Magnetic measurement data processing method and system based on multi-machine collaborative anti-Japanese variable magnetic interference

Abstract

The present invention provides a method and system for processing magnetic measurement data based on multi-aircraft collaborative anti-solar-variation magnetic interference, including: respectively establishing traditional magnetic compensation models for platform maneuvering magnetic interference and geomagnetic gradient magnetic interference for each detection aircraft; during the high-altitude calibration flight of each detection aircraft, solving the compensation coefficients for the traditional magnetic interference compensation models of each detection aircraft; during actual detection, acquiring the data of each detection aircraft, and performing compensation for the platform maneuvering magnetic interference and geomagnetic gradient magnetic interference of the aircraft based on the data of each detection aircraft, the compensation coefficients of each detection aircraft, and the traditional magnetic interference compensation models of each detection aircraft to obtain the residual magnetic field including solar-variation magnetic interference for each detection aircraft; setting a window length, and synchronously windowing the residual magnetic field data of each detection aircraft; using the ICEEMDAN algorithm to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components; solving the correlation coefficients between all components of the synchronous windows of different detection aircraft, and screening out and eliminating one by one the relevant components that exceed the correlation threshold in the synchronous windows of different detection aircraft according to the set correlation threshold; reconstructing the data of the remaining components of each window of each detection aircraft to complete the processing of magnetic measurement data. Applying the technical solution of the present invention can solve the technical problem of the influence caused by solar-variation magnetic interference in the actual detection area in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical fields of aviation magnetic compensation and aviation magnetic detection, and particularly relates to a magnetic measurement data processing method and system based on multi-aircraft cooperation to resist diurnal magnetic interference. Background Art

[0002] Aviation magnetic detection is an important method for geophysical exploration. Compared with traditional detection means, it has the advantages of high efficiency, convenience, flexibility and rapidity. This method mounts a magnetometer for measuring the magnetic field on an aircraft, makes the aircraft continuously scan in a specified detection area, and then uses the method of magnetic anomaly detection to detect and locate magnetic targets within the scanning trajectory range. However, the aircraft body carrying the magnetometer contains a large amount of ferromagnetic substances, which will distort the spatial detection magnetic field. Moreover, the geomagnetic field is not a constant value that remains unchanged. It gradually changes in the horizontal and vertical directions in the detection area, and the geomagnetic gradient magnetic interference generated by it will also contaminate the detection data. For the maneuvering magnetic interference generated by the aircraft platform itself, the traditional compensation model proposed by Tolles and Lawson (hereinafter referred to as the T-L model) can be used for modeling and suppression; for the geomagnetic gradient magnetic interference, the position information of the detection platform, such as longitude, latitude and altitude, can be used to construct a first-order linear compensation model to describe and suppress it. In addition, in actual detection, the magnetometer will also be affected by the diurnal magnetic interference of the geomagnetic field. The diurnal magnetic interference is mainly composed of quiet variations and disturbance variations. The quiet variation field is caused by the stable current system that always exists in the ionosphere. It changes significantly during the day, and its intensity ranges from 30 nT to 200 nT; the disturbance variation field is composed of magnetic storms, substorms and earth pulsations, etc. Its duration is uncertain, and the intensity variation range is from 1 nT to 2000 nT. Among them, the quiet variation field is the main component of the diurnal field. Its variation trend basically depends on latitude and local time, and is closely related to the solar activity cycle. It is obvious during the day, with small intensity and slow change at night; its seasonal variation characteristics are significant, and the variation amplitude in summer is much larger than that in winter. In actual detection, due to the difficult-to-master variation law of the diurnal magnetic interference, its intensity is much greater than the target intensity, and the frequency bands overlap each other, seriously affecting the detection results. Summary of the Invention

[0003] The present invention provides a magnetic measurement data processing method and system based on multi-aircraft cooperation to resist diurnal magnetic interference, which can solve the technical problem of the influence brought by the diurnal magnetic interference in the actual detection area in the prior art.

[0004] According to one aspect of the present invention, a method for processing magnetic measurement data based on multi-aircraft collaborative anti-solar-variation magnetic interference is provided. The method for processing magnetic measurement data based on multi-aircraft collaborative anti-solar-variation magnetic interference includes: for each detection aircraft, respectively establishing traditional magnetic compensation models for platform maneuver magnetic interference and geomagnetic gradient magnetic interference; during the high-altitude calibration flight of each detection aircraft, solving the compensation coefficients for the traditional magnetic interference compensation models of each detection aircraft; during actual detection, acquiring the data of each detection aircraft, and performing compensation for platform maneuver magnetic interference and geomagnetic gradient magnetic interference according to the data of each detection aircraft, the compensation coefficients of each detection aircraft, and the traditional magnetic interference compensation models of each detection aircraft to obtain the residual magnetic field including solar-variation magnetic interference for each detection aircraft; setting a window length, and synchronously windowing the residual magnetic field data of each detection aircraft; using the ICEEMDAN algorithm to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components; solving the correlation coefficients of all components in the synchronous windows of different detection aircraft with each other, and according to the set correlation threshold, screening out and eliminating one by one the correlated components exceeding the correlation threshold in the synchronous windows of different detection aircraft; and reconstructing the data of the remaining components of each window of each detection aircraft to complete the processing of magnetic measurement data.

[0005] Further, setting a window length and synchronously windowing the residual magnetic field data of each detection aircraft specifically includes: for any one detection aircraft, setting the window length to L; for the residual magnetic field data B ri = [b ri1 , b ri2 , …, b riN of the detection aircraft, performing synchronous windowing as [b ri1 , b ri2 , …, b riL , [b riL+1 , b riL+2 , …, b ri2L … [b riN-L , b riN-L+1 , …, b riN .

[0006] Further, using the ICEEMDAN algorithm to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components specifically includes: for any one window of any one detection aircraft, taking the data in any one window as the original signal x, and adding white noise E 1 [w i (i = 1, 2, …, N) to the original signal x to obtain the original signal x i = x + β 0 E 1 [w i (i = 1, 2, …, N), where w iis the i-th white noise added, β 0 is the signal-to-noise ratio, N is the number of white noises added, E k (·) represents the k-th order mode component generated by EMD decomposition; According to calculate to obtain the first component IMF of the ICEEMDAN algorithm 1 , where d 1 is the first component, r 1 is the first group of residuals, M(·) is the function to generate the local mean; According to calculate to obtain the second component IMF of the ICEEMDAN algorithm 2 , where d 2 is the second component, r 2 is the second group of residuals, β 1 is the signal-to-noise ratio, E 2 is the 2nd order mode component generated by EMD decomposition;; Repeat the above process to obtain the third component... the k-th component IMF k , where the k-th component IMF k is where d k is the k-th component, r k is the k-th group of residuals, r k-1 is the (k - 1)-th group of residuals, β k-1 is the (k - 1)-th signal-to-noise ratio, E k is the k-th order mode component generated by EMD decomposition;.

[0007] Further, the correlation coefficients are calculated for all components of the synchronization windows of different detection aircraft. According to the set correlation threshold, the correlated components in the synchronization windows of different detection aircraft that exceed the set correlation threshold are screened out and removed one by one. Specifically, for any one detection aircraft, first select the first component in the first window of any one detection aircraft, and calculate the correlation coefficients between the first component in the first window of any one detection aircraft and each component in the first window synchronized with other detection aircraft in turn. If the correlation coefficient between the first component in the first window of any one detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds the set correlation threshold, then both the first component in the first window and any component in the first window synchronized with any other detection aircraft are removed; then select the second component in the first window of any one detection aircraft, and calculate the correlation coefficients between the second component in the first window of any one detection aircraft and each component in the first window synchronized with other detection aircraft in turn. If the correlation coefficient between the second component in the first window of any one detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds the set correlation threshold, then both the second component in the first window and any component in the first window synchronized with any other detection aircraft are removed; repeat the above process until the correlation coefficients are calculated for all components of the synchronization windows of any one detection aircraft and other different detection aircraft and the removal of the correlated components is completed.

[0008] Further, the traditional magnetic compensation model for platform maneuver magnetic interference and geomagnetic gradient magnetic interference is where a i is the magnetic compensation coefficient to be solved, and μ i is the model function related to magnetic compensation.

[0009] Further, the model function related to magnetic compensation is where T g is the geomagnetic field, T X , T Y , T Z are the three components of vector magnetic resistance, W is the earth's latitude, J is the earth's longitude, and G is the altitude where the platform is located at the current moment.

[0010] Further, in the high-altitude calibration flight of each detection aircraft, the specific process of solving the compensation coefficients for the traditional magnetic interference compensation model of each detection aircraft includes: for any detection aircraft, the detection aircraft performs calibration flights through three maneuvering actions of roll, pitch, and yaw. The scalar magnetometer, vector magnetoresistance, and on-board GPS are used to collect the total magnetic field, three components of vector magnetoresistance, longitude, latitude, and altitude information respectively; the total magnetic field, three components of vector magnetoresistance, longitude, latitude, and altitude information are substituted into the traditional magnetic compensation model, and Butterworth filters are used at both ends of the traditional magnetic compensation model to filter the target frequency band; the magnetic compensation coefficient a is solved by the method of linear regression. i 。

[0011] Further, the specific process of the detection aircraft performing calibration flights through three maneuvering actions of roll, pitch, and yaw includes: the detection aircraft moves from west to north and sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft moves from north to east and sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft moves from east to south and sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft moves from south to west and sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions.

[0012] Further, based on the data of each detection aircraft, the compensation coefficient of each detection aircraft, and the traditional magnetic interference compensation model of each detection aircraft, compensating for the maneuvering magnetic interference and geomagnetic gradient magnetic interference of the aircraft platform to obtain the residual magnetic field of each detection aircraft including diurnal variation magnetic interference specifically includes: for any detection aircraft, substituting the data of the detection aircraft and the compensation coefficient of the detection aircraft into the traditional magnetic interference compensation model of the detection aircraft to calculate and obtain the total magnetic field B of the magnetic interference generated by ferromagnetic substances in the moving platform of the detection aircraft and the magnetic interference generated by the geomagnetic gradient. TLG The magnetic interference value B is measured using a detection magnetometer. t According to B r = B t - B TLG The residual magnetic field of the detection aircraft is calculated.

[0013] According to another aspect of the present invention, a magnetic measurement data processing system based on multi-aircraft collaboration against diurnal variation magnetic interference is provided. The magnetic measurement data processing system based on multi-aircraft collaboration against diurnal variation magnetic interference uses the magnetic measurement data processing method based on multi-aircraft collaboration against diurnal variation magnetic interference as described above to process magnetic measurement data.

[0014] Applying the technical solution of the present invention, a method for processing magnetic measurement data based on multi-aircraft collaborative anti-variable magnetic interference is provided. In this method, during multi-aircraft collaborative detection, data of each aircraft is synchronized and windowed simultaneously using a window with a fixed length. Before windowing, first, a traditional compensation model and compensation coefficients are used to suppress platform magnetic interference and geomagnetic gradient magnetic interference in each data. For the remaining magnetic field data within the window of each aircraft, the ICEEMDAN algorithm is used to decompose them respectively to obtain several components. Next, the correlation coefficients of all components in the synchronous windows of different aircraft are solved with each other, and a correlation threshold is set according to experience to screen out and eliminate the relevant components in the synchronous windows of different aircraft, so as to achieve real-time and high-precision compensation for the three types of magnetic interference. Therefore, compared with the prior art, the method for processing magnetic measurement data based on multi-aircraft collaborative anti-variable magnetic interference provided by the present invention combines with the traditional magnetic compensation algorithm to accurately extract the variable magnetic interference during actual detection, and effectively suppresses the platform magnetic interference, geomagnetic gradient magnetic interference and variable magnetic interference, effectively improving the data quality of the detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings included are used to provide a further understanding of the embodiments of the present invention, which form a part of the specification, are used to illustrate the embodiments of the present invention, and together with the text description are used to explain the principles of the present invention. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It shows a flowchart of calculating magnetic compensation coefficients during calibration provided according to a specific embodiment of the present invention;

[0017] Figure 2 It shows a schematic diagram of the maneuvering actions of the calibration type platform movement provided according to a specific embodiment of the present invention;

[0018] Figure 3 It shows a flowchart of the real-time airborne magnetic compensation process provided according to a specific embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Note that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way restricts the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0020] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0021] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and values set forth in these embodiments do not limit the scope of the present invention. At the same time, it should be understood that, for the sake of convenience of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships. Technologies, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and devices should be regarded as part of the authorized specification. In all the examples shown and discussed herein, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values. It should be noted that like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0022] As Figures 1 to 3As shown in the figure, according to a specific embodiment of the present invention, a magnetic measurement data processing method based on multi-aircraft cooperation against diurnal variation magnetic interference is provided. The magnetic measurement data processing method based on multi-aircraft cooperation against diurnal variation magnetic interference includes: for each detection aircraft, respectively establishing a traditional magnetic compensation model for platform maneuver magnetic interference and geomagnetic gradient magnetic interference; during the high-altitude calibration flight of each detection aircraft, solving the compensation coefficients for the traditional magnetic interference compensation models of each detection aircraft; during actual detection, acquiring the data of each detection aircraft, and performing platform maneuver magnetic interference and geomagnetic gradient magnetic interference compensation according to the data of each detection aircraft, the compensation coefficients of each detection aircraft, and the traditional magnetic interference compensation models of each detection aircraft to obtain the residual magnetic field including diurnal variation magnetic interference of each detection aircraft; setting a window length, and synchronously windowing the residual magnetic field data of each detection aircraft; using the ICEEMDAN (Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) algorithm to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components; solving the correlation coefficients of all components of the synchronous windows of different detection aircraft with each other, and according to the set correlation threshold, screening out and eliminating one by one the correlated components in the synchronous windows of different detection aircraft that exceed the correlation threshold; reconstructing the data of the remaining components of each window of each detection aircraft to complete the magnetic measurement data processing.

[0023] Applying this configuration method, a magnetic measurement data processing method based on multi-aircraft cooperation against diurnal variation magnetic interference is provided. In this method, during multi-aircraft cooperative detection, the data of each aircraft is synchronously windowed simultaneously using a window with a fixed length. Before windowing, first, the platform magnetic interference and geomagnetic gradient magnetic interference in each data are suppressed using a traditional compensation model and compensation coefficients. The ICEEMDAN algorithm is used to decompose the residual magnetic field data within the window of each aircraft respectively to obtain several components. Next, the correlation coefficients of all components of the synchronous windows of different aircraft are solved with each other, and according to the empirically set correlation threshold, the correlated components in the synchronous windows of different aircraft are screened out and eliminated, so as to achieve real-time high-precision compensation for the three types of magnetic interference. Therefore, compared with the prior art, the magnetic measurement data processing method based on multi-aircraft cooperation against diurnal variation magnetic interference provided by the present invention combines with the traditional magnetic compensation algorithm, accurately extracts the diurnal variation magnetic interference in actual detection, effectively suppresses the platform magnetic interference, geomagnetic gradient magnetic interference and diurnal variation magnetic interference of the detection platform, and effectively improves the data quality of the detection results.

[0024] Specifically, in the present invention, in order to realize the magnetic measurement data processing based on multi-aircraft cooperation against diurnal variation magnetic interference, first, for each detection aircraft, a traditional magnetic compensation model for platform maneuver magnetic interference and geomagnetic gradient magnetic interference needs to be established respectively. In the present invention, the traditional magnetic compensation models for platform maneuver magnetic interference and geomagnetic gradient magnetic interference are where a i is the magnetic compensation coefficient to be solved, and μi It is a model function related to magnetic compensation.

[0025] The model function related to magnetic compensation is Among them, T g is the geomagnetic field, T X , T Y , T Z are the three components of vector magnetoresistance, W is the earth's latitude, J is the earth's longitude, and G is the altitude where the platform is located at the current moment.

[0026] After obtaining the traditional magnetic compensation models of each detection aircraft, the compensation coefficients of the traditional magnetic interference compensation models of each detection aircraft can be solved during the high-altitude calibration flight of each detection aircraft. In the present invention, during the high-altitude calibration flight of each detection aircraft, solving the compensation coefficients of the traditional magnetic interference compensation models of each detection aircraft specifically includes: for any one detection aircraft, the detection aircraft performs calibration flights by performing three maneuvering actions of roll, pitch, and yaw, and uses a scalar magnetometer, vector magnetoresistance, and on-board GPS to collect the total magnetic field, three components of vector magnetoresistance, longitude, latitude, and altitude information respectively; substituting the total magnetic field, three components of vector magnetoresistance, longitude, latitude, and altitude information into the traditional magnetic compensation model, and filtering the two ends of the traditional magnetic compensation model with a Butterworth filter for the target frequency band; solving the magnetic compensation coefficient a i .

[0027] Among them, the detection aircraft performing calibration flights by performing three maneuvering actions of roll, pitch, and yaw specifically includes: the detection aircraft from west to north, sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft from north to east, sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft from east to south, sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions; the detection aircraft from south to west, sequentially performs multiple groups of roll maneuvering actions, multiple groups of pitch maneuvering actions, and multiple groups of yaw maneuvering actions. In this configuration method, by performing multiple groups of maneuvering actions in different directions, the equation multicollinearity can be effectively avoided, and at the same time, all directions and attitudes of the aircraft during flight are traversed.

[0028] As a specific embodiment of the present invention, such as Figure 2As shown, the detection platform maneuvers in a sequence of three sets of roll maneuvers, three sets of pitch maneuvers, and three sets of yaw maneuvers from west to north, with the period of each set of maneuvers being 4 to 12 seconds; from north to east, it performs three sets of roll maneuvers, three sets of pitch maneuvers, and three sets of yaw maneuvers in sequence, with the period of each set of maneuvers being 4 to 12 seconds; from east to south, it performs three sets of roll maneuvers, three sets of pitch maneuvers, and three sets of yaw maneuvers in sequence, with the period of each set of maneuvers being 4 to 12 seconds; from south to west, it performs three sets of roll maneuvers, three sets of pitch maneuvers, and three sets of yaw maneuvers in sequence, with the period of each set of maneuvers being 4 to 12 seconds.

[0029] Further, after obtaining the magnetic compensation coefficient a i in actual detection, data of each detection aircraft is acquired, and based on the data of each detection aircraft, the compensation coefficient of each detection aircraft, and the traditional magnetic interference compensation model of each detection aircraft, magnetic interference compensation for aircraft platform maneuvers and geomagnetic gradient magnetic interference is performed to obtain the residual magnetic field including daily-varying magnetic interference for each detection aircraft.

[0030] In the present invention, performing magnetic interference compensation for aircraft platform maneuvers and geomagnetic gradient magnetic interference based on the data of each detection aircraft, the compensation coefficient of each detection aircraft, and the traditional magnetic interference compensation model of each detection aircraft to obtain the residual magnetic field including daily-varying magnetic interference for each detection aircraft specifically includes: for any detection aircraft, substituting the data of the detection aircraft and the compensation coefficient of the detection aircraft into the traditional magnetic interference compensation model of the detection aircraft to calculate and obtain the total magnetic field B generated by ferromagnetic substances in the moving platform of the detection aircraft and the magnetic interference generated by the geomagnetic gradient TLG ; measuring and obtaining the magnetic interference value B using a detection magnetometer t ; according to B r = B t - B TLG calculating and obtaining the residual magnetic field of the detection aircraft.

[0031] Further, after obtaining the residual magnetic field including daily-varying magnetic interference for each detection aircraft, the window length can be set to synchronously window the residual magnetic field data of each detection aircraft. In the present invention, setting the window length and synchronously windowing the residual magnetic field data of each detection aircraft specifically includes: for any detection aircraft, setting the window length to L; synchronously windowing the residual magnetic field data B ri = [b ri1 , b ri2 , …, b riN of the detection aircraft into [b ri1 , b ri2 , …, b riL , [b riL+1 , b riL+2 , …, bri2L …[b riN-L ,b riN-L+1 ,…,b riN 。

[0032] After synchronously windowing the residual magnetic field data of each detection aircraft, the ICEEMDAN algorithm can be used to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components. In the present invention, using the ICEEMDAN algorithm to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components specifically includes: for any window of any detection aircraft, taking the data in any window as the original signal x, adding white noise E 1 [w i (i = 1, 2, …, N) to obtain the original signal x with white noise i = x + β 0 E 1 [w i (i = 1, 2, …, N), where w i is the i-th white noise added, β 0 is the signal-to-noise ratio, N is the number of white noises added, and E 1 is the first-order modal component generated by EMD decomposition; according to calculate to obtain the first component IMF 1 of the ICEEMDAN algorithm, where d 1 is the first component, r 1 is the first group of residuals, and M(·) is the function for generating the local mean; according to calculate to obtain the second component IMF 2 of the ICEEMDAN algorithm, where d 2 is the second component, r 2 is the second group of residuals, β 1 is the signal-to-noise ratio, and E 2 is the second-order modal component generated by EMD decomposition; repeat the above process to sequentially obtain the third component … the k-th component IMF k , where the k-th component IMF k is where d k is the k-th component, r k is the k-th group of residuals, r k-1 is the (k - 1)-th group of residuals, β k-1 is the signal-to-noise ratio, and E k is the k-th order modal component generated by EMD decomposition.

[0033] Furthermore, after using the ICEEMDAN algorithm to decompose the remaining magnetic field data of each window of each detection aircraft to obtain multiple components, the correlation coefficients of all components in the synchronous windows of different detection aircraft can be solved with each other. According to the set correlation threshold, the correlated components in the synchronous windows of different detection aircraft that exceed the correlation threshold are screened out and removed one by one.

[0034] As a specific embodiment of the present invention, solving the correlation coefficients of all components in the synchronous windows of different detection aircraft with each other, and screening out the correlated components in the synchronous windows of different detection aircraft that exceed the set correlation threshold and removing them one by one specifically includes: for any one detection aircraft, first select the first component in the first window of any one detection aircraft, and solve the correlation coefficients of the first component in the first window of any one detection aircraft with each component in the first window synchronized with other detection aircraft in turn. If the correlation coefficient between the first component in the first window of any one detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds the set correlation threshold, then the first component in the first window and any component in the first window synchronized with any other detection aircraft are both removed; then select the second component in the first window of any one detection aircraft, and solve the correlation coefficients of the second component in the first window of any one detection aircraft with each component in the first window synchronized with other detection aircraft in turn. If the correlation coefficient between the second component in the first window of any one detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds the set correlation threshold, then the second component in the first window and any component in the first window synchronized with any other detection aircraft are both removed; repeat the above process until the correlation coefficients of all components in the synchronous windows of any one detection aircraft and other different detection aircraft are solved with each other and the removal of the correlated components is completed.

[0035] After screening out and removing one by one the correlated components in the synchronous windows of different detection aircraft that exceed the correlation threshold, the remaining components of each window of each detection aircraft can be data - reconstructed to complete the magnetic measurement data processing.

[0036] According to another aspect of the present invention, a magnetic measurement data processing system based on multi - aircraft collaborative anti - variable magnetic interference is provided. This magnetic measurement data processing system based on multi - aircraft collaborative anti - variable magnetic interference uses the magnetic measurement data processing method based on multi - aircraft collaborative anti - variable magnetic interference as described above to process magnetic measurement data.

[0037] By applying this configuration method, a magnetic measurement data processing system based on multi-aircraft collaborative anti-solar-variation magnetic interference is provided. In the multi-aircraft collaborative detection, the data of each aircraft is synchronized and windowed simultaneously using a window with a fixed length. Before windowing, the platform magnetic interference and geomagnetic gradient magnetic interference in each data are suppressed using traditional compensation models and compensation coefficients. For the remaining magnetic field data in the window of each aircraft, the ICEEMDAN algorithm is used to decompose them respectively to obtain several components. Next, the correlation coefficients of all components in the synchronized windows of different aircraft are calculated with each other, and a correlation threshold is set according to experience to screen out and remove the relevant components in the synchronized windows of different aircraft, so as to achieve real-time high-precision compensation for the three kinds of magnetic interferences. Therefore, compared with the prior art, the magnetic measurement data processing system based on multi-aircraft collaborative anti-solar-variation magnetic interference provided by the present invention combines with the traditional magnetic compensation algorithm to accurately extract the solar-variation magnetic interference in actual detection, and effectively suppresses the platform magnetic interference, geomagnetic gradient magnetic interference and solar-variation magnetic interference, effectively improving the data quality of the detection results.

[0038] For a further understanding of the present invention, the following is combined with Figures 1 to 3 to elaborate in detail on the magnetic measurement data processing system based on multi-aircraft collaborative anti-solar-variation magnetic interference provided by the present invention.

[0039] As Figures 1 to 3 shown, according to a specific embodiment of the present invention, a magnetic measurement data processing method based on multi-aircraft collaborative anti-solar-variation magnetic interference is provided. This method is used to solve the influence caused by solar-variation magnetic interference in the actual detection area, improve the compensation accuracy of the airborne magnetic compensation algorithm, and further enhance the detection performance of airborne magnetic detection. The magnetic measurement data processing method based on multi-aircraft collaborative anti-solar-variation magnetic interference provided by the present invention specifically includes the following steps.

[0040] 1) Establish a traditional magnetic compensation model for platform maneuvering magnetic interference and geomagnetic gradient magnetic interference, expressed as: where a i is the magnetic compensation coefficient to be solved, and μ i is the model function related to magnetic compensation.

[0041] The model function related to magnetic compensation is where T g is the geomagnetic field, which can be obtained by low-pass filtering the measured total magnetic field, T X , T Y , T Z are the three components of vector magnetoresistance, W is the earth's latitude, J is the earth's longitude, and G is the altitude where the platform is located at the current moment.

[0042] (cosα X )',(cosα Y)', (cosα Z )' respectively represent cosα X , cosα Y , cosα Z 's differential. The angles between the geomagnetic field and the three axes of the moving platform coordinate system are denoted as α X 、α Y 、α Z , and their cosine values are expressed as:

[0043]

[0044] 2) The platform conducts calibration flights to obtain the magnetic compensation coefficient a i ; Figure 1 The following shows the process of calculating the magnetic compensation coefficient during the calibration flight of the present invention, and the specific operations are as follows:

[0045] 2A. The moving platform performs three maneuvering actions to obtain all the required data information. The maneuvering actions are roll, pitch, and yaw, with peak-to-peak angles of 10°, 5°, and 5° respectively. Each maneuvering action has 3 groups, and the period is 4 - 12 seconds, as Figure 2 shown;

[0046] 2B. Use the obtained data to construct a new model and filter the target frequency band at both ends using a Butterworth filter;

[0047] 2C. Solve the magnetic compensation coefficient a i ;

[0048] 3) During actual detection, use B TLG , the compensation coefficient a i and the data collected by the scalar magnetometer and vector magnetoresistance to solve the residual magnetic field, which can be expressed as:

[0049] B r = B t - B TLG

[0050] where B t is the magnetic interference value measured by the detection magnetometer.

[0051] 4) Set the window length to L, and synchronously window the residual magnetic field data B ri = [b ri1 , b ri2 , …, b riN (the decomposition in the frequency domain, where i = 1, 2, … is the number of aircraft, and N is the number of actual detection data of this aircraft) into [b ri1 , b ri2 , …, b riL , [b riL+1 , briL+2 ,…,b ri2L ]…[b riN-L ,b riN-L+1 ,…,b riN ].

[0052] 5) Use ICEEMDAN to decompose the window data of each aircraft. The process is as follows:

[0053] 5A. For any window of any detected aircraft, take the data in any window as the original signal x and add white noise E to the original signal x 1 [w i ](i=1,2,…,N) to get the original signal x with white noise i =x+β 0 E 1 [w i ](i=1,2,…,N), where w i is the i-th white noise added, β 0 is the signal-to-noise ratio, N is the amount of white noise added, E 1 is the first-order modal component generated by EMD decomposition;

[0054] 5B.According to Calculate the first component IMF of the ICEEMDAN algorithm 1 , where d 1 is the first component, r 1 is the first set of residuals, M(·) is the function that generates the local mean;

[0055] 5C.According to Calculate the second component IMF of the ICEEMDAN algorithm 2 , where d 2 is the second component, r 2 is the second set of residuals, β 1 is the signal-to-noise ratio, E 2 is the second-order modal component generated by EMD decomposition;

[0056] 5D. Repeat the above process to obtain the third component...kth component IMF k , where the kth component IMF k for Among them, d k is the kth component, r k is the residual of the kth group, r k-1 is the k-1th group of residuals, β k-1 is the signal-to-noise ratio, E k is the k-order modal component generated by EMD decomposition.

[0057] 6) At this time, set the correlation threshold P. Set the components of each window of each aircraft as a unit, and then calculate the correlation coefficients one by one for all the components in each unit with all the components in the synchronous window units of different detection aircraft. For the components with a value ≥ P, eliminate them.

[0058] In this embodiment, taking the first window of the first detection aircraft as an example, assuming there are a total of three detection aircraft. First, select the first component in the first window of the first detection aircraft, and sequentially calculate the correlation coefficients between the first component in the first window of the first detection aircraft and each component in the first window synchronized with the second detection aircraft and each component in the first window synchronized with the third detection aircraft. If the correlation coefficient between the first component in the first window of the first detection aircraft and the third component in the first window synchronized with the third detection aircraft exceeds the set correlation threshold P, then eliminate both the first component in the first window and the third component in the first window synchronized with the third detection aircraft;

[0059] Then select the second component in the first window of the first detection aircraft, and sequentially calculate the correlation coefficients between the second component in the first window of the first detection aircraft and each component in the first window synchronized with the second detection aircraft and each component in the first window synchronized with the third detection aircraft. If the correlation coefficient between the second component in the first window of the first detection aircraft and the first component in the first window synchronized with the second detection aircraft exceeds the set correlation threshold P, then eliminate both the second component in the first window and the first component in the first window synchronized with the second detection aircraft;

[0060] Repeat the above process until the correlation coefficients are calculated for all the components in the synchronous windows of the first detection aircraft with the second and third detection aircraft and the elimination of the relevant components is completed.

[0061] Through the above steps, effective suppression of the daily variable magnetic interference of the data collected by each aircraft platform in actual detection can be achieved.

[0062] 7) Reconstruct the data of the remaining components of each window of each detection aircraft to complete the magnetic measurement data processing.

[0063] In summary, the present invention provides a method for processing magnetic measurement data based on multi-aircraft collaborative anti-solar-variation magnetic interference. In this method, during multi-aircraft collaborative detection, data of each aircraft is windowed synchronously and simultaneously using a window with a fixed length. Before windowing, first, a traditional compensation model and compensation coefficients are used to suppress the platform magnetic interference and geomagnetic gradient magnetic interference in each data. For the remaining magnetic field data within the window of each aircraft, the ICEEMDAN algorithm is used to decompose them respectively to obtain several components. Next, the correlation coefficients are calculated for all components in the synchronous windows of different aircraft, and a correlation threshold is set according to experience to screen out and remove the correlated components in the synchronous windows of different aircraft, thereby achieving real-time high-precision compensation for the three types of magnetic interference. Therefore, compared with the prior art, the method for processing magnetic measurement data based on multi-aircraft collaborative anti-solar-variation magnetic interference provided by the present invention combines with the traditional magnetic compensation algorithm to accurately extract the solar-variation magnetic interference in actual detection, and effectively suppresses the platform magnetic interference, geomagnetic gradient magnetic interference, and solar-variation magnetic interference, effectively improving the data quality of the detection results.

[0064] For ease of description, spatial relative terms such as "above", "over", "on the upper surface of", "above-mentioned", etc. may be used herein to describe the spatial positional relationship between one device or feature and other devices or features as shown in the figures. It should be understood that the spatial relative terms are intended to encompass different orientations in use or operation in addition to the orientation depicted in the figures. For example, if the device in the figures is inverted, the device described as "above" or "over" other devices or structures will then be oriented "below" or "beneath" the other devices or structures. Thus, the exemplary term "above" can include both the orientation of "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and corresponding interpretations should be made for the spatial relative descriptions used herein.

[0065] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. Without further statement, the above terms have no special meaning, and thus should not be construed as limiting the protection scope of the present invention.

[0066] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A magnetic measurement data processing method based on multi-machine collaboration to resist solar variable magnetic interference, characterized in that: The magnetic measurement data processing method based on multi-machine collaboration to resist solar variable magnetic interference includes: For each detection aircraft, the traditional magnetic compensation model of platform maneuvering magnetic interference and geomagnetic gradient magnetic interference is established respectively; During the high-altitude calibration flight of each detection aircraft, the compensation coefficient of the traditional magnetic interference compensation model of each detection aircraft is solved; In actual detection, the data of each detection aircraft is obtained, and the magnetic interference caused by aircraft platform maneuvering and geomagnetic gradient is compensated according to the data of each detection aircraft, the compensation coefficient of each detection aircraft and the traditional magnetic interference compensation model of each detection aircraft to obtain the residual magnetic field including the daily variable magnetic interference of each detection aircraft; Set the window length and synchronously draw a window for the residual magnetic field data of each detection aircraft; The ICEEMDAN algorithm is used to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components; Solve the correlation coefficients of all components in the synchronization windows of different detection aircraft, and according to the set correlation threshold, filter out the correlation components in the synchronization windows of different detection aircraft that exceed the correlation threshold and remove them one by one; The remaining components of each window of each detection aircraft are reconstructed to complete the magnetic survey data processing.

2. The magnetic measurement data processing method based on multi-machine collaboration to resist solar variable magnetic interference according to claim 1 is characterized in that: Setting the window length and synchronously windowing the residual magnetic field data of each detection aircraft specifically includes: For any detected aircraft, set the window length to L; The residual magnetic field data B of the detection aircraft ri =[b ri1 ,b ri2 ,…,b riN ] to synchronize the window for [b ri1 ,b ri2 ,…,b riL ]、[b riL+1 ,b riL+2 ,…,b ri2L ]…[b riN-L ,b riN-L+1 ,…,b riN ].

3. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 1 is characterized in that: The ICEEMDAN algorithm is used to decompose the residual magnetic field data of each window of each detection aircraft to obtain multiple components, including: For any window of any detected aircraft, the data in any window is taken as the original signal x, and white noise E1[w i ], i = 1, 2, ..., N to obtain the original signal x with white noise i =x+β0E1[w i ],i=1,2,…,N, where w i is the i-th white noise added, β0 is the signal-to-noise ratio, N is the number of white noises added, and E1 is the first-order modal component generated by EMD decomposition; according to Calculate and obtain the first component IMF1 of the ICEEMDAN algorithm, where d1 is the first component, r1 is the first set of residuals, and M(·) is the function that generates the local mean; according to Calculate and obtain the second component IMF2 of the ICEEMDAN algorithm, where d2 is the second component, r2 is the second set of residuals, β1 is the signal-to-noise ratio, and E2 is the second-order modal component generated by EMD decomposition; Repeat the above process to obtain the third component...kth component IMF k , where the kth component IMF k for Among them, d k is the kth component, r k is the residual of the kth group, r k-1 is the k-1th group of residuals, β k-1 is the signal-to-noise ratio, E k is the k-order modal component generated by EMD decomposition.

4. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 3 is characterized in that: Solving the correlation coefficients of all components in the synchronization windows of different detection aircraft, and screening out the correlation components in the synchronization windows of different detection aircraft that exceed the set correlation threshold according to the set correlation threshold, and removing them one by one specifically includes: For any detection aircraft, firstly, the first component in the first window of the any detection aircraft is selected, and the correlation coefficients of the first component in the first window of the any detection aircraft and the components in the first windows synchronized with other detection aircraft are solved in sequence; if the correlation coefficient between the first component in the first window of the any detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds a set correlation threshold, then the first component in the first window and any component in the first window synchronized with any other detection aircraft are eliminated; Then, the second component in the first window of any one of the detection aircraft is selected, and the correlation coefficients of the second component in the first window of any one of the detection aircraft and the components in the first window synchronized with other detection aircraft are solved in sequence; if the correlation coefficient between the second component in the first window of any one of the detection aircraft and any component in the first window synchronized with any other detection aircraft exceeds a set correlation threshold, the second component in the first window and any component in the first window synchronized with any other detection aircraft are eliminated; The above process is repeated until the correlation coefficients of all components of the synchronization windows of any detection aircraft and other different detection aircraft are solved and the elimination of the related components is completed.

5. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to any one of claims 1 to 4, characterized in that: The traditional magnetic compensation model for the platform maneuvering magnetic interference and geomagnetic gradient magnetic interference is: Among them, a i is the magnetic compensation coefficient to be solved, μ i is the model function related to magnetic compensation.

6. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 5 is characterized in that: The model function related to the magnetic compensation is: Among them, T g is the Earth's magnetic field, T X , T Y , T Z are the three components of vector magnetic resistance, W is the earth's latitude, J is the earth's longitude, and G is the height of the platform at the current moment.

7. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 6 is characterized in that: During the high-altitude calibration flight of each detection aircraft, the compensation coefficient of the traditional magnetic interference compensation model of each detection aircraft is solved, including: For any detection aircraft, the detection aircraft performs three maneuvers of rolling, pitching and yaw for calibration flight, and uses scalar magnetometer, vector magnetic resistance and airborne GPS to collect total magnetic field, three components of vector magnetic resistance, longitude, latitude and altitude information respectively; Substituting the total magnetic field, three components of vector magnetic resistance, longitude, latitude and altitude information into the traditional magnetic compensation model, and filtering the target frequency band using a Butterworth filter at both ends of the traditional magnetic compensation model; Solving the magnetic compensation coefficient a by linear regression method i .

8. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 7 is characterized in that: The detection aircraft performs three maneuvers of rolling, pitching and yaw for calibration flight, which specifically includes: The detection aircraft performed multiple sets of rolling maneuvers, multiple sets of pitching maneuvers, and multiple sets of yaw maneuvers from west to north; The detection aircraft moves from north to east, performing multiple sets of rolling maneuvers, multiple sets of pitching maneuvers, and multiple sets of yaw maneuvers in sequence; The detection aircraft moves from east to south, performing multiple sets of rolling maneuvers, multiple sets of pitching maneuvers, and multiple sets of yaw maneuvers in sequence; The detection aircraft performed multiple sets of rolling maneuvers, multiple sets of pitch maneuvers and multiple sets of yaw maneuvers from south to west.

9. The magnetic measurement data processing method based on multi-machine collaboration to resist solar-induced magnetic interference according to claim 8 is characterized in that: According to the data of each detection aircraft, the compensation coefficient of each detection aircraft and the traditional magnetic interference compensation model of each detection aircraft, the aircraft platform maneuvering magnetic interference and geomagnetic gradient magnetic interference compensation are performed to obtain the residual magnetic field including daily variable magnetic interference of each detection aircraft, which specifically includes: For any of the detection aircraft, the data of the detection aircraft and the compensation coefficient of the detection aircraft are substituted into the conventional magnetic interference compensation model of the detection aircraft to calculate and obtain the total field B of the magnetic interference generated by the ferromagnetic material in the motion platform of the detection aircraft and the magnetic interference generated by the geomagnetic gradient. TLG ; Use the detection magnetometer to measure and obtain the magnetic interference value B t ; According to B r =B t -B TLG The residual magnetic field of the detection aircraft is obtained by calculation.

10. A magnetic measurement data processing system based on multi-machine collaboration to resist the interference of solar-induced magnetic field, characterized in that: The magnetic data processing system based on multi-machine collaboration to resist solar-variable magnetic interference uses the magnetic data processing method based on multi-machine collaboration to resist solar-variable magnetic interference as described in any one of claims 1 to 9 to process magnetic data.

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