The order strength map reflects the local error level after the model covariance error propagates, representing the highest effective order that can be supported at each location.

[0116] In some implementations, the gravity field assessment system 100 based on spherical harmonic spectral domain recursion and structured matrix blocks also provides a human-computer interaction interface. This interface adopts a modern integrated design, concentrating functions such as model file selection, covariance slicing, order strength calculation, signal and error plotting, batch result redrawing, model constant setting, and operation log monitoring into a single window. Users can complete path configuration, parameter setting, task initiation, result redrawing, and operation status viewing within the same interface, thereby reducing window switching and improving operational efficiency. The entire interface, from top to bottom, mainly consists of a file and path configuration area, a workflow tab area, a covariance slicing setting area, a calculation and plotting setting area, a model constant setting area, a task control area, and a log display area.

[0117] Specifically, the file and path configuration area is located in the Control Deck area at the top of the interface, used to complete the main input and output path settings. The Model file is used to select the model file, which is the main input for the entire calculation process. The Output path is used to set the output directory for images and result files. The Batch path is used to specify the directory for the generated batch results, mainly used for batch result redrawing. Each path input box in the interface has a Select button, facilitating quick selection of the corresponding path via file or folder dialog boxes.

[0118] The file and path configuration area also includes a Slice path, which specifies the storage location of the covariance slice file. In slice mode, it can be used to create new slices or read existing slices.

[0119] It should be noted that the current interface does not have a separate input box for covariance label description files. When the user selects a model file, the program will automatically attempt to identify the corresponding label description file and automatically fill in some record format parameters and model constants based on the label content, thereby reducing the amount of manual input.

[0120] The Workflow tab area is located within the Workflow region and uses three tabs—Slicing, Run & Plot, and Constants—to organize the main functions. Slicing is used for covariance slicing preprocessing, Run & Plot is used for order strength calculation, error plotting, and batch result redrawing, and Constants is used to set the model reading format and theoretical constants.

[0121] The covariance slicing settings area is accessed via the Slicing tab and is used to control the preprocessing of covariance slices. The Slice Covariance button is used to start the slice construction task. Key parameters in this area include Lat batch, Usable RAM, VRAM ignored, Slice cols, and Row chunk. Lat batch represents the reference latitude batch size used during slice planning, used to estimate the grid size of subsequent single batches to automatically plan slice width and row chunk size. Usable RAM represents the maximum amount of main memory allowed during the slice construction stage. VRAM ignored indicates that video memory is not used during the single-core slicing stage. Slice cols controls the column width of a single covariance slice, and Row chunk controls the number of rows in the matrix chunks during slice construction. When Slice cols and Row chunk are set to 0, the program will automatically estimate appropriate values ​​based on memory conditions. The calculation and plotting settings area is accessed via the Run & Plot tab and is used to set the order strength calculation and plotting output tasks. The Compute Map button is used to start the complete calculation task, outputting the order strength map, the fixed-order cumulative error map, and the local order error map. The Replot Batches button reads existing batch results and replots them without recalculating the spectral domain. The Extra Map button opens an extra plotting window for a specified order range. The order range can be set via Start degree and End degree, and plotting can be started via Run Maps. This function outputs four types of plots for each selected order: signal, noise, cumulative signal, and cumulative noise.

[0122] In the calculation and plotting settings area, there is also a Run mode, used to select the covariance processing method, including two modes: Use Covariance Slices and Load Full Covariance (Dense). Device is used to select the calculation backend, currently supporting both CPU and GPU modes. Slice status displays whether the current slice directory matches the model file, such as Matched, Not selected, or Signature mismatch. The Check Slice button is used to manually check the slice validity.

[0123] In the calculation and plotting settings area, "Latitudes per batch" indicates the number of latitude lines included in each latitude batch during the formal calculation phase. "Usable RAM" and "Usable VRAM" limit the main memory and video memory resources available during the calculation phase, respectively. "Projection" selects the plotting projection method; currently, Rect grid and Mollweide projections are supported. "Colormap" selects the color mapping scheme. "Draw contours" controls whether contour lines are overlaid in the plot; it is off by default. "Noise curve" controls whether error curve-related results are output. "Color scale" indicates the color band enhancement factor; the default value of 1.0 indicates enhancement is off. "Color min" and "Color max" specify the data distribution range for color enhancement, with values ​​ranging from 0 to 1.

[0124] The plotting area is set using two sets of range controls: Latitude range and Longitude range. Each set of range controls provides Min and Max input boxes and sliders for more intuitively defining the latitude and longitude range of the study area. The Global extent button can restore the global extent with one click. Lat step and Lon step are used to set the grid step size, and Contour step is used to set the contour interval when plotting.

[0125] The model constants setting area is accessed via the Constants tab and is primarily used to configure file reading format parameters and theoretical model constants. REC_BYTES, REC_HEADER, REC_NAMES, REC_COEFF, REC_COV, and NAMES_TABLE_LEN control how various records in the model file are read. Kaula scale adjusts the overall amplitude of the Kaula curve. Cov upper order specifies the storage order of the upper triangular covariance matrix, with options for auto, row, and column. Cumulative noise map degree specifies the order at which the fixed-order cumulative error map is plotted; either a specific integer or `max` indicates using the maximum model order.

[0126] The task control area is located above the Runtime Log area and includes two buttons: Stop and Clear Log. Stop is used to terminate the currently executing calculation or plotting task, as well as the currently executing slicing task. Clear Log is used to clear the log window content, allowing the user to review subsequent execution processes.

[0127] The log display area, located at the bottom of the interface, is a text window used to display the program's running status in real time. Log content includes task startup information, executed commands, batch save information, drawing completion information, error messages, and the final process exit status. In the current version, a local timestamp is automatically added before each line of information in the log area for easy tracking of task execution order and runtime.

[0128] The log content in the log display area also includes the slice construction progress.

[0129] The human-computer interaction interface of this application embodiment, with tabbed workflow and integrated parameter control as the core, realizes a complete interactive process from model input, order strength calculation, error plot drawing, additional order plot output, batch result redrawing to log monitoring, providing a unified, intuitive and more compact modern human-computer interaction platform for the order strength calculation program.

[0130] The human-computer interaction interface is designed to monitor the calculation progress and running status in real time, reduce operational complexity, improve ease of use, and enhance the system's practicality and scalability.

[0131] In practical applications, this embodiment can use the lunar high-order gravity field model jggrx_0660b_shb as the processing object. The lunar gravity field model jggrx_0660b_shb is a high-order gravity field model in spherical harmonic expansion form, with a maximum order of 660. Its parameters include 436,918 spherical harmonic coefficients and a corresponding upper triangular covariance matrix containing 9,544,888,7821 independent elements. Its binary storage file size is 745 Gb. The spherical harmonic coefficients are used to describe the characteristics of the lunar gravity field signal, and the covariance matrix is ​​used to characterize the uncertainty of the spherical harmonic coefficients and the correlation between parameters.

[0132] In practice, user input is first received through a graphical user interface module. The user selects the lunar gravity field model data file jggrx_0660b_shb.dat and its corresponding tag description file jggrx_0660b_shb.lbl in the interface, and sets the calculation mode, computation grid, memory parameters, video memory parameters, latitude batch quantity, and whether to enable covariance slicing, among other operating parameters. After receiving the input, the main script scheduling module calls the file reading module to read and perform preliminary verification of the input file.

[0133] Subsequently, the parameter recognition module identifies structural information from the jggrx_0660b_shb.lbl file, including record length, record number, name length, starting record position of spherical harmonic coefficients, starting record position of the covariance matrix, and the upper triangular storage order of the covariance data. Through this step, the system obtains the positioning parameters required to read the jggrx_0660b_shb.dat binary model data, thereby accurately locating the model header information, parameter name table, spherical harmonic coefficient table, and covariance matrix data.

[0134] After parsing the tag file, the parameter identification module reads the header information and parameter name table from the model file based on the aforementioned record structure information, and uniformly identifies and organizes the model parameters to establish a model parameter description structure. This structure includes the spherical harmonic coefficient name, order, degree, cosine or sine term type, parameter number, covariance matrix index, and model constants. Based on this, the preprocessing module constructs an index set, an order term index mapping relationship, and a set of constants required for calculation, enabling spherical harmonic coefficients of different orders and degrees to be quickly located and called in subsequent error propagation calculations.

[0135] When using the spherical harmonic domain recursive calculation of the complete covariance matrix (i.e., using the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch), the file reading module directly reads and loads the spherical harmonic coefficients from order 2 to 660 and their corresponding covariance matrices, constructs recursive auxiliary terms based on the global covariance matrix, and updates the cumulative variance step by step according to the spherical harmonic order from low to high. In each order calculation, the system extracts the design quantity and covariance sub-block corresponding to the current order. The covariance contribution of this order and its coupling contribution with the accumulated lower-order parameters are calculated to obtain the incremental contribution of the current order to the cumulative radial acceleration variance. .

[0136] When performing spherical harmonic domain recursive calculations using structured covariance matrix slicing (i.e., calculating and processing the multiple target slices sequentially across all spherical harmonic orders in each latitude batch using the spectral domain recursive error propagation method), the system no longer loads the complete covariance matrix at once. Instead, it determines the block size of the covariance matrix based on the user-input parameters of available memory, video memory, number of slice columns, and temporary row block size. The slice construction module divides the covariance matrix into slices, and each slice file includes the self-covariance submatrices of each order parameter within the current slice. and global coupling matrix block This enables spectral domain recursive error propagation calculations even when memory resources are insufficient to load the complete covariance matrix.

[0137] In the spectral domain recursive error propagation calculation stage, the matrix construction module first constructs the design quantity of the partial derivative of the radial acceleration of the non-central term with respect to the spherical harmonic coefficients based on the lunar reference radius, gravitational constant, spherical harmonic order, degree, and computational grid. The system divides the user-selected latitude and longitude grid into multiple calculation batches according to the latitudinal direction to control the data scale of a single calculation. For each latitudinal batch, the system initializes the cumulative variance, cumulative standard deviation, recursive auxiliary terms, and order strength result array, and then performs recursive calculations order by order from low to high according to the spherical harmonic order. For the... For the spherical harmonic order, the system uses a spectral domain recursive algorithm to calculate the incremental contribution of this order to the variance of the radial acceleration of the non-central term. This increment is then added to the cumulative variance of the previous grid point. In this process, the cumulative variance of the radial acceleration of the non-central term of that order, i.e., the cumulative error, is obtained. + This avoids the repetitive calculation process in traditional methods and calculates the Kaula signal of the non-central radial acceleration of this order. Update the cumulative signal and error values ​​for this order using the actual signal, error, and cumulative signal. Compare the cumulative error with the theoretical signal obtained based on the Kaula criterion. The system performs comparisons. When the cumulative standard deviation of a grid point first reaches or exceeds the theoretical signal strength of the corresponding order, the system records that order as the order strength value of that grid point. This order strength value characterizes the maximum spherical harmonic order that the lunar gravity field model can reliably support at that location, thus reflecting the local accuracy and effective spatial resolution of the gravity field model in that region. After all latitude and longitude batches are calculated, the system outputs the following grid maps based on user selection: order strength grid map, actual signal grid map, single-order signal grid map, cumulative actual signal grid map, and single-order error grid map.

[0138] Through the above applications, the methods and systems described in this application can process the gravity field model jggrx_0660b and its covariance data, and can efficiently realize the numerical calculation of error propagation of large-scale matrices under limited resources, thereby improving the computational efficiency and engineering applicability of high-order gravity field model accuracy evaluation while ensuring computational accuracy.

[0139] In the above applications, the order intensity map (also known as the order intensity grid map) can be referenced. Figure 6 ( Figure 6 As shown in the diagram (with the Moon as the target planet), the order strength grid is used to characterize the highest spherical harmonic order that the gravity field model can effectively support at different spatial locations. The spatial distribution of the order strength values ​​can be used to identify regional differences in model accuracy and resolution; the higher the order strength value, the more likely the region can still support higher-order gravity field information after error propagation, thus exhibiting higher theoretical spatial resolution and stronger local accuracy support capability. Figure 6It is also the order intensity diagram of the lunar gravity field model jggrx0660b.

[0140] The cumulative actual signal grid diagram can be referenced. Figure 7 ( Figure 7 (With Mars as the target planet) As shown. The cumulative actual signal grid diagram represents the spatial distribution of the radial acceleration signal at each grid point after accumulating from the second order to the specified order. Figure 7 It is also the intensity map of the gravity field model of Mars MRO120d.

[0141] The single-order signal grid diagram can be referenced. Figure 8 ( Figure 8 As shown in the image (with Mars as the target planet). Figure 8 It is also the 120th order cumulative signal diagram of the Mars MRO120d gravity field model.

[0142] The single-order error map grid diagram can be referenced. Figure 9 ( Figure 9 As shown in the image (with Mars as the target planet). Figure 9 This is also the 7th order unit error diagram of the Mars MRO120d gravity field model.

[0143] Therefore, the embodiments of this application are particularly applicable to the calculation of successive error propagation in high-order physical quantity models.

[0144] A third aspect of this application provides a terminal device, the schematic diagram of which is as follows: Figure 10 As shown. The terminal device includes a processor, memory, network interface, display screen, and temperature sensor connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the terminal device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks. The display screen can be a liquid crystal display (LCD) or an e-ink display. The temperature sensor is pre-installed inside the terminal device to detect the operating temperature of the internal components.

[0145] Those skilled in the art will understand that Figure 10 The schematic diagram shown is only a partial structural diagram related to the present invention and does not constitute a limitation on the terminal device to which the present invention is applied. The specific terminal device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0146] In some embodiments, this application provides a terminal device, which includes a processor and a memory. The memory stores a computer program, and the processor calls and runs the computer program stored in the memory to perform the steps of the gravity field assessment method based on spherical harmonic domain recursion and structured matrix blocks provided in the first aspect of this application.

[0147] A fourth aspect of this application provides a computer-readable storage medium for storing a computer program that causes a computer to perform the steps of the gravity field assessment method based on spherical harmonic domain recursion and structured matrix blocks provided in the first aspect of this application.

[0148] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0149] The technical features of the above embodiments can be combined without changing the basic principles of this application. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above embodiments merely illustrate several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the patent protection scope of this application should be determined by the appended claims.

Claims

1. A method for evaluating a gravity field based on spherical harmonic spectral domain recursion and structured matrix blocks, characterized in that, include: Obtain the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet; The latitude and longitude calculation grid is divided into multiple latitude batches along the latitudinal direction; The target covariance matrix is ​​divided into rows and columns to obtain multiple target slices; The target covariance matrix or the multiple target slices are calculated sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method. This yields the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch. The gravitational field of the target planet is evaluated based on the theoretical, actual, error, cumulative, and cumulative error values ​​of radial acceleration for all non-central terms. The steps of using the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch, include: using a first preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; using a second preset algorithm of the spectral domain recursive error propagation calculation method to calculate the target covariance matrix step-by-step in all spherical harmonic orders of each latitude batch, and obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch. The actual signal value corresponding to each spherical harmonic order in each latitude batch; the third preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; the fourth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the fifth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch; The steps of employing a spectral domain recursive error propagation calculation method to process the multiple target slices sequentially across all spherical harmonic orders in each latitude batch, and obtaining the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch, include: processing the multiple target slices sequentially across all spherical harmonic orders in each latitude batch using the first preset algorithm to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; and processing the multiple target slices sequentially across all spherical harmonic orders in each latitude batch using the second preset algorithm to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch. The actual signal value corresponding to each spherical harmonic order in each latitude batch; the third preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; the fourth preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the sixth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate and process the multiple target slices step by step in all spherical harmonic orders in each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

2. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 1, characterized in that, After calculating the target covariance matrix or the multiple target slices sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: The cumulative error values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the cumulative error value fusion result. The theoretical signal values ​​of radial acceleration of non-central terms corresponding to all spherical harmonic orders in all latitudinal batches are spliced ​​to obtain the theoretical signal value fusion result. The actual signal values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the actual signal value fusion result. The error values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the error value fusion result. The cumulative signal values ​​corresponding to all spherical harmonic orders in all latitude batches are spliced ​​together to obtain the cumulative signal value fusion result. The cumulative error value fusion result, the theoretical signal value fusion result, the actual signal value fusion result, the error value fusion result, and the cumulative signal value fusion result are displayed.

3. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 1, characterized in that, The steps for obtaining the target covariance matrix include: Obtain the model file; The target covariance matrix is ​​generated based on the compressed upper triangular covariance data of the model file.

4. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 1, characterized in that, The steps for obtaining the latitude and longitude calculation grid include: The latitude and longitude calculation grid is generated based on the preset latitude and longitude range and the preset latitude and longitude interval.

5. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 1, characterized in that, After calculating the target covariance matrix or the multiple target slices sequentially in all spherical harmonic orders of each latitude batch using the spectral domain recursive error propagation calculation method to obtain the theoretical signal value, actual signal value, error value, cumulative signal value, and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: Determine whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value of the non-central term corresponding to the target spherical harmonic order is greater than a preset value. If so, record the target spherical harmonic order as the order strength value. The target spherical harmonic order is any one of the spherical harmonic orders.

6. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 5, characterized in that, After determining whether the signal-to-noise ratio of the theoretical radial acceleration signal value and the cumulative error value corresponding to the target spherical harmonic order is greater than a preset value, and if so, recording the target spherical harmonic order as the order strength value, the gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks further includes: All order strength values ​​are concatenated to obtain the order strength value fusion result; The order strength value fusion result is then displayed.

7. The gravity field assessment method based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 1, characterized in that, The steps of dividing the target covariance matrix into row and column slices to obtain multiple target slices include: Get the memory size, video memory size, number of columns in the slice, and number of rows in the temporary slice; The target covariance matrix is ​​divided into rows and columns based on the memory size data, the video memory size data, the number of slice columns, and the number of temporary slice rows and blocks to obtain the multiple target slices.

8. A gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks, characterized in that, include: The data acquisition module is used to acquire the target covariance matrix and latitude / longitude calculation grid corresponding to the target planet; The grid partitioning module is used to divide the latitude and longitude calculation grid into multiple latitude batches along the latitude direction; The slicing module is used to perform row and column slicing on the target covariance matrix to obtain multiple target slices; The calculation module is used to calculate the target covariance matrix or the multiple target slices in each latitude batch in all spherical harmonic orders by using the spectral domain recursive error propagation calculation method, and to obtain the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of the non-central radial acceleration corresponding to each spherical harmonic order in each latitude batch; The evaluation module is used to evaluate the gravitational field of the target planet based on the theoretical signal value, actual signal value, error value, cumulative signal value and cumulative error value of radial acceleration for all non-central terms. The calculation module is also used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch using the first preset algorithm of the spectral domain recursive error propagation calculation method, so as to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch. The second preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix in all spherical harmonic orders of each latitude batch, thereby obtaining the actual signal value corresponding to each spherical harmonic order in each latitude batch. The third preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch; the fourth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the fifth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate the target covariance matrix step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch. The calculation module is also used to perform calculation processing on the multiple target slices step by step in all spherical harmonic orders of each latitude batch using the first preset algorithm, so as to obtain the theoretical signal value of the non-central term radial acceleration corresponding to each spherical harmonic order in each latitude batch; The second preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the actual signal value corresponding to each spherical harmonic order in each latitude batch; The third preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the error value corresponding to each spherical harmonic order in each latitude batch. The fourth preset algorithm is used to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative signal value corresponding to each spherical harmonic order in each latitude batch; the sixth preset algorithm of the spectral domain recursive error propagation calculation method is used to calculate and process the multiple target slices step by step in all spherical harmonic orders of each latitude batch to obtain the cumulative error value corresponding to each spherical harmonic order in each latitude batch.

9. The gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 8, characterized in that, The data acquisition module includes a graphical interaction module, a matrix construction module, and a grid acquisition module. The graphical interaction module is used to acquire the model file; the matrix construction module is used to generate the target covariance matrix based on the compressed upper triangular covariance data of the model file; and the grid acquisition module is used to acquire the latitude and longitude calculation grid.

10. The gravity field assessment system based on spherical harmonic spectral domain recursion and structured matrix blocks according to claim 9, characterized in that, The grid acquisition module is also used to generate the latitude and longitude calculation grid according to the preset latitude and longitude range and the preset latitude and longitude interval.

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