Evolutionary aeromagnetic compensation method and device considering geomagnetic change and medium

Abstract

The invention discloses an evolutionary aeromagnetic compensation method and device considering geomagnetic variation and a medium, and the method comprises the steps: S01, employing a T-L model to describe the magnetic interference of an aircraft, introducing an estimable geomagnetic field parameter into the model, constructing a magnetic interference linear model, and obtaining a geomagnetic field model with the estimable parameter; s02, establishing a comprehensive parameter model which considers the magnetic interference and the geomagnetic field at the same time; and S03, acquiring a real-time measurement signal, inputting the real-time measurement signal into the comprehensive parameter model to obtain a magnetic interference estimation result, and calculating an interference parameter to be estimated by using a previous magnetic interference estimation result, the stored updated measurement signal and a current magnetic interference estimation result to realize synchronous estimation of the magnetic interference and the geomagnetic parameter. According to the method, evolutionary aeromagnetic compensation can be carried out by considering geomagnetic changes, synchronous estimation of variable interference and geomagnetic parameters is accurately realized, magnetic interference is effectively reduced, and the flexibility and applicability of the evolutionary compensation method are improved.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic measurement technology, and in particular to an evolutionary aeromagnetic compensation method, equipment and medium taking geomagnetic changes into consideration. Background Art

[0002] Electromagnetic measurement is of great significance in geological exploration, mineral exploration, magnetic object detection, geomagnetic navigation and other fields. Aeromagnetic detection is to install a high-precision magnetometer on the mobile platform of the aircraft and use magnetic scalar information to achieve the measurement task. Although the aircraft platform itself has the advantage of mobility, the platform's interfering magnetic field, such as permanent magnetic field, induced magnetic field, eddy current magnetic field, and interference from the onboard electronic system will always cause contamination of the measured magnetic signal. Therefore, aeromagnetic compensation is used as a standard process before the aeromagnetic measurement mission to eliminate the interference of the platform. Traditional aeromagnetic compensation is a calibration flight at an altitude of 3km-5km, which includes maneuvers such as pitch, yaw and roll. The geomagnetic field at this altitude is considered to be moderately variable. The TL (Tolles-Lawson) model is a model for magnetic interference compensation in aeromagnetic exploration. The aeromagnetic interference parameters can be estimated by using the magnetic data obtained in the calibration flight for the TL model. For example, the interference parameter estimation problem can be equivalent to a linear regression problem and solved by the least squares method.

[0003] In order to improve the compensation performance, the existing technology usually adopts methods such as ridge regression, truncated singular value decomposition, partial least squares, neural network, deep autoencoder, convolutional neural network, etc. to reduce the multicollinearity of aeromagnetic data, or add interference to the aeromagnetic compensation model, such as adding interference from electronic equipment such as beacon lights, rudders, switching power supplies, etc. However, in practical applications, there are still two "changes" that limit the performance of aeromagnetic compensation: changes in magnetic interference and changes in the ambient magnetic field. In the traditional TL model-based compensation, magnetic interference is regarded as static. Due to different aircraft operating conditions and load equipment, interference may actually change, resulting in low actual compensation accuracy. The evolutionary compensation method based on the Woodbury equation can estimate magnetic interference parameters online and solve the problem of magnetic interference changes, but this type of method requires the assumption that the geomagnetic background is uniform and constant, and cannot solve the problem of ambient magnetic field changes. Moreover, this assumption is only applicable to traditional FOM flights, because the magnetic gradient fluctuates gently above 3 km, but it is not applicable in conventional mission flights at altitudes below 1 km, so the applicable scenarios are limited. Summary of the invention

[0004] The technical problem to be solved by the present invention is: in response to the technical problems existing in the prior art, the present invention provides an evolutionary aeromagnetic compensation method, equipment and medium that take into account geomagnetic changes, which has a simple implementation method, good compensation effect and a wide range of applications. The method can perform evolutionary aeromagnetic compensation taking into account geomagnetic changes and accurately realize the synchronous estimation of variable interference and geomagnetic parameters.

[0005] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0006] An evolutionary aeromagnetic compensation method considering geomagnetic changes, comprising the following steps:

[0007] Step S01. Use the TL model to describe the aircraft magnetic interference, use the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated to build a magnetic interference linear model, and introduce estimable geomagnetic field parameters into the TL model to describe the changing environmental magnetic field, and build a geomagnetic field model based on the geomagnetic field strength, the residual magnetic field generated by the vertical gradient, and the geomagnetic field strength on the horizontal flight plane;

[0008] Step S02. Establishing a comprehensive parameter model that takes into account both magnetic interference and geomagnetic field according to the magnetic interference linear model and geomagnetic field model;

[0009] Step S03. Acquire a real-time measurement signal and input it into the comprehensive parameter model to obtain a magnetic interference estimation result, wherein the measurement signal includes magnetic interference observation data and geomagnetic field position, and stores an updated portion of the measurement signal each time the measurement signal is updated. When the current magnetic interference estimation result is estimated, the previous magnetic interference estimation result, the stored updated measurement signal and the current magnetic interference estimation result are used to calculate the interference parameter to be estimated, so as to evolve the estimation parameters of the comprehensive parameter model and realize the synchronous estimation of magnetic interference and geomagnetic parameters.

[0010] Furthermore, the TL model used in step S01 is:

[0011]

[0012] Among them, B I represents magnetic interference, p, a, e are the interference coefficients to be estimated defined by the TL model, p is the fixed magnetic field interference, a is the induced magnetic field interference, e is the eddy current magnetic field interference, u is the direction cosine vector of the measured magnetic field vector, u = [cosα, cosβ, cosγ] T , α, β, γ are the roll, pitch and yaw of the aircraft maneuvering angle, u' is the time derivative of u, i, j refer to the x, y, z three-axis coordinates, B0 represents the magnetic flux density of the environmental geomagnetic field, H0 represents the magnetic field strength of the Earth's magnetic field. The relationship between H0 and B0 satisfies B0 = μH0, where μ is the magnetic permeability;

[0013] Measured magnetic signal B m By magnetic interference B I and the ambient geomagnetic field B0, namely:

[0014] B m =B0+BI

[0015] The magnetic interference linear model is constructed using the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated:

[0016] B I =Cθ

[0017] Among them, C and θ are the observation matrix and the interference parameter matrix to be estimated, respectively, which are expressed as:

[0018]

[0019] Where n is the sampling point during the measurement.

[0020] Furthermore, in step S01, constructing the geomagnetic field model includes:

[0021] Describe B0 as the geomagnetic field strength and vertical gradient B in the horizontal flight plane z The residual magnetic field generated is used to construct a first-order vertical gradient model:

[0022] B0(x,y,z)=B h (x,y)+B z (x,y,z0)Δz

[0023]

[0024] Δz=z-z0

[0025] Where Δz is the height drop during turbulence, z0 is the starting altitude of the flight, and B h is the geomagnetic field intensity on the horizontal flight plane, which is expressed by Taylor polynomial fitting method. The horizontal gradient second-order model is expressed as:

[0026]

[0027] Where N is the order of the local geomagnetic model, A ij are the horizontal geomagnetic parameters to be estimated, x0 is the longitude of the starting point, and y0 is the latitude of the starting point.

[0028] Furthermore, the comprehensive parameter model established in step S02 that takes into account both magnetic interference and the geomagnetic field is:

[0029]

[0030] Where r is the sensor measurement error, R is the standard deviation matrix, C is the magnetic interference observation matrix, θ is the corresponding interference parameter, L is the geomagnetic field position matrix, A is the geomagnetic parameter to be estimated, and the geomagnetic field B0 is described as: B0 = LA.

[0031] Further, step S03 includes:

[0032] Get historical estimation results

[0033]

[0034] Wherein, subscript 1 represents the last estimation result, λ is the regularization parameter, and R is the standard deviation matrix of sensor measurement error;

[0035] definition:

[0036]

[0037] Among them, I represents the identity matrix;

[0038] In evolutionary compensation, only the updated partial data Φ2 is stored, where the subscript 2 represents the estimated result after the current evolution;

[0039] Evolutionary estimates of magnetic disturbance parameters and geomagnetic parameters:

[0040]

[0041] in, is the inverse matrix of M2.

[0042] Furthermore, when the measurement signal is updated, the following signal is obtained:

[0043]

[0044] Among them, C2 and L2 are the observation matrices composed of updated data, B2 is the updated measurement signal, n1 is the sampling point of the last measurement, and n2 is the sampling point of the update;

[0045] According to the updated measurement signal, the data to be stored and updated is determined as follows:

[0046]

[0047] Furthermore, the inverse matrix of M2 is calculated using the Woodbury equation for the stored update data:

[0048] An evolutionary aeromagnetic compensation device considering geomagnetic changes, comprising:

[0049] The geomagnetic field model construction module is used to describe the aircraft magnetic interference using the TL model, construct a magnetic interference linear model using the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated, and introduce estimable geomagnetic field parameters into the TL model to describe the changing environmental magnetic field, and construct a geomagnetic field model based on the geomagnetic field strength, the residual magnetic field generated by the vertical gradient, and the geomagnetic field strength on the horizontal flight plane;

[0050] A comprehensive parameter model building module, used to build a comprehensive parameter model that takes both magnetic interference and geomagnetic field into consideration according to the magnetic interference linear model and geomagnetic field model;

[0051] A synchronous estimation module is used to obtain real-time measurement signals and input them into the comprehensive parameter model to obtain magnetic interference estimation results. The measurement signals include magnetic interference observation data and geomagnetic field positions. Each time the measurement signals are updated, the updated part of the measurement signals is stored. When the current magnetic interference estimation result is estimated, the interference parameters to be estimated are calculated using the previous magnetic interference estimation result, the stored updated measurement signal and the current magnetic interference estimation result, so as to evolve the estimation parameters of the comprehensive parameter model and realize synchronous estimation of magnetic interference and geomagnetic parameters.

[0052] An electronic device comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to perform the above method.

[0053] A computer-readable storage medium storing a computer program, wherein the computer program implements the above method when executed by a processor.

[0054] Compared with the prior art, the advantages of the present invention are:

[0055] 1. The present invention first establishes a geomagnetic field model with estimable parameters, and then expands a comprehensive parameter model composed of geomagnetic parameters and magnetic interference parameters. On the basis of the comprehensive parameter model, the evolutionary aeromagnetic compensation method is improved to achieve synchronous estimation of variable interference and geomagnetic parameters, so that in actual scenarios where interference and geomagnetic field dynamically change, magnetic interference can be effectively reduced, while increasing the flexibility and applicability of the evolutionary compensation method.

[0056] 2. The present invention does not need to store all the data, but only needs to store the updated partial dimensional data, and then calculate the evolved M2 inverse matrix according to the Woodbury equation, and finally obtain the expression of the estimated parameters. Since it is no longer necessary to store the complete test data, the parameters can be estimated in real time to evolve the parameters through the updated data during the flight mission, and the evolutionary estimation of magnetic interference parameters and geomagnetic parameters can be realized at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of the implementation process of the evolutionary aeromagnetic compensation method taking into account geomagnetic changes in this embodiment.

[0058] Figure 2 It is a schematic diagram of original data and compensation results under a constant geomagnetic field using the present invention and the traditional compensation method in a specific application embodiment.

[0059] Figure 3 It is a schematic diagram of original data and compensation results under geomagnetic gradient using the present invention and the traditional compensation method in a specific application embodiment.

[0060] Figure 4 It is a schematic diagram of the original data and compensation results under the geomagnetic gradient using the present invention and the traditional compensation method in a specific application embodiment, and a schematic diagram of the impact of geomagnetic gradient changes under different interference change rates. DETAILED DESCRIPTION

[0061] The present invention is further described below in conjunction with the accompanying drawings and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0062] The evolutionary aeromagnetic compensation method is to update the magnetic interference parameters by evolution using conventional mission flight data. At present, the evolutionary aeromagnetic compensation is operated under the assumption of geomagnetic invariance, but conventional mission flights usually occur at low altitudes where the geomagnetic field is changeable and complex. The present invention first establishes a geomagnetic field model with estimable parameters, and then expands a comprehensive parameter model composed of geomagnetic parameters and magnetic interference parameters. On the basis of the comprehensive parameter model, the evolutionary aeromagnetic compensation method is improved to achieve synchronous estimation of variable interference and geomagnetic parameters, so that in actual scenarios where interference and geomagnetic fields change dynamically, magnetic interference can be effectively reduced, while increasing the flexibility and applicability of the evolutionary compensation method.

[0063] like Figure 1 As shown, the steps of the evolutionary aeromagnetic compensation method considering geomagnetic changes in this embodiment include:

[0064] Step S01. Use the TL model to describe the aircraft magnetic interference, use the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated to build a magnetic interference linear model, and introduce estimable geomagnetic field parameters into the TL model to describe the changing environmental magnetic field. The geomagnetic field model is built according to the geomagnetic field strength, the residual magnetic field generated by the vertical gradient, and the geomagnetic field strength on the horizontal flight plane.

[0065] The TL model can be used to describe the aircraft magnetic interference, including the superposition of permanent magnetic field, induced magnetic field and eddy current magnetic field. The TL model describes the above three interferences as the product of the coefficient matrix to be solved and the observation matrix, thus converting the aeromagnetic compensation problem into a linear estimation problem of the coefficients to be solved.

[0066] Since the magnetic interference is much smaller than the Earth's magnetic field, the projection approximation is used to simplify the magnetic interference to B I The linear model in :

[0067]

[0068] Where p, a, and e are the interference coefficients to be estimated defined by the TL model, p is the fixed magnetic field interference, a is the induced magnetic field interference, e is the eddy current magnetic field interference, u is the direction cosine vector of the measured magnetic field vector, u' is the time derivative of u, i and j refer to the x, y, and z coordinates, and B0 represents the ambient geomagnetic field.

[0069] Under the assumption of geomagnetic invariance, the parameters of the induced magnetic field and eddy current magnetic field can be rewritten as: H0 represents the magnetic field strength of the Earth's magnetic field.

[0070] Therefore, it can be expressed as the classic TL model form:

[0071]

[0072] Where u is the direction cosine vector, which can be expressed as:

[0073] u=[cosα,cosβ,cosγ] T (3)

[0074] Among them, α, β, and γ are the aircraft maneuvering angles, corresponding to roll, pitch, and yaw, respectively.

[0075] The measured magnetic signal is composed of magnetic interference B I And the ambient geomagnetic field B0:

[0076] B m =B0+B I (4)

[0077] In order to estimate the interference parameters, it is necessary to extract the magnetic interference from the measurement signal and construct a linear model of magnetic interference as follows:

[0078] B I =Cθ (5)

[0079] Where C and θ are the observation matrix and the interference parameter matrix to be estimated respectively:

[0080]

[0081] Where n is the sampling point during the measurement.

[0082] The above magnetic interference linear model is the interference magnetic field model. After the interference parameters are estimated according to the model, the interference can be compensated.

[0083] When the geomagnetic field changes, the interference parameters also change, so the assumption of geomagnetic invariance does not hold. At the same time, under the assumption that the geomagnetic field is constant, it is simple to extract magnetic interference from the measurement signal; but under the changing environmental geomagnetic field, it may not work properly, so the model needs to introduce estimable geomagnetic field parameters to describe the changing environmental magnetic field.

[0084] Since the magnetic field measurement value includes the magnetic interference vector and the geomagnetic field vector, the traditional method is to directly extract the interference magnetic field from the measured magnetic field through a filter, which will result in the loss of some information. In this embodiment, the interference magnetic field model and the geomagnetic field model are respectively established to jointly estimate the parameters. The use of the constructed geomagnetic field model can reduce the loss of information, so that the interference magnetic field model can be estimated more accurately. Considering that the aircraft usually flies at a specific altitude and turbulence occasionally occurs, this embodiment describes B0 as the geomagnetic field intensity and vertical gradient B on the horizontal flight plane. z The residual magnetic field generated is used to construct a first-order vertical gradient model:

[0085]

[0086] Where B0 is the geomagnetic field strength and vertical gradient B on the horizontal flight plane z The residual magnetic field generated, Δz is the height drop during turbulence, z0 is the starting altitude of the flight, B h is the geomagnetic field strength on the horizontal flight plane, which can be expressed by Taylor polynomial fitting method. Set the horizontal geomagnetic parameter A to be estimated ij , the second-order model of horizontal gradient is expressed as:

[0087]

[0088] Where N is the order of the local geomagnetic model, A ij are the horizontal geomagnetic parameters to be estimated, x0 is the longitude of the starting point, and y0 is the latitude of the starting point.

[0089] Step S02: establishing a comprehensive parameter model that takes both magnetic interference and geomagnetic field into consideration based on the magnetic interference linear model and the geomagnetic field model with estimable parameters.

[0090] This embodiment constructs a comprehensive parameter model consisting of a magnetic interference model and an environmental geomagnetic model on the basis of the traditional TL model. This model can directly describe the measured magnetic signal and solve the problem that the geomagnetic field gradient is quite complex in low-altitude flight and the simple preprocessing of the traditional model is unreasonable.

[0091] Specifically, the geomagnetic field B0 can be described as the product of the geomagnetic parameter A to be estimated and the observation matrix L composed of the position information:

[0092] B0=LA (8)

[0093] A is the geomagnetic parameter to be estimated set in the previous step, that is A ij , L is the observation matrix composed of position information, that is, the geomagnetic field position matrix:

[0094]

[0095] The comprehensive parameter model that considers both magnetic interference and geomagnetic field is established as follows:

[0096]

[0097] In the formula, r is the sensor measurement error, the standard deviation matrix is ​​R, C is the magnetic interference observation matrix, and θ is the corresponding interference parameter. C is the traditional interference parameter, L is the introduced estimable geomagnetic field parameter, and θ is the interference parameter to be estimated based on p, a, and e, that is,

[0098] Step S03. Acquire real-time measurement signals and input them into the comprehensive parameter model to obtain magnetic interference estimation results. The measurement signals include magnetic interference observation data and geomagnetic field positions. Each time the measurement signals are updated, the updated part of the measurement signals is stored. When the current magnetic interference estimation results are estimated, the interference parameters to be estimated are calculated using the previous magnetic interference estimation results, the stored updated measurement signals and the current magnetic interference estimation results, so as to evolve the estimation parameters of the comprehensive parameter model and realize the synchronous estimation of magnetic interference and geomagnetic parameters.

[0099] Assume that the estimated results obtained by the previous model are for:

[0100]

[0101] Wherein, subscript 1 represents the last estimation result, λ is the regularization parameter, and R is the standard deviation matrix of sensor measurement error;

[0102] The solution can be obtained by ridge regression, where λ is the regularization parameter, which can be determined by L curve optimization. R is the standard deviation matrix of the sensor measurement error, which can be described as a diagonal matrix with the elements being the standard deviation σr .

[0103] Further definition:

[0104]

[0105] Where I represents the identity matrix.

[0106] When updating the measurement signal:

[0107]

[0108] Among them, C2 and L2 are observation matrices composed of updated data, B2 is the updated measurement signal, n1 is the sampling point at the last measurement, and n2 is the sampling point at the update.

[0109] The traditional compensation method directly uses all the data in the formula for parameter estimation. This operation requires storing data in the dimensions of (n1+n2)×25 and (n1+n2)×1. In the evolutionary compensation process, this embodiment does not need to store all the data, but only stores the updated part of the data in the evolutionary compensation:

[0110]

[0111] Among them, subscript 2 indicates the evolved parameters;

[0112] Therefore, only data of (n1+n2)×25 and (n1+n2)×1 dimensions need to be stored, so that the inverse matrix of M2 can be calculated using the Woodbury equation on the stored update data:

[0113]

[0114] The evolutionary estimation of magnetic disturbance parameters and geomagnetic parameters can be expressed as:

[0115]

[0116] in, is the inverse matrix of M2.

[0117] This embodiment improves the traditional evolutionary compensation method. It is not necessary to store all the data, but only to store the updated partial dimensional data, and then calculate the evolved M2 inverse matrix according to the Woodbury equation to finally obtain the expression of the estimated parameters. Since it is no longer necessary to store the complete test data, the parameters can be estimated in real time through the updated data to evolve the parameters during the flight mission, and the evolutionary estimation of magnetic interference parameters and geomagnetic parameters can be achieved simultaneously.

[0118] In the above-mentioned evolutionary aeromagnetic compensation method considering geomagnetic changes, the present invention utilizes previous estimation results and updated measurement signals to evolve the estimation parameters in the comprehensive parameter model expression, which can reduce the negative impact of changes in the geomagnetic field on the compensation results and improve the accuracy and performance of the compensation.

[0119] In order to verify the performance of the present invention, the method of the present invention was used to conduct experiments in a specific application embodiment. The standard process of aeromagnetic compensation includes two flights: a calibration FOM flight and a conventional mission flight. The data obtained during the FOM calibration flight is used to estimate parameters, which are applied to conventional mission flights to eliminate magnetic interference. Since the present invention aims to estimate parameters evolutionarily during conventional mission flights, the conventional mission flight is divided into two parts: the data of the first part is used to evolve the parameters, and the remaining data is used to test the compensation performance of the present invention, and the initial values ​​of the parameters are obtained from the calibration FOM flight. The maneuvers during the FOM calibration flight meet the aeromagnetic standards. The interference parameters and the ambient geomagnetic field are designed to be variable, and the interference parameters are set to change by 5% and 10%, and the effects of different interferences are analyzed. The geomagnetic field is set to change by 0-1.2 times based on the original value, and the effects of different geomagnetic gradients are analyzed.

[0120] The compensation residual (GeoEvo) of the method of the present invention, the traditional ridge regression method without considering evolutionary compensation (denoted as TraRR) and the traditional evolutionary compensation method without considering geomagnetism (TraEvo) were compared respectively, and the compensation performance was evaluated by the standard deviation (STD) and improvement rate (IR) after compensation. The evaluation criteria can be expressed as:

[0121]

[0122] Where x is the compensated magnetic data, x is the average value, and n is the number of sampling points. The subscript un represents the uncompensated data, and the subscript com represents the compensated data. Comparing the compensation results under different conditions, including different interference parameters and different variance amplitudes of geomagnetic gradients, the simulation results are shown in Figures 2 to 4 As shown in the figure, we can see that:

[0123] (1) The influence of disturbance changes under a constant geomagnetic field is as follows Figure 2 As shown, Figure 2(a) corresponds to the original data (RawData), (b) corresponds to the compensated magnetic interference results (Compensated MagneticInterferences) obtained by each method, and (c) corresponds to the interference change influence results (Influence of Interference Change) obtained by various methods at different influence rates. It can be seen from the figure that under constant geomagnetic field and unchanged interference, the method GeoEvo of the present invention, the traditional methods TraRR and TraEvo can reduce STD from 0.7722nT to 0.0703nT, 0.0806nT and 0.1001nT respectively. That is, under unchanged conditions, all compensation methods can work well. However, with the increase of interference, the performance of traditional TraRR has declined, while the evolutionary compensation method of the method GeoEvo of the present invention and the traditional TraEvo have shown higher adaptability to changing interference.

[0124] (2) Compensation performance under geomagnetic gradient Figure 3 As shown, among which Figure 3 (a) corresponds to the original data (RawData), (b) corresponds to the compensated magnetic interference results (Compensated MagneticInterferences) obtained by each method, and (c) corresponds to the interference change influence results (Influence of Interference Change) obtained by various methods at different influence rates. It can be seen from the figure that under the geomagnetic gradient and constant interference, the GeoEvo of the present invention can reduce the STD from 0.8456nT to 0.0938nT, which is 56% and 52% higher than the traditional TraRR and TraEvo respectively. Compared with the results under constant geomagnetism in Figure a3), neither the traditional TraRR nor TraEvo has the ability to change geomagnetic field. Taking into account the interference change, at a change rate of 5%, the GeoEvo of the present invention is 55% and 51% higher than the traditional TraRR and TraEvo respectively. When the interference change rate is 10%, it is increased by 51% and 46% respectively.

[0125] (3) Analysis of the impact of geomagnetic gradient changes on compensation performance. Figure 4 As shown, Figure 4(a) shows the result when the interference changes by 0%, (b) shows the result when the interference changes by 5%, and (c) shows the result when the interference changes by 10%. It can be seen from the figure that when the geomagnetic gradient increases from 0 times to 1.2 times, the STD of the traditional TraRR and TraEvo increases by 2.4 times and 2.2 times, respectively, while the GeoEvo of the present invention has higher robustness, and its STD only increases by 4.8%. Considering the case where the interference change rate is 5% and 10%, at the interference change rate of 5%, with the increase of the geomagnetic gradient, the traditional TraRR and TraEvo also show performance degradation, and the STD of TraRR increases by 2.2 times, and that of TraEvo increases by 2.0 times. At the interference change rate of 10%, TraRR increases by 1.6 times, and TraEvo increases by 1.5 times. On the contrary, the GeoEvo of the present invention still shows a higher robustness, which increases by 16% and 35% at the interference change rates of 5% and 10%, respectively.

[0126] It can be concluded from the above simulation results that the present invention has better adaptability and robustness, and the variance of interference parameters and geomagnetic gradient is larger.

[0127] This embodiment further provides an electronic device, including a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program to perform the above method.

[0128] It is understandable that the above method of this embodiment can be executed by a single device, such as a computer or server, etc., and can also be applied to a distributed scenario and completed by multiple devices in cooperation with each other. In the case of a distributed scenario, one of the multiple devices can only execute one or more steps in the above method of this embodiment, and multiple devices interact to complete the above method. The processor can be implemented in the form of a general-purpose CPU, a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, etc., for executing related programs to implement the above method of this embodiment. The memory can be implemented in the form of a read-only memory ROM, a random access memory RAM, a static storage device, and a dynamic storage device. The memory can store an operating system and other applications. When the above method of this embodiment is implemented by software or firmware, the relevant program code is stored in the memory and called and executed by the processor.

[0129] This embodiment further provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0130] Those skilled in the art will appreciate that the above-mentioned embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0131] The above is only a preferred embodiment of the present invention, and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment, it is not intended to limit the present invention. Therefore, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the scope of protection of the technical solution of the present invention.

Claims

1. An evolutionary aeromagnetic compensation method considering geomagnetic changes, characterized in that the steps include: Step S01. Use the TL model to describe the aircraft magnetic interference, use the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated to build a magnetic interference linear model, and introduce estimable geomagnetic field parameters into the TL model to describe the changing environmental magnetic field, and build a geomagnetic field model based on the geomagnetic field strength, the residual magnetic field generated by the vertical gradient, and the geomagnetic field strength on the horizontal flight plane; Step S02. Establishing a comprehensive parameter model that takes into account both magnetic interference and geomagnetic field according to the magnetic interference linear model and geomagnetic field model; Step S03. Acquire a real-time measurement signal and input it into the comprehensive parameter model to obtain a magnetic interference estimation result, wherein the measurement signal includes magnetic interference observation data and geomagnetic field position, and stores an updated portion of the measurement signal each time the measurement signal is updated. When the current magnetic interference estimation result is estimated, the previous magnetic interference estimation result, the stored updated measurement signal and the current magnetic interference estimation result are used to calculate the interference parameter to be estimated, so as to evolve the estimation parameters of the comprehensive parameter model and realize the synchronous estimation of magnetic interference and geomagnetic parameters.

2. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to claim 1, characterized in that: In step S01, the TL model used is: Among them, B I represents magnetic interference, p, a, e are the interference coefficients to be estimated defined by the TL model, p is the fixed magnetic field interference, a is the induced magnetic field interference, e is the eddy current magnetic field interference, u is the direction cosine vector of the measured magnetic field vector, u = [cosα, cosb, cosγ] T , α, b, γ are roll, pitch and yaw of the aircraft maneuvering angle, u' is the time derivative of u, i, j refer to the x, y, z three-axis coordinates, B0 represents the magnetic flux density of the environmental geomagnetic field, H0 represents the magnetic field strength of the Earth's magnetic field. The relationship between H0 and B0 satisfies B0 = μH0, where μ is the magnetic permeability; Measured magnetic signal B m By magnetic interference B I and the ambient geomagnetic field B0, namely: B m =B0+B I The magnetic interference linear model is constructed using the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated: B I =Cθ Among them, C and θ are the observation matrix and the interference parameter matrix to be estimated, respectively, which are expressed as: Where n is the sampling point during the measurement.

3. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to claim 1, characterized in that: In step S01, constructing the geomagnetic field model includes: Describe B0 as the geomagnetic field strength and vertical gradient B in the horizontal flight plane z The residual magnetic field generated is used to construct a first-order vertical gradient model: B0(x,y,z)=B h (x,y)+B z (x,y,z0)Δz Δz=z-z0 Where Δz is the height drop during turbulence, z0 is the starting altitude of the flight, and B h is the geomagnetic field intensity on the horizontal flight plane, and the horizontal gradient second-order model is expressed as: Where N is the order of the local geomagnetic model, A ij are the horizontal geomagnetic parameters to be estimated, x0 is the longitude of the starting point, and y0 is the latitude of the starting point.

4. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to claim 3 is characterized in that: The comprehensive parameter model established in step S02 that takes into account both magnetic interference and the geomagnetic field is: Where r is the sensor measurement error, R is the standard deviation matrix, C is the magnetic interference observation matrix, θ is the corresponding interference parameter, L is the geomagnetic field position matrix, A is the geomagnetic parameter to be estimated, and the geomagnetic field B0 is described as: B0 = LA.

5. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to any one of claims 1 to 4, characterized in that: Step S03 includes: Get historical estimation results Wherein, subscript 1 represents the last estimation result, λ is the regularization parameter, and R is the standard deviation matrix of sensor measurement error; definition: Where I represents the identity matrix; In evolutionary compensation, only the updated partial data Φ2 is stored, where the subscript 2 represents the estimated result after the current evolution; Evolutionary estimates of magnetic disturbance parameters and geomagnetic parameters: in, is the inverse matrix of M2.

6. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to claim 5, characterized in that: When updating the measurement signal, the following signals are obtained: Among them, C2 and L2 are the observation matrices composed of updated data, B2 is the updated measurement signal, n1 is the sampling point of the last measurement, and n2 is the sampling point of the update; According to the updated measurement signal, the data to be stored and updated is determined as follows:

7. The evolutionary aeromagnetic compensation method considering geomagnetic changes according to claim 5, characterized in that: For the updated data stored, use the Woodbury equation to calculate the inverse matrix of M2 8. An evolutionary aeromagnetic compensation device taking into account geomagnetic changes, characterized in that: include: The geomagnetic field model construction module is used to describe the aircraft magnetic interference using the TL model, construct a magnetic interference linear model using the observation matrix formed by the direction vector and the interference parameter matrix formed by the interference parameters to be estimated, and introduce estimable geomagnetic field parameters into the TL model to describe the changing environmental magnetic field, and construct a geomagnetic field model based on the geomagnetic field strength, the residual magnetic field generated by the vertical gradient, and the geomagnetic field strength on the horizontal flight plane; A comprehensive parameter model building module, used to build a comprehensive parameter model that takes both magnetic interference and geomagnetic field into consideration according to the magnetic interference linear model and geomagnetic field model; A synchronous estimation module is used to obtain real-time measurement signals and input them into the comprehensive parameter model to obtain magnetic interference estimation results. The measurement signals include magnetic interference observation data and geomagnetic field positions. Each time the measurement signals are updated, the updated part of the measurement signals is stored. When the current magnetic interference estimation result is estimated, the interference parameters to be estimated are calculated using the previous magnetic interference estimation result, the stored updated measurement signal and the current magnetic interference estimation result, so as to evolve the estimation parameters of the comprehensive parameter model and realize synchronous estimation of magnetic interference and geomagnetic parameters.

9. An electronic device comprising a processor and a memory, wherein the memory is used to store a computer program, wherein: The processor is configured to execute the computer program to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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