Spacecraft single-machine magnetic source determination method, electronic equipment and storage medium

Abstract

The present application provides a method for determining the magnetic source of a single spacecraft, an electronic device, and a storage medium. The method uses a magnetometer magnetic sensor in a zero magnetic space to collect the time domain magnetic field value at each specified time, and uses an optimization algorithm to invert the dynamic magnetic moment of the single spacecraft in the corresponding time period based on the magnetic field value at each specified time, and then calculates the coefficient vector through the time domain coefficient equation of the defined magnetic source, and reconstructs the dynamic magnetic source model based on the coefficient vector. Based on the above method, the dynamic magnetic source model can be efficiently and accurately reconstructed, and the power spectrum of the dynamic magnetic field of the single spacecraft at any point can be calculated through the dynamic magnetic source model, which is not constrained by time and space, so that the magnetic characteristics of the single spacecraft and the frequency domain information of any interested point can be effectively grasped, which is helpful for the optimization design of satellites.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of magnetic source determination, and in particular to a method for determining a magnetic source of a single spacecraft, an electronic device and a storage medium. Background Art

[0002] Using magnetometer magnetic sensors to measure the magnetic field generated by a single spacecraft, and then using this magnetic field to invert the size and position of the single spacecraft magnetic source, is an important means to understand the magnetic characteristics of a single spacecraft. Related technologies can still achieve the purpose of determining the magnetic source of a single spacecraft by constructing a dynamic magnetic dipole moment model, but the construction process faces time complexity problems, cannot cope with noise, and it is difficult to correct the magnetic dipole moment parameters at each moment, so there is a lack of accurate estimation of the magnetic characteristics of a single spacecraft. Summary of the invention

[0003] The purpose of the present invention is to provide a method for determining the magnetic source of a single spacecraft, an electronic device and a storage medium, aiming to efficiently and accurately reconstruct the dynamic magnetic source model of a single spacecraft, so as to effectively grasp the magnetic characteristics of the single spacecraft and contribute to the optimization design of the satellite.

[0004] To achieve the above objectives, in a first aspect, the present application provides a method for determining a magnetic source of a single spacecraft, comprising:

[0005] Arrange a single spacecraft and a magnetometer magnetic sensor in a zero magnetic space, and obtain original magnetic measurement data of the single spacecraft through the magnetometer magnetic sensor;

[0006] The time-domain magnetic field value at each specified time is selected from the original magnetic measurement data, and an optimization algorithm is used to perform inversion based on the time-domain magnetic field value and the position coordinates of the magnetometer magnetic sensor to obtain the magnetic source parameters at each specified time, where the magnetic source parameters include the dynamic magnetic moment of the spacecraft in the time period corresponding to each specified time;

[0007] Define the time domain coefficient equation of the magnetic source, use the least square method to solve the time domain coefficient equation based on the original magnetic measurement data and the magnetic source parameters, and obtain the coefficient vector, where the coefficient vector represents the relationship between the time domain magnetic field frequency and the corresponding magnetic moment component;

[0008] The magnetic source model of a single spacecraft is reconstructed according to the coefficient vector to obtain a dynamic magnetic source model.

[0009] In some embodiments, arranging a spacecraft stand-alone and a magnetometer magnetic sensor in a zero magnetic space includes:

[0010] Arrange a sample stage at the center of the zero magnetic space, place the spacecraft at the center of the sample stage, and ensure that the spacecraft is turned on;

[0011] Arranging sensor brackets around the sample stage respectively, and arranging a specified number of magnetometer magnetic sensors on each sensor bracket;

[0012] All magnetometer magnetic sensors are connected to a multi-channel data acquisition instrument, and the original magnetic measurement data of all magnetometer magnetic sensors are collected through the multi-channel data acquisition instrument.

[0013] In some embodiments, the optimization algorithm includes any one of a particle swarm algorithm, a genetic algorithm, and a sparrow algorithm.

[0014] In some embodiments, the expression of the magnetic source parameter is:

[0015] (M(q),r)

[0016] q=t1,t2,…,t m represents each specified moment, M(q) represents the three-dimensional parameter of the magnetic moment of the magnetic source at each specified moment, and r represents the three-dimensional parameter of the position of the magnetic source.

[0017] In some embodiments, the expression of the time domain coefficient equation is:

[0018] X T XC i =X T Y i

[0019] C i =(X T X) -1 X T Y i

[0020] i=x, y, z represent three-dimensional components, C i represents the corresponding component of the coefficient vector, Y i represents the corresponding component of the magnetic moment transposed matrix, X represents the time domain frequency matrix;

[0021] The expression of the magnetic moment transpose matrix is:

[0022] Y=[M(t1)M(t2)…M(t m )] T

[0023] t1,t2,…,t m represents each specified moment, Y represents the magnetic moment transposed matrix;

[0024] The expression of the time domain frequency matrix is:

[0025]

[0026] f represents the time domain frequency, n represents the number of time domain frequencies, and the dimension of X is m×2n.

[0027] In some embodiments, the expression of the dynamic magnetic source model is:

[0028]

[0029] k=1, 2, ..., n represents each time domain frequency, and n represents the number of time domain frequencies.

[0030] In some embodiments, after obtaining the dynamic magnetic source model, the method further includes:

[0031] The original time-domain magnetic field at the magnetometer magnetic sensor is obtained, and the dynamic time-domain magnetic field at the magnetometer magnetic sensor is calculated according to the dynamic magnetic source model; the expression of the dynamic time-domain magnetic field is:

[0032]

[0033] B′ p (t) represents the dynamic time domain magnetic field, r represents the position coordinates of the magnetic source to the magnetic sensor of the magnetometer, is the corresponding unit vector, μ0 represents the vacuum permeability, which is 4π×10 -7 H / m.

[0034] The power spectra of the original time-domain magnetic field and the dynamic time-domain magnetic field are calculated respectively, and the correlation coefficient between the original time-domain magnetic field and the dynamic time-domain magnetic field is calculated based on the obtained power spectra;

[0035] The dynamic magnetic source model is iteratively updated according to the correlation coefficient until the correlation coefficient reaches a preset coefficient threshold, and the final dynamic magnetic source model is output.

[0036] In some embodiments, the coefficient threshold is 0.95; the expression of the correlation coefficient is:

[0037]

[0038] R represents the correlation coefficient, and its value range is [-1,1]; Represents the amplitude of the power spectrum of the original time-domain magnetic field; Represents the amplitude of the power spectrum of the dynamic time-domain magnetic field; Represents the average value of the amplitude of the power spectrum of the original time-domain magnetic field; Represents the average value of the amplitude of the power spectrum of the dynamic time-domain magnetic field.

[0039] In a third aspect, the present application provides an electronic device, including a memory and a processor, wherein the memory stores instructions, and when the instructions are called by the processor, the processor executes the method described in any one of the first aspects above.

[0040] In a fourth aspect, the present application provides a storage medium comprising computer program instructions, wherein the computer program instructions are used to enable a computer to execute a method as described in any one of the first aspects above.

[0041] Compared with the prior art, the present invention has the following advantages:

[0042] The present application provides a method for determining the magnetic source of a single spacecraft, an electronic device, and a storage medium. The method uses a magnetometer magnetic sensor in a zero magnetic space to collect the time domain magnetic field value at each specified time, and uses an optimization algorithm to invert the dynamic magnetic moment of the single spacecraft in the corresponding time period based on the magnetic field value at each specified time, and then calculates the coefficient vector through the time domain coefficient equation of the defined magnetic source, and reconstructs the dynamic magnetic source model based on the coefficient vector. Based on the above method, the dynamic magnetic source model can be efficiently and accurately reconstructed, and the power spectrum of the dynamic magnetic field of the single spacecraft at any point can be calculated through the dynamic magnetic source model, which is not constrained by time and space, so that the magnetic characteristics of the single spacecraft and the frequency domain information of any interested point can be effectively grasped, which is helpful for the optimization design of satellites. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings:

[0044] Figure 1 This is a flow chart of a method for determining a magnetic source of a single spacecraft provided by the present application as an example;

[0045] Figure 2 is a flow chart of the particle swarm algorithm exemplarily provided in this application;

[0046] Figure 3 is a logical schematic diagram of a reconstructed dynamic magnetic source model exemplarily provided in the present application;

[0047] Figure 4 This is an example diagram of randomly selecting magnetic field values ​​at a certain moment provided by the present application;

[0048] Figure 5 This is a result diagram of the real dynamic magnetic moment and the fitted dynamic magnetic moment provided by the present application as an example;

[0049] Figure 6 It is a schematic diagram of the power spectrum of the magnetic field generated at the magnetic sensor of the magnetometer by the real dynamic magnetic moment and the fitted dynamic magnetic moment provided by the present application as an example;

[0050] Figure 7 This is a result diagram of the real magnetic moment and the fitted magnetic moment in the time domain provided by the present application as an example;

[0051] Figure 8 This is a result diagram of the real magnetic moment and the fitted magnetic moment in the frequency domain provided by the present application as an example;

[0052] Fig. 9 This is a schematic diagram of a magnetic field signal generated by a real magnetic moment and a fitted magnetic moment at a magnetically sensitive position provided by the present application as an example;

[0053] Fig.10 is a schematic diagram of the power spectrum of the magnetic field generated by the real magnetic moment and the fitted magnetic moment at the magnetic sensitive position provided by the present application as an example;

[0054] Fig.11 It is a schematic diagram of an electronic device provided as an example in this application. DETAILED DESCRIPTION

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0056] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0057] The embodiments of the present application aim to efficiently and accurately reconstruct the dynamic magnetic source model of a single spacecraft, thereby effectively grasping the magnetic characteristics of the single spacecraft and facilitating the optimization design of the satellite.

[0058] To achieve the above purpose, refer to Figure 1 The present application provides a method for determining a magnetic source of a single spacecraft, which can be executed on an electronic device and includes:

[0059] S101, arranging a single spacecraft and a magnetometer magnetic sensor in a zero magnetic space, and obtaining original magnetic measurement data of the single spacecraft through the magnetometer magnetic sensor.

[0060] In some embodiments, step S101 can be performed as follows: first, a sample table is arranged at the center of the zero magnetic space, a single spacecraft is placed in the center of the sample table, and the single spacecraft is ensured to be turned on; then, sensor brackets are arranged around the sample table, a specified number of magnetometer magnetic sensors are arranged on each sensor bracket, and then all magnetometer magnetic sensors are connected to a multi-channel data acquisition instrument, and the original magnetic measurement data of all magnetometer magnetic sensors are collected through the multi-channel data acquisition instrument.

[0061] Specifically, the magnetometer magnetic sensors can be arranged on the top of the four sides of the sample stage, and four magnetometer magnetic sensors can be arranged on the sensor brackets on each side. The sampling frequency of the multi-channel data acquisition instrument is approximately 5Hz, or it can be flexibly adjusted according to the frequency band of interest, and there is no restriction on this. After the spacecraft single machine runs stably, the magnetometer magnetic sensor reads and records the time domain magnetic field of the frequency band of interest, and performs fast Fourier transform on the time domain magnetic field to obtain the original magnetic measurement data.

[0062] The original magnetic measurement data includes the magnetic field frequency, and the expression of the magnetic field frequency is shown in the following formula (1):

[0063] B(f)=FFT[B(t)] (1)

[0064] B(t) represents the three-dimensional time domain magnetic field, FFT represents fast Fourier transform, B(f) represents the frequency domain signal after fast Fourier transform, and f represents the corresponding frequency.

[0065] S102, selecting the time domain magnetic field value at each designated moment from the original magnetic measurement data, and using an optimization algorithm to perform inversion based on the time domain magnetic field value and the position coordinates of the magnetometer magnetic sensor to obtain the magnetic source parameters at each designated moment.

[0066] Specifically, the magnetic source parameters include the dynamic magnetic moment of the spacecraft in the time period corresponding to each specified moment. The number of specified moments is denoted as m. In some embodiments, m moments can be randomly selected in the frequency band of interest as each specified moment, and each magnetometer magnetic sensor extracts an equal number of moments. Then, each specified moment and the position coordinates of the corresponding magnetometer magnetic sensor are used as inputs of the optimization algorithm, and the optimization algorithm is used to invert the magnetic source parameters at the same moment. The expression of the magnetic source parameters is shown in the following formula (2):

[0067] (M(q),r)(2)

[0068] q=t1,t2,…,t m represents each specified moment, M(q) represents the three-dimensional parameter of the magnetic moment of the magnetic source at each specified moment, and r represents the three-dimensional parameter of the position of the magnetic source.

[0069] In some embodiments, the optimization algorithm includes any one of a particle swarm algorithm, a genetic algorithm, and a sparrow algorithm. Figure 2 The main steps of the particle swarm algorithm include: calculating the individual fitness function value after setting the initial parameters, then updating the individual optimal value and the global optimal value, and then updating the individual position, judging whether the iteration meets the iteration number, and returning to the step of calculating the individual fitness function value when the iteration number is not met, until the global optimal value and the position of each individual are saved after the iteration. The individual refers to the input of the optimization algorithm.

[0070] S103, defining a time domain coefficient equation of the magnetic source, using the least square method, solving the time domain coefficient equation based on the original magnetic measurement data and the magnetic source parameters to obtain a coefficient vector, wherein the coefficient vector represents the relationship between the time domain magnetic field frequency and the corresponding magnetic moment component.

[0071] The expressions of the time domain coefficient equation are shown in (3) and (4):

[0072] X T XC i =X T Y i (3)

[0073] C i =(X T X) -1 X T Y i (4)

[0074] i=x, y, z represent three-dimensional components, C i represents the corresponding component of the coefficient vector, Y i represents the corresponding component of the magnetic moment transposed matrix, and X represents the time domain frequency matrix.

[0075] The expression of the magnetic moment transpose matrix is ​​shown as follows (5):

[0076] Y=[M(t1)M(t2)…M(t m )] T (5)

[0077] q=t1,t2,…,t m represents each specified moment, and M(q) represents the three-dimensional parameter of the magnetic moment of the magnetic source at each specified moment.

[0078] The expression of the time domain frequency matrix is ​​shown as follows (6):

[0079]

[0080] f represents the time domain frequency, n represents the number of time domain frequencies, and the dimension of X is m×2n.

[0081] The least squares method is used to solve the time domain coefficient equation so that ‖XC i -Y i ‖ 2 Minimize and get the coefficient vector.

[0082] S104, reconstructing the magnetic source model of the single spacecraft according to the coefficient vector to obtain a dynamic magnetic source model.

[0083] The expression of the dynamic magnetic source model is shown as follows (7):

[0084]

[0085] k=1, 2, ..., n represents each time domain frequency, and n represents the number of time domain frequencies.

[0086] In some embodiments, the power spectrum of the dynamic magnetic field generated by a single spacecraft at any point or area of ​​interest is calculated through a dynamic magnetic source model, thereby verifying whether the single spacecraft meets the dynamic magnetic field noise index. Specifically, it includes: obtaining the original time domain magnetic field at the magnetometer magnetic sensor, and calculating the dynamic time domain magnetic field at the magnetometer magnetic sensor according to the dynamic magnetic source model; calculating the power spectra of the original time domain magnetic field and the dynamic time domain magnetic field respectively, and calculating the correlation coefficient between the original time domain magnetic field and the dynamic time domain magnetic field according to the obtained power spectrum; iteratively updating the dynamic magnetic source model according to the correlation coefficient until the correlation coefficient reaches the preset coefficient threshold, and outputting the final dynamic magnetic source model.

[0087] The expression of dynamic time domain magnetic field is shown as follows (8):

[0088]

[0089] B′ p (t) represents the dynamic time domain magnetic field, r represents the position coordinates of the magnetic source to the magnetic sensor of the magnetometer, is the corresponding unit vector, μ0 represents the vacuum permeability, which is 4π×10 -7 H / m.

[0090] The expression of the power spectrum of the original time-domain magnetic field is shown as follows (9):

[0091]

[0092] The expression of the power spectrum of the dynamic time-domain magnetic field is shown as follows (10):

[0093]

[0094] and Respectively represent the power spectrum amplitude of the original time domain magnetic field and the dynamic time domain magnetic field, and Represent the power spectrum frequencies of the original time domain magnetic field and the dynamic time domain magnetic field respectively.

[0095] The expression of the correlation coefficient is shown as follows (11):

[0096]

[0097] R represents the correlation coefficient, and its value range is [-1,1]; Represents the amplitude of the power spectrum of the original time-domain magnetic field; Represents the amplitude of the power spectrum of the dynamic time-domain magnetic field; Represents the average value of the amplitude of the power spectrum of the original time-domain magnetic field; Represents the average value of the amplitude of the power spectrum of the dynamic time-domain magnetic field.

[0098] In some embodiments, the coefficient threshold R is 0.95. When R<0.95, it means that the fitted dynamic magnetic source model is significantly different from the original magnetic source model, and the process can return to step S102 to increase the number of specified moments, and then perform iterative operations according to the above steps. Figure 3 , from the original magnetic field B ac Extract the magnetic field B at each specified time t And invert the corresponding magnetic moment M t , and then fit the dynamic magnetic moment M ac and dynamic magnetic field B′ ac , respectively according to the original magnetic field B ac and dynamic magnetic field B′ ac Calculate the original time domain magnetic field fB ac Power spectrum and dynamic time-domain magnetic field fB′ ac The power spectra are compared. When the correlation coefficient between the power spectra reaches 0.95 or above, it proves that the dynamic magnetic source model of the spacecraft is slightly different from the original magnetic source model, thereby efficiently and accurately reconstructing the dynamic magnetic source model.

[0099] In addition, the power spectrum of the dynamic magnetic field of a single spacecraft at any point can be calculated through formulas (9)-(11) related to the dynamic magnetic source model, which is not constrained by time and space. This can effectively grasp the magnetic characteristics of the single spacecraft and the frequency domain information of any point of interest, which is helpful for the optimization design of satellites.

[0100] In order to verify the proposed method for determining the magnetic source of a single spacecraft, a total of 30 different experiments were conducted. In each experiment, ten frequencies between 0.1 and 0.9 Hz were randomly selected as the main frequencies of a magnetic source, and random noise of 5% of its amplitude was added to the magnetic field at each moment. Figure 4This shows an example of randomly selecting magnetic field values ​​at a certain moment, with the horizontal axis representing time and the vertical axis representing the magnetic field value. Figure 4 It can be seen that, on average, only 45 inversions are required to realize inversion in the time domain, which saves 94.37% of the number of calculations compared to the prior art and improves the calculation efficiency of the dynamic magnetic moment model.

[0101] Figure 5 The results of the true dynamic magnetic moment and the fitted dynamic magnetic moment during a measurement process are shown, where the true magnetic moment at the corresponding moment of the magnetic field inversion at 45 randomly selected moments is obtained. Figure 5 The horizontal axis represents time, and the vertical axis represents magnetic moment. Figure 6 The power spectrum of the magnetic field generated by the real dynamic magnetic moment and the fitted dynamic magnetic moment at the magnetometer magnetic sensor is shown. Figure 6 The horizontal axis represents frequency, and the vertical axis represents power. Figure 5 , Figure 6 It can be seen that due to the noise in the experimental data, -2 ~10 -1 There is a certain error within the frequency band, but the amplitude is small. 0 In the frequency band above Hz, there is a big difference between the power spectrum of the fitted magnetic field and the power spectrum of the real magnetic field. The reason is that the fitted dynamic magnetic moment model cannot fit the influence of the noise signal, while the power spectrum of the magnetic field generated by the noise-free dynamic magnetic moment model is basically consistent with the power spectrum of the fitted magnetic field in this frequency band. This means that the present application can effectively fit the original dynamic magnetic source information and can also accurately calculate the power spectrum of the dynamic magnetic field.

[0102] Figure 7 The results of the true magnetic moment and the fitted magnetic moment in the time domain are shown (the input used for the fitted magnetic moment is different from the time period of the true magnetic moment), with the horizontal axis representing time and the vertical axis representing the magnetic moment. Figure 8 The results of the true magnetic moment and the fitted magnetic moment in the frequency domain are shown, with the horizontal axis representing frequency and the vertical axis representing power. Fig. 9 It shows that the real magnetic moment and the fitted magnetic moment generate magnetic field signals at the magnetic sensitive position (non-measurement point position), with the horizontal axis representing time and the vertical axis representing the magnetic field value. Fig.10 The power spectrum of the magnetic field generated by the real magnetic moment and the fitted magnetic moment at the magnetic sensitive position (non-measurement point position) is shown, and the horizontal axis represents the frequency and the vertical axis represents the power. Figure 7 , Figure 8 It can be seen that although the fitted dynamic magnetic moment and the real dynamic magnetic moment have huge differences in different time periods, their frequency domain information is basically consistent, indicating that the dynamic magnetic source model in this application can well determine the frequency domain information of the magnetic source. Fig. 9 , Fig.10It can be seen that although the dynamic magnetic field generated at the magnetic sensitive position is also different, the power spectrum of the magnetic field is basically the same. Therefore, the frequency domain information of the magnetic source at any position can also be obtained, which is not constrained by time and space. It can help the spacecraft to test whether the magnetic field generated by itself at the magnetic sensitive position meets the indicators, thereby helping to carry out the optimal design of the satellite.

[0103] Further, if Fig.11 An exemplary embodiment of the present application further provides an electronic device, including a memory 1101 and a processor 1102, wherein the memory 1101 stores instructions, and when the instructions are executed by the processor 1102, the processor 1102 executes any method of the first aspect.

[0104] It should be understood that the processor mentioned in the embodiments of the present application may be a CPU, or other general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0105] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory, dynamic random access memory, synchronous dynamic random access memory, double data rate synchronous dynamic random access memory, enhanced synchronous dynamic random access memory, synchronously connected dynamic random access memory, and direct memory bus random access memory.

[0106] The present application also provides a storage medium storing computer program instructions, which, when executed by a processor of a computer, enables the computer to execute the steps of any of the methods mentioned above.

[0107] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or any combination of the above mediums.

[0108] The basic concepts have been described above. Obviously, for those skilled in the art, the above invention disclosure is only used as an example and does not constitute a limitation of the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements and amendments to the present application. Such modifications, improvements and amendments are suggested in the present application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of the present application.

[0109] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0110] Some aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, various aspects of the present application may be expressed as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes ...), optical disks (e.g., compact disks CDs, digital versatile disks DVDs ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0111] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated via any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or any combination of the above mediums.

[0112] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the object of this application are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0113] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0114] Although the present application has been described with reference to the current specific embodiments, ordinary technicians in this technical field should recognize that the above embodiments are only used to illustrate the present application, and various equivalent changes or substitutions may be made without departing from the spirit of the present application. Therefore, as long as the changes and modifications to the above embodiments are within the essential spirit of the present application, they will fall within the scope of the claims of the present application.

Claims

1. A method for determining a single-machine magnetic source of a spacecraft, characterized in that: include: Arranging a single spacecraft and a magnetometer magnetic sensor in a zero magnetic space, and obtaining raw magnetic measurement data of the single spacecraft through the magnetometer magnetic sensor; Selecting the time-domain magnetic field value at each designated moment from the original magnetic measurement data, and using an optimization algorithm to perform inversion based on the time-domain magnetic field value and the position coordinates of the magnetic sensor of the magnetometer to obtain the magnetic source parameters at each designated moment, wherein the magnetic source parameters include the dynamic magnetic moment of the single spacecraft in the time period corresponding to each designated moment; Defining a time domain coefficient equation of the magnetic source, solving the time domain coefficient equation based on the original magnetic measurement data and the magnetic source parameters using a least square method to obtain a coefficient vector, wherein the coefficient vector represents the relationship between the time domain magnetic field frequency and the corresponding magnetic moment component; The magnetic source model of the single spacecraft is reconstructed according to the coefficient vector to obtain a dynamic magnetic source model.

2. The method according to claim 1, characterized in that The arrangement of the spacecraft and the magnetometer magnetic sensor in the zero magnetic space includes: Arranging a sample stage at the center of the zero magnetic space, placing the single spacecraft at the center of the sample stage, and ensuring that the single spacecraft is in a powered-on state; Arranging sensor brackets around the sample stage respectively, and arranging a specified number of magnetometer magnetic sensors on each sensor bracket; All magnetometer magnetic sensors are connected to a multi-channel data acquisition instrument, and the original magnetic measurement data of all magnetometer magnetic sensors are collected by the multi-channel data acquisition instrument.

3. The method according to claim 1 or 2, characterized in that The optimization algorithm includes any one of a particle swarm algorithm, a genetic algorithm, and a sparrow algorithm.

4. The method according to claim 1, characterized in that The expression of the magnetic source parameter is: (M(q), r) q=t1,t2,...,t m Represents each specified moment, M(q) represents the three-dimensional parameter of the magnetic moment of the magnetic source at each specified moment, and r represents the three-dimensional parameter of the position of the magnetic source.

5. The method according to claim 1, characterized in that The expression of the time domain coefficient equation is: X T XC i =X T Y i C i =(X T X) -1 X T Y i i=x,y,z represents three-dimensional components, C i represents the corresponding component of the coefficient vector, Y i represents the corresponding component of the magnetic moment transposed matrix, X represents the time domain frequency matrix; The expression of the magnetic moment transposed matrix is: Y=[M(t1)M(t2)…M(t m )] T t1, t2, ..., t m represents each designated moment, and Y represents the magnetic moment transposed matrix; The expression of the time domain frequency matrix is: f represents the time domain frequency, n represents the number of time domain frequencies, and the dimension of X is m×2n.

6. The method according to claim 1, characterized in that The expression of the dynamic magnetic source model is: k=1, 2, ..., n represents each time domain frequency, and n represents the number of time domain frequencies.

7. The method according to claim 6, characterized in that After the dynamic magnetic source model is obtained, the method further includes: The original time domain magnetic field at the magnetometer magnetic sensor is obtained, and the dynamic time domain magnetic field at the magnetometer magnetic sensor is calculated according to the dynamic magnetic source model; wherein the expression of the dynamic time domain magnetic field is: B′ p (t) represents the dynamic time-domain magnetic field, r represents the position coordinates of the magnetic source to the magnetic sensor of the magnetometer, is the corresponding unit vector, μ0 represents the vacuum permeability, which is 4π×10 -7 H / m; Calculating the power spectra of the original time-domain magnetic field and the dynamic time-domain magnetic field respectively, and calculating the correlation coefficient between the original time-domain magnetic field and the dynamic time-domain magnetic field according to the obtained power spectra; The dynamic magnetic source model is iteratively updated according to the correlation coefficient until the correlation coefficient reaches a preset coefficient threshold, and a final dynamic magnetic source model is output.

8. The method according to claim 7, characterized in that The coefficient threshold is 0.95; the expression of the correlation coefficient is: R represents the correlation coefficient, and its value range is [-1,1]; represents the amplitude of the power spectrum of the original time-domain magnetic field; represents the amplitude of the power spectrum of the dynamic time-domain magnetic field; represents the average value of the amplitude of the power spectrum of the original time-domain magnetic field; Represents the average value of the amplitude of the power spectrum of the dynamic time-domain magnetic field.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores instructions, and when the instructions are called by the processor, the processor executes the method according to any one of claims 1 to 8.

10. A storage medium, characterized in that: The method comprises computer program instructions, wherein the computer program instructions are used to cause a computer to execute the method according to any one of claims 1 to 8.

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