Multi-band adaptive frequency division three-dimensional gravity spectrum construction system and method

Abstract

The invention provides a multiband adaptive frequency division three-dimensional gravity spectrum construction system and method, and the system comprises an adaptive frequency division module which is used for decomposing a gravity field signal into a plurality of frequency bands through spherical harmonic expansion, dynamically adjusting the truncation order of each frequency band according to the set total number of multibands, and determining the frequency band nodes of multiband decomposition; the gravity spectrum decomposition module is used for converting the gravity field signal into a frequency domain by adopting two-dimensional Fourier transform, and performing band-pass filtering according to determined frequency band nodes to obtain gravity spectrums of different frequency bands; and the multiband stacking module is used for converting the filtering gravity in each band back to a spatial domain through two-dimensional inverse Fourier transform, and stacking the two-dimensional gravity signals of each band in sequence to obtain a multiband feature stacked three-dimensional gravity spectrum. The three-dimensional gravity spectrum construction method has the advantages that the three-dimensional gravity spectrum construction method for performing multi-band adaptive frequency division on the full-band gravity field according to the geophysical principle is established for the first time.

Description

Technical Field

[0001] This application belongs to the field of marine remote sensing mapping, and specifically relates to a three-dimensional gravity spectrum construction system and method with multi-band adaptive frequency division. Background Art

[0002] The oceanic gravity field is an important physical field of the Earth system, which can reflect the material distribution, motion, and change state determined by the interaction and dynamic processes of the Earth's various spheres. It has important application values in aspects such as seabed topography inversion, underwater matching navigation, plate tectonics and lithosphere structure research, seabed volcano research, and seabed resource exploration. Different from the two-dimensional gravity field products containing full-band signals, the gravity spectrum is a three-dimensional cube composed of multiple discrete gravity bands stacked, where each band encapsulates gravity characteristics corresponding to different topography-gravity response mechanisms. The multi-band architecture of the gravity spectrum enhances the seabed topography inversion based on neural networks due to its rich gravity characteristics, while retaining the geophysical principle of the topography-gravity interaction corresponding to discrete wavelengths.

[0003] Each band in the gravity spectrum represents the gravity signal at the corresponding spatial scale. How to perform multi-band decomposition on the full-band two-dimensional gravity field according to geophysical principles is the key and difficulty in the construction of the three-dimensional gravity spectrum. The spherical harmonic expansion of the gravity field can decompose the complex gravity field into components with different spatial frequencies, and its order reflects the spatial frequency of the gravity field. The low order corresponds to long-wave signals (such as mantle convection, plate movement), and the high order corresponds to short-wave signals (such as topography undulation, local density anomaly). However, currently, there is no three-dimensional gravity spectrum construction method for multi-band adaptive frequency division of the full-band gravity field according to geophysical principles. Summary of the Invention

[0004] The purpose of this application is to overcome the current lack of a method for multi-band adaptive decomposition of the full-band gravity field according to geophysical principles and provide an effective three-dimensional gravity spectrum construction.

[0005] To achieve the above purpose, this application proposes a three-dimensional gravity spectrum construction system with multi-band adaptive frequency division, including:

[0006] An adaptive frequency division module, which is used to decompose the gravity field signal into multiple frequency bands by using spherical harmonic expansion, dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands, and determine the frequency band nodes of multi-band decomposition;

[0007] A gravity spectrum decomposition module, which is used to convert the gravity field signal to the frequency domain by using two-dimensional Fourier transform, and perform band-pass filtering respectively according to the determined frequency band nodes to obtain gravity spectra of different frequency bands;

[0008] Multi-band stacking module, which is used to convert the filtered gravity in each frequency band back to the spatial domain through inverse two-dimensional Fourier transform, and stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking.

[0009] As an improvement of the above system, the processing process of the adaptive frequency division module includes:

[0010] Step A1: Decompose the gravity field signal into multiple frequency bands by using spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands;

[0011]

[0012] In the formula, is the truncation order of the spherical harmonic function expansion of the gravity field; is the wavelength corresponding to the spherical harmonic function expansion of the gravity field up to order; is the average radius of the earth;

[0013] Step A2: Determine the nodes for decomposing each frequency band according to the wavelengths corresponding to the multi-band decomposition of the gravity field;

[0014]

[0015] Among them, is the node of the th frequency band of the gravity field decomposition, and λ i represents the wavelength corresponding to the

[0016] As an improvement of the above system, the processing process of the gravity spectrum decomposition module includes:

[0017] Step B1: Convert the gravity field signal from the spatial domain to the frequency domain by using two-dimensional Fourier transform ;

[0018]

[0019] Among them, and are the two-dimensional coordinates of the frequency domain, and are the two-dimensional coordinates of the spatial domain; is the two-dimensional gravity field of the full band in the spatial domain; and are respectively the sizes of the gravity field in the and directions;

[0020] Step B2: Design a suitable band-pass filter according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands;

[0021] Band-pass filter Can be expressed as:

[0022]

[0023] Wherein, Represents the frequency band node And Constitute the th frequency band.

[0024] The th gravity spectrum of the frequency band Is:

[0025] .

[0026] As an improvement of the above system, the processing process of the multi-band stacking module includes:

[0027] Step C1: Convert the filtered gravity in each frequency band back to the spatial domain through two-dimensional inverse Fourier transform;

[0028]

[0029] Wherein, Is the two-dimensional gravity signal of the th band in the spatial domain; And Are the two-dimensional coordinates in the frequency domain, and their value ranges are from 0 to And from 0 to ; And Are respectively the gravity field sizes in the And directions;

[0030] Step C2: Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking:

[0031]

[0032] Wherein, Is the three-dimensional gravity spectrum with multi-band feature stacking; Is the two-dimensional gravity signal of the th band in the spatial domain; Is the number of multi-bands; Represents the stacking operation of multi-band features.

[0033] This application also provides a method for constructing a three-dimensional gravity spectrum with multi-band adaptive frequency division, which is implemented based on the above system and includes:

[0034] Step 1: Decompose the gravity field signal into multiple frequency bands using spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands;

[0035] Step 2: Determine the nodes for decomposing each frequency band according to the wavelengths corresponding to the multi-band decomposition of the gravity field;

[0036] Step 3: Convert the filtered gravity in each frequency band back to the spatial domain through two-dimensional inverse Fourier transform;

[0037] Step 4: Design a band-pass filter according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands;

[0038] Step 5: Convert the filtered gravity in each frequency band back to the spatial domain through two-dimensional inverse Fourier transform;

[0039] Step 6: Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with stacked multi-band features.

[0040] Compared with the prior art, the advantages of this application are as follows:

[0041] 1. This application introduces spherical harmonic expansion for dynamic frequency division to establish a three-dimensional gravity spectrum construction system with multi-band adaptive frequency division.

[0042] 2. The three-dimensional gravity spectrum construction method with multi-band adaptive frequency division proposed in this application adaptively decomposes the gravity field signal into multiple bands according to the set total number of multi-bands through the characteristic that the spherical harmonic order of the gravity field corresponds to different spatial frequencies, and then stacks the two-dimensional gravity signals of different bands in sequence to realize the construction of the three-dimensional gravity spectrum. Brief Description of the Drawings

[0043] Figure 1 Shown is the structure diagram of a three-dimensional gravity spectrum construction system with multi-band adaptive frequency division;

[0044] Figure 2 Shown is the flowchart of a three-dimensional gravity spectrum construction method with multi-band adaptive frequency division. Detailed Embodiments

[0045] The technical solutions of this application will be described in detail below with reference to the accompanying drawings.

[0046] The three-dimensional gravity spectrum construction system and method with multi-band adaptive frequency division proposed in this application adaptively decomposes the gravity field signal into multiple bands according to the set total number of multi-bands through the characteristic that the spherical harmonic order of the gravity field corresponds to different spatial frequencies, and then stacks the two-dimensional gravity signals of different bands in sequence to realize the construction of the three-dimensional gravity spectrum.

[0047] Example 1

[0048] AsFigure 1 As shown in Figure 1 , the present application proposes a three-dimensional gravity spectrum construction system with multi-band adaptive frequency division, including an adaptive frequency division module, a gravity spectrum decomposition module, and a multi-band stacking module.

[0049] The design of each module is as follows:

[0050] 1. Adaptive frequency division module: It is used to decompose the gravity field signal into multiple frequency bands by spherical harmonic expansion, dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands, and then determine the frequency band nodes of multi-band decomposition;

[0051] The processing process of the adaptive frequency division module includes:

[0052] Step 1: Spherical harmonic dynamic frequency division; Decompose the gravity field signal into multiple frequency bands by spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands;

[0053]

[0054] In the formula, is the truncation order of the spherical harmonic function expansion of the gravity field; is the half-wavelength corresponding to the spherical harmonic function expansion of the gravity field up to order; is the average radius of the earth (about 6371 km).

[0055]

[0056] Step 2: Determination of frequency band nodes; Determine the nodes for decomposing each frequency band according to the wavelength corresponding to the multi-band decomposition of the gravity field;

[0057]

[0058] In the formula, is the node of the th frequency band of the gravity field decomposition, and λ i represents the wavelength corresponding to the

[0059] 2. Gravity spectrum decomposition module: It is used to convert the gravity field signal to the frequency domain by two-dimensional Fourier transform, and perform band-pass filtering respectively according to the determined frequency band nodes to obtain gravity spectra of different frequency bands;

[0060] The processing process of the gravity spectrum decomposition module includes:

[0061] Step 1: Two-dimensional Fourier transform; Convert the gravity field signal from the spatial domain to the frequency domain by two-dimensional Fourier transform;

[0062]

[0063] In the formula, and are the two-dimensional coordinates in the frequency domain, and are the two-dimensional coordinates in the spatial domain, is the full-band two-dimensional gravity field in the spatial domain; and are respectively in and the gravity field sizes in the directions represents the two-dimensional Fourier transform.

[0064] Step 2: Band-pass filtering by frequency points; Design a suitable band-pass filter according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands;

[0065] The band-pass filter can be expressed as

[0066]

[0067] In the formula, represents the frequency band node and constitute the th frequency band.

[0068] The th gravity spectrum of the frequency band is

[0069]

[0070] 3. Multi-band stacking module: Used to convert the filtered gravity in each frequency band back to the spatial domain through the two-dimensional inverse Fourier transform, and then stack the two-dimensional gravity signals of each band in turn to obtain a three-dimensional gravity spectrum with multi-band feature stacking;

[0071] The processing process of the multi-band stacking module includes:

[0072] Step 1: Two-dimensional inverse Fourier transform; Convert the filtered gravity in each frequency band back to the spatial domain through the two-dimensional inverse Fourier transform;

[0073]

[0074] In the formula, is the two-dimensional gravity signal of the th band in the spatial domain; represents the two-dimensional inverse Fourier transform; and are the two-dimensional coordinates in the frequency domain, and their value ranges are from 0 to and from 0 to .

[0075] Step 2: Multi-band feature stacking; Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking.

[0076]

[0077] Wherein, is the three-dimensional gravity spectrum with multi-band feature stacking; is the two-dimensional gravity signal of the th band in the spatial domain; is the number of multi-bands; represents the stacking operation of multi-band features.

[0078] Embodiment 2

[0079] As Figure 2 shown, the present application also proposes a method for constructing a three-dimensional gravity spectrum with multi-band adaptive frequency division, which is implemented based on the above system, and includes:

[0080] Step 1) Spherical harmonic dynamic frequency division; Decompose the gravity field signal into multiple frequency bands by spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands;

[0081] Step 2) Frequency band node determination; Determine the nodes for decomposing each frequency band according to the wavelengths corresponding to the multi-band decomposition of the gravity field;

[0082] Step 3) Inverse two-dimensional Fourier transform; Convert the filtered gravity in each frequency band back to the spatial domain through the inverse two-dimensional Fourier transform;

[0083] Step 4) Band-pass filtering according to frequency points; Design a suitable band-pass filter according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands;

[0084] Step 5) Inverse two-dimensional Fourier transform; Convert the filtered gravity in each frequency band back to the spatial domain through the inverse two-dimensional Fourier transform;

[0085] Step 6) Multi-band feature stacking; Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking.

[0086] The present application can also provide a computer device, including: at least one processor, a memory, at least one network interface, and a user interface. Each component in the device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0087] Among them, the user interface may include a display, a keyboard, or a pointing device. For example, a mouse, a trackball, a touchpad, or a touch screen, etc.

[0088] It can be understood that the memory in the disclosed embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM). The memories described herein are intended to include but not be limited to these and any other suitable types of memories.

[0089] In some embodiments, the memory stores the following elements, executable modules, or data structures, or subsets or supersets thereof: an operating system and application programs.

[0090] Among them, the operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., and is used to implement various basic services and process hardware-based tasks. The application programs include various application programs, such as a media player and a browser, etc., and are used to implement various application services. The program for implementing the method of the disclosed embodiments of the present application can be included in the application programs.

[0091] In the above embodiments, by calling the programs or instructions stored in the memory, specifically, the programs or instructions stored in the application programs, the processor is configured to:

[0092] Execute the steps of the above method.

[0093] The above method can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with the ability to process signals. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor or the instructions in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed above. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Combining the steps of the above-disclosed method can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0094] It can be understood that these embodiments described in the present application can be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described in the present application, or a combination thereof.

[0095] For software implementation, the techniques of the present application can be implemented by executing the functional modules of the present application (such as procedures, functions, etc.). The software code can be stored in the memory and executed by the processor. The memory can be implemented inside or outside the processor.

[0096] The present application may also provide a non-volatile storage medium for storing a computer program. When the computer program is executed by a processor, each step in the above method embodiments can be implemented.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the embodiments, those of ordinary skill in the art should understand that any modification or equivalent replacement of the technical solutions of the present application does not depart from the spirit and scope of the technical solutions of the present application, and they should all be covered within the scope of the claims of the present application.

Claims

1. A three-dimensional gravity spectrum construction system with multi-band adaptive frequency division, characterized in that, Including: An adaptive frequency division module, which is used to decompose the gravity field signal into multiple frequency bands by using spherical harmonic expansion, dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands, and determine the frequency band nodes of multi-band decomposition; A gravity spectrum decomposition module, which is used to convert the gravity field signal to the frequency domain by using two-dimensional Fourier transform, and perform band-pass filtering respectively according to the determined frequency band nodes to obtain gravity spectra of different frequency bands; And A multi-band stacking module, which is used to convert the filtered gravity in each frequency band back to the spatial domain through inverse two-dimensional Fourier transform, and stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking.

2. The three-dimensional gravity spectrum construction system with multi-band adaptive frequency division according to claim 1, characterized in that, The processing process of the adaptive frequency division module includes: Step A1: Decompose the gravity field signal into multiple frequency bands by using spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands; ； In the formula, is the truncation order of the spherical harmonic expansion of the gravity field; is the half-wavelength corresponding to the spherical harmonic expansion of the gravity field up to order; is the average radius of the Earth; Step A2: Determine the nodes for decomposing each frequency band according to the wavelengths corresponding to the multi-band decomposition of the gravity field; ； Among them, is the node of the th frequency band of the gravitational field decomposition, and λ i represents the wavelength corresponding to the ith frequency band of the gravitational field decomposition.

3. The three-dimensional gravity spectrum construction system with multi-band adaptive frequency division according to claim 1, characterized in that, The processing process of the gravity spectrum decomposition module includes: Step B1: Convert the gravity field signal from the spatial domain to the frequency domain using two-dimensional Fourier transform ; ； Among them, and are the two-dimensional coordinates in the frequency domain, and are the two-dimensional coordinates in the spatial domain; is the full-band two-dimensional gravity field in the spatial domain; and are respectively the gravity field sizes in the directions of and ; Step B2: Design appropriate band-pass filters according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands; Band-pass filter Can be expressed as: ； Among them, represents a frequency band node and constitute the th frequency band; The gravity spectrum of the first frequency band is as follows: 。 4. The three-dimensional gravity spectrum construction system with multi-band adaptive frequency division according to claim 1, characterized in that The processing process of the multi-band stacking module includes: Step C1: Convert the filtered gravity in each frequency band back to the spatial domain through inverse two-dimensional Fourier transform; ； Among them, is the two-dimensional gravity signal of the th band in the spatial domain; and are the two-dimensional coordinates in the frequency domain, and their value ranges are from 0 to and from 0 to ; and are the gravity field sizes in the and directions respectively; Step C2: Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking: ； Among them, is the three-dimensional gravity spectrum stacked with multi-band features; is the two-dimensional gravity signal of the th band in the spatial domain; is the number of multi-bands; represents the stacking operation of multi-band features.

5. A method for constructing a three-dimensional gravity spectrum with multi-band adaptive frequency division, which is implemented based on the system according to any one of claims 1-4, includes: Step 1: Decompose the gravity field signal into multiple frequency bands by using spherical harmonic expansion, and dynamically adjust the truncation order of each frequency band according to the set total number of multi-bands; Step 2: Determine the nodes for decomposing each frequency band according to the wavelengths corresponding to the multi-band decomposition of the gravity field; Step 3: Convert the filtered gravity in each frequency band back to the spatial domain through inverse two-dimensional Fourier transform; Step 4: Design band-pass filters according to the determined frequency band nodes, and perform band-pass filtering respectively to obtain gravity spectra of different frequency bands; Step 5: Convert the filtered gravity in each frequency band back to the spatial domain through inverse two-dimensional Fourier transform; Step 6: Stack the two-dimensional gravity signals of each band in sequence to obtain a three-dimensional gravity spectrum with multi-band feature stacking.

Images