Positioning methods, devices, electronic equipment, and storage media based on magnetic induction intensity.

Abstract

This disclosure relates to the field of communication technology, and in particular to a positioning method, apparatus, electronic device, and storage medium based on magnetic induction intensity. The method includes: acquiring scene information corresponding to a positioning target, and acquiring a location information determination method corresponding to the scene information; using a low-frequency transmission source to acquire a first set of magnetic induction intensity values ​​corresponding to the positioning target; processing the first set of magnetic induction intensity values ​​using a data processing method corresponding to the location information determination method to acquire a second set of magnetic induction intensity values; and inputting the second set of magnetic induction intensity values ​​into a positioning model for identification to acquire the location information corresponding to the positioning target. Using this disclosure can improve the matching between the data processing method and scene information, improve the matching between the data processing method and positioning distance, reduce positioning time, reduce the time the positioning target is trapped, improve the convenience and accuracy of acquiring the positioning target's location information, and improve search and rescue efficiency.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a positioning method, apparatus, electronic device and storage medium based on magnetic induction intensity. Background Technology

[0002] In the field of mine communications, the technical bottlenecks faced by traditional radio positioning systems have become a key factor restricting the improvement of the effectiveness of mine safety monitoring systems. The propagation characteristics of high-frequency electromagnetic waves (such as 2.4 GHz Wireless Fidelity (Wi-Fi) and Ultra Wide Band (UWB)) are significantly degraded in metal tunnel environments. The signal delay spread caused by multipath effects exceeds 200 ns, resulting in ranging ambiguity in the time domain and causing the ranging error of traditional Time Difference of Arrival (TDOA) algorithms to exceed the 5-meter threshold. Even more seriously, tunnel deformation caused by mine disasters can lead to polarization mismatch of base station antennas, directly causing the positioning system to malfunction.

[0003] While magnetic induction positioning technology demonstrates advantages in penetration performance, its implementation still faces two major challenges. First, static magnetic field modeling methods, based on pre-defined assumptions about magnetic dipole distribution, cannot respond in real-time to spatial topological changes caused by mining operations. In longwall mining faces, every 10 meters of advance can lead to a 15% distortion in the magnetic field distribution characteristics, causing the static model's positioning error to accumulate to 1.2 meters. Second, in multi-layered tunnel structures, the magnetic field coupling effect generated by traditional single-frequency magnetic sources creates positioning ambiguity zones. Experimental data shows that in a double-layered tunnel environment with a vertical spacing of 5 meters, the positioning error in the Z-axis direction can reach 2.3 meters, severely limiting the accuracy of three-dimensional spatial positioning. Furthermore, the static model lacks an integrated geomagnetic diurnal variation compensation mechanism. In a 12-hour continuous monitoring experiment, the positioning drift showed a linear increasing trend, with a maximum cumulative error of 4.7 meters, failing to meet the timeliness requirements of mine emergency rescue. These technical deficiencies indicate that magnetic induction positioning systems have not yet achieved deep adaptation between magnetic field characteristics and the dynamic mine environment, necessitating the development of adaptive magnetic field modeling and high-precision calculation methods. Summary of the Invention

[0004] This disclosure provides a positioning method, apparatus, electronic device, and storage medium based on magnetic induction intensity, which can improve the matching between data processing methods and scene information, and improve the accuracy of obtaining the location information of the positioning target. The technical solution of this disclosure is as follows:

[0005] According to a first aspect of the present disclosure, a positioning method based on magnetic induction intensity is provided, the method comprising:

[0006] Obtain scene information corresponding to the positioning target, and obtain the location information determination method corresponding to the scene information;

[0007] A low-frequency signal source is used to obtain the first set of magnetic induction intensity values ​​corresponding to the positioning target;

[0008] Using a data processing method corresponding to the location information determination method, the first set of magnetic induction intensity values ​​is processed to obtain the second set of magnetic induction intensity values;

[0009] The second set of magnetic induction intensity values ​​is input into the positioning model for identification to obtain the location information corresponding to the positioning target.

[0010] According to some embodiments, processing the first set of magnetic flux density values ​​to obtain a second set of magnetic flux density values ​​includes:

[0011] The first set of magnetic flux density values ​​is transformed using Fast Fourier Transform (FFT) to obtain the third set of magnetic flux density values ​​after transformation.

[0012] Obtain the first fitting coefficients corresponding to the Fast Fourier Transform (FFT);

[0013] The first fitting coefficient is used to adjust each magnetic induction value in the third magnetic induction value set to obtain the second magnetic induction value set.

[0014] According to some embodiments, processing the first set of magnetic flux density values ​​to obtain a second set of magnetic flux density values ​​includes:

[0015] A lock-in amplifier is used to process each magnetic induction value in the first set of magnetic induction values ​​to obtain the amplitude corresponding to each magnetic induction value, and the amplitude corresponding to each magnetic induction value is added to the second set of magnetic induction values.

[0016] According to some embodiments, obtaining the amplitude corresponding to each magnetic induction intensity value includes:

[0017] Obtain the second fitting coefficient corresponding to the lock-in amplifier;

[0018] The amplitude corresponding to each magnetic induction intensity value is adjusted using the second fitting coefficient to obtain the adjusted amplitude corresponding to each magnetic induction intensity value.

[0019] According to some embodiments, the method further includes:

[0020] The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is kept horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field.

[0021] Obtain the magnetic induction intensity collected at each historical location in the historical location set;

[0022] The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity;

[0023] Using the least squares method, the processed magnetic induction intensity, and the environmental noise, a set of fitting coefficients is obtained, wherein the set of fitting coefficients includes the fitting coefficients corresponding to the target scene and each data processing method.

[0024] According to some embodiments, the method further includes:

[0025] Obtain parameter information corresponding to the fitting coefficients from the display interface of the target application, wherein the fitting coefficients correspond to each data processing method in the target scene and data processing method set;

[0026] Based on the parameter information and the fitting algorithm, a set of fitting coefficients is obtained, wherein the set of fitting coefficients includes fitting coefficients corresponding to both the target scene and each data processing method.

[0027] According to a second aspect of the present disclosure, a positioning device based on magnetic induction intensity is provided, comprising:

[0028] The method acquisition unit is used to acquire scene information corresponding to the positioning target and acquire the location information determination method corresponding to the scene information;

[0029] The set acquisition unit is used to acquire a set of first magnetic induction intensity values ​​corresponding to the positioning target using a low-frequency signal source;

[0030] The set acquisition unit is further configured to process the first magnetic induction intensity value set using a data processing method corresponding to the location information determination method, and obtain the second magnetic induction intensity value set.

[0031] The positioning unit is used to input the second set of magnetic induction intensity values ​​into the positioning model for identification, and to obtain the location information corresponding to the positioning target.

[0032] According to a third aspect of the present disclosure, an electronic device is provided, comprising:

[0033] processor;

[0034] Memory used to store the processor's executable instructions;

[0035] The processor is configured to execute the instructions to implement the positioning method based on magnetic induction intensity as described in any one of the preceding aspects.

[0036] According to a fourth aspect of the present disclosure, a storage medium is provided that, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform the positioning method based on magnetic induction intensity as described in any of the preceding aspects.

[0037] According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method described in any one of the preceding aspects.

[0038] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects:

[0039] In some or related embodiments, the method involves acquiring scene information corresponding to the positioning target and obtaining a location information determination method corresponding to the scene information; using a low-frequency transmission source to acquire a first set of magnetic induction intensity values ​​corresponding to the positioning target; processing the first set of magnetic induction intensity values ​​using a data processing method corresponding to the location information determination method to acquire a second set of magnetic induction intensity values; and inputting the second set of magnetic induction intensity values ​​into a positioning model for identification to acquire the location information corresponding to the positioning target. Therefore, the acquired data can be processed according to the data processing method corresponding to the location information determination method, improving the accuracy of magnetic induction intensity value acquisition, reducing the use of the same data processing method for different scene information or the lack of processing of the acquired magnetic induction intensity values, which could lead to inaccurate positioning information determination. This can reduce the situation where high-frequency electromagnetic waves cannot locate the target during mine disasters, thus preventing positioning paralysis. It can also improve the matching between the data processing method and the scene information, i.e., improve the matching between the data processing method and the positioning distance, reduce positioning time, reduce the time the positioning target is trapped, improve the efficiency of location information acquisition, improve the convenience and accuracy of acquiring the location information of the positioning target, and improve search and rescue efficiency.

[0040] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0042] Figure 1This is a flowchart of the first positioning method based on magnetic induction intensity provided in the embodiments of this disclosure;

[0043] Figure 2 This is a flowchart of a second positioning method based on magnetic induction intensity provided in the embodiments of this disclosure;

[0044] Figure 3 This is a flowchart of the third positioning method based on magnetic induction intensity provided in the embodiments of this disclosure;

[0045] Figure 4 This is a block diagram illustrating a positioning device based on magnetic induction intensity according to an exemplary embodiment;

[0046] Figure 5 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0047] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0048] This disclosure provides a positioning method, apparatus, electronic device, and storage medium based on magnetic induction intensity. In some embodiments, the terms "positioning method based on magnetic induction intensity" and "information processing method," "communication method," etc., can be used interchangeably; the terms "positioning apparatus based on magnetic induction intensity" and "information processing apparatus," "communication apparatus," etc., can be used interchangeably; and the terms "information processing system," "communication system," etc., can be used interchangeably.

[0049] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0050] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0051] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0052] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0053] In the embodiments disclosed herein, "multiple" refers to two or more.

[0054] In some embodiments, the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0055] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0056] In some embodiments, "terminal" or "terminal device" may be referred to as "user equipment (UE)," "user terminal," "mobile station (MS)," "mobile terminal (MT)," "subscriber station," "mobile unit," "subscriber unit," "wireless unit," "remote unit," "mobile device," "wireless device," "wireless communication device," "remote device," "mobile subscriber station," "access terminal," "mobile terminal," "wireless terminal," "remote terminal," "handset," "user agent," "mobile client," "client," etc.

[0057] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0058] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0059] Figure 1 This is a flowchart of the first positioning method based on magnetic induction intensity provided in the embodiments of this disclosure, as follows: Figure 1 As shown, this magnetic induction intensity-based positioning method can be used in scenarios where positioning is based on low-frequency transmitters, and includes the following steps:

[0060] In step S11, the scene information corresponding to the positioning target is obtained, and the location information determination method corresponding to the scene information is obtained;

[0061] According to some embodiments, the executing entity of this disclosure may be, for example, an electronic device. This electronic device does not specifically refer to a particular fixed device. For example, when the composition of the electronic device changes, the electronic device may also change accordingly. For example, when the identifier of the electronic device changes, the electronic device may also change accordingly. Furthermore, the executing entity of this disclosure may also be, for example, a server or a base station, and this disclosure does not limit this.

[0062] According to some embodiments, the positioning target can be, for example, a target whose location information is to be determined. The positioning target is not specifically a fixed target. The positioning target can be, for example, a fixed target or a moving target. The positioning target can also be, for example, a user or a user's terminal. The positioning target can be, for example, located underground in a coal mine.

[0063] In some embodiments, scene information may be used to indicate the scene where the current positioning target is located. This scene information may include indoor positioning or outdoor positioning. Indoor positioning may include penetrating and non-penetrating scenes. A non-penetrating scene may be, for example, an area without obstacles between the positioning target and the low-frequency signal source. This scene information is not specific to any fixed information. For example, the scene information may change accordingly when the location of the positioning target or the location of the low-frequency signal source changes.

[0064] According to some embodiments, the location information determination method can be used to indicate the method of determining location information, such as the processing method when the magnetic induction intensity value is acquired. This location information determination method is not specifically defined by a fixed method. For example, different scene information can correspond to different location information determination methods. The scene information and location information determination method can be obtained by a method determination model, or they can be determined based on a method setting instruction; this disclosure does not limit this approach.

[0065] In some embodiments, scene information corresponding to the positioning target is obtained, and the location information determination method corresponding to the scene information is obtained.

[0066] In step S12, a low-frequency signal source is used to obtain the first set of magnetic induction intensity values ​​corresponding to the positioning target;

[0067] In some embodiments, the low-frequency transmitter may be, for example, a signal source transmitting at a lower frequency. This low-frequency transmitter may be referred to as a miniaturized low-frequency transmitter, and may be, for example, a mechanical antenna. The mechanical antenna may be a device for transmitting radio signals, consisting of one or more metal rods, capable of emitting electromagnetic waves. The low-frequency transmitter does not specifically refer to a fixed device. For example, when the frequency corresponding to the low-frequency transmitter changes, the low-frequency transmitter may also change accordingly. For example, when the structure of the low-frequency transmitter changes, the low-frequency transmitter may also change accordingly.

[0068] According to some embodiments, the first set of magnetic field strength values ​​may, for example, be a collection of at least one first magnetic field strength value. The "first" in this first set of magnetic field strength values ​​is used to distinguish it from other sets of magnetic field strength values. This first set of magnetic field strength values ​​does not specifically refer to a fixed set. For example, when the number of strength values ​​included in the first set of magnetic field strength values ​​changes, the first set of magnetic field strength values ​​may also change accordingly. For example, when a particular magnetic field strength value in the first set of magnetic field strength values ​​changes, the first set of magnetic field strength values ​​may also change accordingly.

[0069] In some embodiments, a low-frequency transmission source may be used to obtain a set of first magnetic induction intensity values ​​corresponding to the positioning target.

[0070] In step S13, the first set of magnetic induction intensity values ​​is processed using a data processing method corresponding to the location information determination method to obtain the second set of magnetic induction intensity values.

[0071] In some embodiments, the data processing method may be, for example, processing the acquired set of magnetic induction intensities. Different location information determination methods may correspond to different data processing methods. These data processing methods may, for example, include Fast Fourier Transform (FFT) and lock-in amplifier processing. The data processing method corresponding to the location information determination method may be preset, or it may be determined based on the positioning requirements of the current target; this disclosure does not limit this approach.

[0072] The second set of magnetic field strength values ​​can be, for example, a set obtained by processing the first set of magnetic field strength values. This second set of magnetic field strength values ​​is not specifically a fixed set. For example, when the first set of magnetic field strength values ​​changes, the second set of magnetic field strength values ​​can also change accordingly. For example, when the data processing method changes, the second set of magnetic field strength values ​​can also change accordingly.

[0073] In some embodiments, a data processing method corresponding to the location information determination method can be used to process the first set of magnetic induction intensity values ​​to obtain the second set of magnetic induction intensity values.

[0074] In step S14, the second set of magnetic induction intensity values ​​is input into the positioning model for identification to obtain the location information corresponding to the positioning target.

[0075] According to some embodiments, the localization model may be a trained or constructed model that can be used to determine the location information of a target. This localization model is not specifically a fixed model. For example, when the sub-models included in the localization model change, the localization model may also change accordingly. For example, when the model parameters of each sub-model in the localization model change, the localization model may also change accordingly.

[0076] In some embodiments, location information may refer to information about the current location of the target. This location information is not specifically fixed. For example, when the target is moving or the location time changes, the location information may also change accordingly.

[0077] In some embodiments, a second set of magnetic induction intensity values ​​can be input into the positioning model for identification to obtain the location information corresponding to the positioning target.

[0078] In some or related embodiments, the method involves acquiring scene information corresponding to the positioning target and determining the location information corresponding to the scene information; using a low-frequency transmission source to acquire a first set of magnetic induction intensity values ​​corresponding to the positioning target; processing the first set of magnetic induction intensity values ​​using a data processing method corresponding to the location information determination method to acquire a second set of magnetic induction intensity values; and inputting the second set of magnetic induction intensity values ​​into a positioning model for identification to acquire the location information corresponding to the positioning target. Therefore, the acquired data can be processed according to the data processing method corresponding to the location information determination method, improving the accuracy of magnetic induction intensity value acquisition. This reduces the likelihood of inaccurate positioning information due to using the same data processing method for different scene information or directly positioning without processing the acquired magnetic induction intensity values. It can also reduce the possibility of positioning paralysis caused by the inability to locate using high-frequency electromagnetic waves during mine disasters. Furthermore, it improves the matching between the data processing method and the scene information, i.e., improves the matching between the data processing method and the positioning distance, reduces positioning time, reduces the time the positioning target is trapped, improves the efficiency of location information acquisition, enhances the convenience and accuracy of acquiring the positioning target's location information, and improves search and rescue efficiency.

[0079] Figure 2 This is a flowchart of the second positioning method based on magnetic induction intensity provided in the embodiments of this disclosure, as follows: Figure 2As shown, this magnetic induction intensity-based positioning method can be used in scenarios where high-frequency electromagnetic waves cannot locate the location during a mine disaster, but positioning can be achieved based on a low-frequency transmitter. The method includes the following steps:

[0080] In step S21, the scene information corresponding to the positioning target is obtained, and the location information determination method corresponding to the scene information is obtained;

[0081] The relevant descriptions are as described above and will not be repeated here.

[0082] According to some embodiments, scene information may include, for example, indoor positioning.

[0083] In step S22, a low-frequency signal source is used to obtain the first set of magnetic induction intensity values ​​corresponding to the positioning target;

[0084] The relevant descriptions are as described above and will not be repeated here.

[0085] According to some embodiments, the low-frequency transmitting source can be, for example, a rotating permanent magnet mechanical antenna. The transmission frequency of the rotating permanent magnet mechanical antenna can be, for example, 20 Hz. The magnetic flux density modulus |B| at a point in space is measured using a fluxgate magnetometer. j For example, it can be shown in formula (1):

[0086]

[0087] Among them, because the magnetic dipole moment, a key parameter of rotating permanent magnet mechanical antennas, cannot be accurately obtained, At that time, the magnetic flux density modulus |B used for positioning j | It can be as shown in formula (2):

[0088]

[0089] Where A represents the magnetic flux density |B j |and The proportionality coefficient between the two can also be called the fitting coefficient. The measurement of the proportionality coefficient requires that the probe be kept horizontal and parallel to the target plane of the magnetic field radiation field of the rotating permanent magnet mechanical antenna, and aligned with the origin coordinates of the radiation field. This ensures the applicability of the magnetic field model.

[0090] In some embodiments, a low-frequency transmitter and a fluxgate magnetometer can be used to obtain a first set of magnetic flux density values ​​corresponding to the target. The location of the fluxgate magnetometer probe can be, for example, the location of the target.

[0091] In step S23, a data processing method corresponding to the location information determination method is adopted, and the first magnetic induction intensity value set is transformed by the Fast Fourier Transform (FFT) to obtain the transformed third magnetic induction intensity value set.

[0092] The relevant descriptions are as described above and will not be repeated here.

[0093] Data processing methods may include Fast Fourier Transform (FFT) and lock-in amplifier (LPA) processing. Specifically, for example, a fluxgate magnetometer can be used to measure the magnetic flux density at the probe's location, obtaining an instantaneous value of the dynamic magnetic field's magnetic flux density that changes over time. This instantaneous value is then obtained by performing a Fast Fourier Transform (FFT), and the amplitude found at 20Hz in the frequency spectrum is the result. The LPA can then process the instantaneous magnetic flux density value from the fluxgate magnetometer and display it directly as a voltage amplitude on the experimental instrument's screen.

[0094] In step S24, the first fitting coefficients corresponding to the Fast Fourier Transform (FFT) are obtained;

[0095] The relevant descriptions are as described above and will not be repeated here.

[0096] In some embodiments, the first fitting coefficient may be, for example, a coefficient corresponding to a Fast Fourier Transform (FFT). The "first" in this first fitting coefficient is used to distinguish it from the other fitting coefficients and does not specifically refer to a fixed coefficient. For example, when the method of determining the fitting coefficients changes, the first fitting coefficient may also change accordingly. For example, when the value of the coefficient corresponding to the first fitting coefficient changes, the first fitting coefficient may also change accordingly.

[0097] In some embodiments, the first fitting coefficients may be preset, or they may be fitted based on the acquired parameters. This disclosure does not limit this aspect. The first fitting coefficients may, for example, be coefficients that have been pre-verified and meet the coefficient requirements.

[0098] According to some embodiments, the method further includes:

[0099] The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field.

[0100] Obtain the magnetic induction intensity collected at each historical location in the historical location set;

[0101] The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity;

[0102] The least squares method, processed magnetic induction intensity, and environmental noise are used to obtain a set of fitting coefficients. This set includes the fitting coefficients corresponding to the target scene and each data processing method. The target plane can be, for example, the y1o1z1 plane.

[0103] According to some embodiments, the method further includes:

[0104] Obtain the parameter information corresponding to the fitting coefficients in the display interface of the target application, where the fitting coefficients correspond to each data processing method in the target scenario and data processing method set;

[0105] Based on the parameter information and the fitting algorithm, a set of fitting coefficients is obtained, which includes fitting coefficients corresponding to the target scene and each data processing method.

[0106] According to some embodiments, the target application may be, for example, a data processor app. This data processor app may be developed in modules, with the user interface designed using MATLAB App Designer. The core functionality consists of localization algorithm functions built using MATLAB. In MATLAB App Designer, an integrated development environment can be used to lay out the user interface (display interface) and write code for the app. MATLAB App Designer has a comprehensive component library, which can be used to implement most of the functions required by an app. Using MATLAB, the function formulas mentioned above can be easily converted into code.

[0107] The parameter information may include, for example, the measurement distance, the lateral measurement value Ax, and the longitudinal measurement value Ay. Upon receiving the fitting instruction for the fitting coefficients, the fitting coefficients can be determined based on the measurement distance, the lateral measurement value Ax, the longitudinal measurement value Ay, and the fitting algorithm.

[0108] In step S25, the first fitting coefficient is used to adjust each magnetic induction value in the third magnetic induction value set to obtain the second magnetic induction value set.

[0109] The relevant descriptions are as described above and will not be repeated here.

[0110] According to some embodiments, for example, a first fitting coefficient can be used to adjust each magnetic induction value in the third magnetic induction value set to obtain a second magnetic induction value set.

[0111] In some embodiments, the first set of magnetic flux density values ​​may be obtained, for example, by a first fluxgate magnetometer.

[0112] According to some embodiments, the determination of the first fitting coefficient may also include, for example:

[0113] When the second fluxgate is in the scene corresponding to the scene information and the probe of the second fluxgate is determined to meet the preset installation position, the set of historical magnetic induction intensity values ​​corresponding to the historical positioning target is obtained.

[0114] Based on the set of historical magnetic induction intensity values, obtain the first location information corresponding to the historical positioning target;

[0115] Based on the first location information and the second location information, a first fitting coefficient is determined, wherein the second location information is the location information obtained by marking historical positioning targets.

[0116] In step S26, the second set of magnetic induction intensity values ​​is input into the positioning model for identification to obtain the location information corresponding to the positioning target.

[0117] The relevant descriptions are as described above and will not be repeated here.

[0118] In some embodiments, a data processing method corresponding to the location information determination method can be adopted. A Fast Fourier Transform (FFT) is used to transform the first set of magnetic field strength values ​​to obtain a third set of magnetic field strength values. First fitting coefficients corresponding to the FFT are obtained. These first fitting coefficients are used to adjust each magnetic field strength value in the third set of magnetic field strength values ​​to obtain a second set of magnetic field strength values. The second set of magnetic field strength values ​​is then input into a positioning model for identification to obtain the location information corresponding to the positioning target. Therefore, the data can be processed, and the accuracy of obtaining the magnetic field strength values ​​can be improved by adjusting the fitting coefficients, thereby improving the accuracy of determining the location information of the positioning target.

[0119] Figure 3 This is a flowchart of the third positioning method based on magnetic induction intensity provided in the embodiments of this disclosure, as follows: Figure 3 As shown, this magnetic induction intensity-based positioning method can be used in scenarios where positioning is based on low-frequency transmitters, and includes the following steps:

[0120] In step S31, the scene information corresponding to the positioning target is obtained, and the location information determination method corresponding to the scene information is obtained;

[0121] The relevant descriptions are as described above and will not be repeated here.

[0122] In step S32, a low-frequency signal source is used to obtain the first set of magnetic induction intensity values ​​corresponding to the positioning target;

[0123] The relevant descriptions are as described above and will not be repeated here.

[0124] In step S33, a data processing method corresponding to the position information determination method is adopted. A lock-in amplifier is used to process each magnetic induction intensity value in the first magnetic induction intensity value set to obtain the amplitude corresponding to each magnetic induction intensity value, and the amplitude corresponding to each magnetic induction intensity value is added to the second magnetic induction intensity value set.

[0125] The relevant descriptions are as described above and will not be repeated here.

[0126] The data processing method may include, for example, a lock-in amplifier processing method. Specifically, for example, a fluxgate magnetometer is used to measure the magnetic flux density at the location of the fluxgate magnetometer probe. The measured value is the instantaneous value of the magnetic flux density of the dynamic magnetic field that changes over time. The lock-in amplifier can process the instantaneous value of the magnetic flux density from the fluxgate magnetometer and display it directly on the screen of the experimental instrument as a voltage amplitude.

[0127] According to some embodiments, the amplitude corresponding to each magnetic induction intensity value is obtained, including:

[0128] Obtain the second fitting coefficients corresponding to the lock-in amplifier;

[0129] The amplitude corresponding to each magnetic induction intensity value is adjusted using a second fitting coefficient to obtain the adjusted amplitude of each magnetic induction intensity value. Therefore, the fitting coefficient can be used to adjust the magnetic induction intensity value, thereby improving the accuracy of the obtained magnetic induction intensity value and the accuracy of positioning.

[0130] According to some embodiments, the method further includes:

[0131] The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field.

[0132] Obtain the magnetic induction intensity collected at each historical location in the historical location set;

[0133] The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity;

[0134] The least squares method, the processed magnetic induction intensity, and the environmental noise are used to obtain a set of fitting coefficients. The set of fitting coefficients includes the fitting coefficients corresponding to the target scene and each data processing method.

[0135] According to some embodiments, the method further includes:

[0136] Obtain the parameter information corresponding to the fitting coefficients in the display interface of the target application, where the fitting coefficients correspond to each data processing method in the target scenario and data processing method set;

[0137] Based on the parameter information and the fitting algorithm, a set of fitting coefficients is obtained, which includes fitting coefficients corresponding to the target scene and each data processing method.

[0138] According to some embodiments, the target application may be, for example, a data processor app. This data processor app may be developed in modules, with the user interface designed using MATLAB App Designer. The core functionality consists of localization algorithm functions built using MATLAB. In MATLAB App Designer, an integrated development environment can be used to lay out the user interface (display interface) and write code for the app. MATLAB App Designer has a comprehensive component library, which can be used to implement most of the functions required by an app. Using MATLAB, the function formulas mentioned above can be easily converted into code.

[0139] The parameter information may include, for example, the measurement distance, the lateral measurement value Ax, and the longitudinal measurement value Ay. Upon receiving the fitting instruction for the fitting coefficients, the fitting coefficients can be determined based on the measurement distance, the lateral measurement value Ax, the longitudinal measurement value Ay, and the fitting algorithm.

[0140] In step S34, the second set of magnetic induction intensity values ​​is input into the positioning model for identification to obtain the location information corresponding to the positioning target.

[0141] The relevant descriptions are as described above and will not be repeated here.

[0142] In some embodiments, a data processing method corresponding to the location information determination method can be adopted. A lock-in amplifier is used to process each magnetic induction intensity value in the first magnetic induction intensity value set to obtain the amplitude corresponding to each magnetic induction intensity value, and the amplitude corresponding to each magnetic induction intensity value is added to the second magnetic induction intensity value set. The second magnetic induction intensity value set is then input into the positioning model for identification to obtain the location information corresponding to the positioning target. Therefore, a lock-in amplifier can be used to process the data, and the accuracy of obtaining the magnetic induction intensity value can be improved by adjusting the fitting coefficient, thereby improving the accuracy of determining the location information of the positioning target.

[0143] A block diagram of a positioning device based on magnetic induction intensity is shown according to an exemplary embodiment. (Refer to...) Figure 4 The device 400 includes:

[0144] The method acquisition unit 401 is used to acquire scene information corresponding to the positioning target and acquire the location information determination method corresponding to the scene information;

[0145] The set acquisition unit 402 is used to acquire the first set of magnetic induction intensity values ​​corresponding to the positioning target using a low-frequency signal source;

[0146] The set acquisition unit 402 is also used to process the first set of magnetic induction intensity values ​​using a data processing method corresponding to the location information determination method, and to acquire the second set of magnetic induction intensity values.

[0147] The positioning unit 403 is used to input the second set of magnetic induction intensity values ​​into the positioning model for identification and to obtain the location information corresponding to the positioning target.

[0148] According to some embodiments, the set acquisition unit 402 is used to process the first set of magnetic induction intensity values, and when acquiring the second set of magnetic induction intensity values, it is specifically used for:

[0149] The first set of magnetic flux density values ​​is transformed using Fast Fourier Transform (FFT) to obtain the third set of magnetic flux density values ​​after transformation.

[0150] Obtain the first fitting coefficients corresponding to the Fast Fourier Transform (FFT);

[0151] The first fitting coefficient is used to adjust each magnetic induction value in the third magnetic induction value set to obtain the second magnetic induction value set.

[0152] According to some embodiments, the set acquisition unit 402 is used to process the first set of magnetic flux density values, and when acquiring the second set of magnetic flux density values, it is specifically used for:

[0153] A lock-in amplifier is used to process each magnetic induction value in the first set of magnetic induction values ​​to obtain the amplitude corresponding to each magnetic induction value, and the amplitude corresponding to each magnetic induction value is added to the second set of magnetic induction values.

[0154] According to some embodiments, when the collection acquisition unit 402 is used to acquire the amplitude corresponding to each magnetic induction intensity value, it is specifically used for:

[0155] Obtain the second fitting coefficients corresponding to the lock-in amplifier;

[0156] The amplitude corresponding to each magnetic induction intensity value is adjusted using the second fitting coefficient to obtain the amplitude corresponding to each magnetic induction intensity value after adjustment.

[0157] According to some embodiments, the collection acquisition unit 402 is further specifically used for:

[0158] The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field.

[0159] Obtain the magnetic induction intensity collected at each historical location in the historical location set;

[0160] The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity;

[0161] The least squares method, the processed magnetic induction intensity, and the environmental noise are used to obtain a set of fitting coefficients. The set of fitting coefficients includes the fitting coefficients corresponding to the target scene and each data processing method.

[0162] According to some embodiments, the collection acquisition unit 402 is further specifically used for:

[0163] Obtain the parameter information corresponding to the fitting coefficients in the display interface of the target application, where the fitting coefficients correspond to each data processing method in the target scenario and data processing method set;

[0164] Based on the parameter information and the fitting algorithm, a set of fitting coefficients is obtained, which includes fitting coefficients corresponding to the target scene and each data processing method.

[0165] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0166] In some or related embodiments, a method acquisition unit is used to acquire scene information corresponding to the positioning target and acquire a location information determination method corresponding to the scene information; a set acquisition unit is used to acquire a first magnetic induction intensity value set corresponding to the positioning target using a low-frequency signal source; the set acquisition unit is also used to process the first magnetic induction intensity value set using a data processing method corresponding to the location information determination method to acquire a second magnetic induction intensity value set; and a positioning unit is used to input the second magnetic induction intensity value set into a positioning model for identification to acquire the location information corresponding to the positioning target. Therefore, the acquired data can be processed according to the data processing method corresponding to the location information determination method, thereby improving the accuracy of magnetic induction intensity value acquisition. This reduces the situation where different scene information uses the same data processing method or does not process the acquired magnetic induction intensity value, resulting in inaccurate positioning information determination. It can also reduce the situation where high-frequency electromagnetic waves cannot locate the target during mine disasters, thus paralyzing the positioning. Furthermore, it can improve the matching between data processing method and scene information, that is, improve the matching between data processing method and positioning distance, reduce positioning time, reduce the time the target is trapped, improve the efficiency of location information acquisition, improve the convenience and accuracy of obtaining the target's location information, and improve search and rescue efficiency.

[0167] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device 500 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0168] like Figure 5 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. The RAM 503 may also store various programs and data required for the operation of the electronic device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0169] Multiple components in electronic device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows electronic device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0170] The computing unit 501 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above. For example, in some embodiments, the above methods can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 501 can be configured to perform the above methods by any other suitable means (e.g., by means of firmware).

[0171] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0172] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0173] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0174] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0175] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0176] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is established by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the management difficulties and weak business scalability inherent in traditional physical hosts and VPS (Virtual Private Server) services. Servers can also be servers for distributed systems or servers integrated with blockchain technology.

[0177] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0178] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A positioning method based on magnetic induction intensity, characterized in that, The method includes: Obtain scene information corresponding to the positioning target, and obtain the location information determination method corresponding to the scene information; A low-frequency signal source is used to obtain the first set of magnetic induction intensity values ​​corresponding to the positioning target; Using a data processing method corresponding to the location information determination method, the first set of magnetic induction intensity values ​​is processed to obtain the second set of magnetic induction intensity values; The second set of magnetic induction intensity values ​​is input into the positioning model for identification to obtain the location information corresponding to the positioning target; The method further includes: The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is kept horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field. Obtain the magnetic induction intensity collected at each historical location in the historical location set; The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity; Using the least squares method, the processed magnetic induction intensity, and the environmental noise, a set of fitting coefficients is obtained, wherein the set of fitting coefficients includes the fitting coefficients corresponding to the target scene and each data processing method.

2. The method according to claim 1, characterized in that, The step of processing the first set of magnetic induction intensity values ​​to obtain the second set of magnetic induction intensity values ​​includes: The first set of magnetic flux density values ​​is transformed using Fast Fourier Transform (FFT) to obtain the third set of magnetic flux density values ​​after transformation. Obtain the first fitting coefficients corresponding to the Fast Fourier Transform (FFT); The first fitting coefficient is used to adjust each magnetic induction value in the third magnetic induction value set to obtain the second magnetic induction value set.

3. The method according to claim 1, characterized in that, The step of processing the first set of magnetic induction intensity values ​​to obtain the second set of magnetic induction intensity values ​​includes: A lock-in amplifier is used to process each magnetic induction value in the first set of magnetic induction values ​​to obtain the amplitude corresponding to each magnetic induction value, and the amplitude corresponding to each magnetic induction value is added to the second set of magnetic induction values.

4. The method according to claim 3, characterized in that, The step of obtaining the amplitude corresponding to each magnetic induction intensity value includes: Obtain the second fitting coefficient corresponding to the lock-in amplifier; The amplitude corresponding to each magnetic induction intensity value is adjusted using the second fitting coefficient to obtain the adjusted amplitude corresponding to each magnetic induction intensity value.

5. The method according to claim 1, characterized in that, The method further includes: Obtain parameter information corresponding to the fitting coefficients from the display interface of the target application, wherein the fitting coefficients correspond to each data processing method in the target scene and data processing method set; Based on the parameter information and the fitting algorithm, a set of fitting coefficients is obtained, wherein the set of fitting coefficients includes fitting coefficients corresponding to both the target scene and each data processing method.

6. A positioning device based on magnetic induction intensity, characterized in that, include: The method acquisition unit is used to acquire scene information corresponding to the positioning target and acquire the location information determination method corresponding to the scene information; The set acquisition unit is used to acquire a set of first magnetic induction intensity values ​​corresponding to the positioning target using a low-frequency signal source; The set acquisition unit is further configured to process the first magnetic induction intensity value set using a data processing method corresponding to the location information determination method, and obtain the second magnetic induction intensity value set. The positioning unit is used to input the second set of magnetic induction intensity values ​​into the positioning model for identification, and to obtain the location information corresponding to the positioning target; The set acquisition unit is further configured to: The ambient noise is acquired after determining that the probe is in the target scene, and that the probe is kept horizontal and parallel to the target plane of the magnetic induction intensity radiation field of the low-frequency signal source, and aligned with the origin coordinates of the radiation field. Obtain the magnetic induction intensity collected at each historical location in the historical location set; The magnetic induction intensity is processed using various data processing methods in the data processing method set to obtain the processed magnetic induction intensity; Using the least squares method, the processed magnetic induction intensity, and the environmental noise, a set of fitting coefficients is obtained, wherein the set of fitting coefficients includes the fitting coefficients corresponding to the target scene and each data processing method.

7. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the positioning method based on magnetic induction intensity as described in any one of claims 1 to 5.

8. A storage medium storing instructions, characterized in that, When the instructions are executed on an electronic device, the electronic device performs the positioning method based on magnetic induction intensity as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the positioning method based on magnetic induction intensity according to any one of claims 1 to 5.

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