Geomagnetic contour matching method and device and medium

Abstract

The invention discloses a geomagnetic contour matching method and device and a medium, and the method comprises the steps: obtaining an actual measurement geomagnetic vector sequence, carrying out the grid search of a geomagnetic matching region under the condition of initial search spatial resolution, obtaining a to-be-matched point, and generating a reference geomagnetic vector sequence based on the to-be-matched point; and determining the combination similarity of the two sequences in direction and strength, and screening out candidate points greater than a similarity threshold. And then, continuously reducing the resolution of the search space to carry out loop search until a given number of iterations is reached, and taking a candidate point corresponding to the maximum combination similarity obtained by final loop as a matching positioning point. Therefore, the geomagnetic vector information is fully utilized, and the similarity of the two sequences is determined based on the multi-dimensional combination similarity of the direction and intensity of the geomagnetic sequences, so that the points to be matched are screened, and the matching precision is improved. In addition, a multi-scale search strategy is adopted, and the resolution of a search space is continuously reduced for cyclic search, so that the matching efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of geomagnetic navigation, and in particular, to a geomagnetic contour matching method, device, and medium. Background Art

[0002] The geomagnetic navigation technology matches the data measured in the field with the pre-stored geomagnetic map through the geomagnetic contour matching algorithm to find the most similar geomagnetic contour, thereby determining the actual position of the carrier. Due to the advantages of not relying on external signal sources, strong anti-interference ability, and no cumulative error, and being able to provide reliable positioning information in cases where satellite signals are limited or signals are interfered, the geomagnetic navigation technology is widely used in underground, underwater, garage and other scenarios.

[0003] Currently, mainly through the MAGCOM (Magnetic Contour Matching) geomagnetic contour matching algorithm, the scalar geomagnetic field intensity information is matched and calculated to determine the actual position information of the carrier. Such a geomagnetic contour matching method only utilizes the scalar information of the geomagnetic field intensity, with low matching accuracy, high computational complexity, low matching efficiency, and it is difficult to meet the high real-time requirements of many application scenarios.

[0004] Therefore, how to improve the accuracy and efficiency of geomagnetic navigation is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, one aspect of this application provides a geomagnetic contour matching method, and the method includes: S10: Obtain the measured geomagnetic vector sequence and the search space resolution for searching the geomagnetic matching region; S11: Conduct a grid search on the geomagnetic matching region under the condition of the search space resolution to obtain the points to be matched; and generate a reference geomagnetic vector sequence based on the points to be matched; S12: Determine the combined similarity in direction and intensity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; and screen out the candidate points corresponding to the combined similarity greater than the similarity threshold; S13: Reduce the search space resolution, and repeat steps S11 to S13 until the preset iteration condition is met. The preset iteration condition includes reaching a given number of iterations; S14: Take the candidate point corresponding to the maximum combined similarity obtained after step S13 as the matching and positioning point.

[0006] Optionally, the determining the combined similarity in direction and intensity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence includes: Determine the direction similarity, intensity similarity, and matching quality index between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; Determine a pair of weight coefficients including a direction weight coefficient and an intensity weight coefficient according to the matching quality index; Determine the combined similarity according to the pair of weight coefficients, the direction similarity, and the intensity similarity.

[0007] Optionally, when the matching quality index is larger, the direction weight coefficient is larger and the intensity weight coefficient is smaller; and the sum of the direction weight coefficient and the intensity weight coefficient is equal to 1.

[0008] Optionally, determining the direction similarity, intensity similarity, and matching quality index between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence includes: Determine the direction similarity and the intensity similarity respectively based on the cosine distance and the normalized Euclidean distance between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; Obtain a preset direction similarity threshold and intensity similarity threshold; Determine a direction quality component and an intensity quality component according to the direction similarity threshold and the intensity similarity threshold; Determine the matching quality index according to the direction quality component and the intensity quality component.

[0009] Optionally, the preset iteration condition includes that there is one remaining candidate point, the given number of iterations is reached, and at least one of the difference between the maximum value and the second maximum value of the combined similarity is greater than a preset difference.

[0010] Optionally, the search space resolution includes a search area and a search step size. Obtaining the search space resolution of the search geomagnetic matching area includes: Obtain a preset reference step size, the motion speed of the carrier, the drift error of the inertial navigation system, and the geomagnetic characteristics of the geomagnetic matching area; Determine the search step size according to the preset reference step size and the motion speed; wherein, when the motion speed is larger, the search step size is larger; Determine the search area according to the drift error; wherein, when the drift error is larger, the search area is larger; when the geomagnetic characteristics are more obvious, the search area is larger.

[0011] Optionally, the geomagnetic profile matching method further includes: Obtain the influence factor of the given number of iterations; wherein the influence factor includes the motion characteristic parameters of the carrier, the spatial distribution characteristic parameters of the geomagnetic matching area, and the matching real-time instruction; Determine the given number of iterations according to the influence factor; wherein, when the motion characteristic parameter characterizes the more complex motion of the carrier, the given number of iterations is larger; when the spatial distribution characteristic parameter characterizes the more complex geomagnetic distribution, the given number of iterations is larger; when the matching real-time instruction characterizes the higher real-time requirement, the given number of iterations is smaller.

[0012] Another aspect of the present application provides a geomagnetic contour matching device, the device includes: A first acquisition module, configured to acquire a measured geomagnetic vector sequence and the search space resolution of the search geomagnetic matching area; A reference sequence acquisition module, configured to perform grid search on the geomagnetic matching area under the condition of the search space resolution to obtain points to be matched; and generate a reference geomagnetic vector sequence based on the points to be matched; A candidate point screening module, configured to determine the combined similarity in direction and intensity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; and screen out candidate points corresponding to the combined similarity greater than the similarity threshold; A processing module, configured to reduce the search space resolution, and repeatedly call the reference sequence acquisition module and the candidate point screening module until a preset iteration condition is met, and the preset iteration condition includes reaching a given number of iterations; A matching positioning point acquisition module, configured to use the candidate point corresponding to the maximum combined similarity obtained after the processing module as the matching positioning point.

[0013] Another aspect of the present application provides a geomagnetic contour matching device, including a memory and a processor, and a computer program that can run on the processor is stored on the memory, and when the processor executes the program, the steps of the geomagnetic contour matching method are implemented.

[0014] Another aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the geomagnetic contour matching method are implemented.

[0015] The beneficial effects of the geomagnetic contour matching method, device and medium provided by the present application are as follows: Thus, by making full use of geomagnetic vector information and determining the similarity between two sequences based on the combined similarity in multiple dimensions of the geomagnetic sequence direction and intensity, the points to be matched obtained by searching are screened, thereby improving the accuracy of geomagnetic contour matching. In addition, a multi-scale search strategy is adopted, and the search space resolution is continuously reduced to perform cyclic search from top to bottom, improving the matching efficiency to meet the real-time requirement of navigation while further improving the matching accuracy. That is, the present application is based on geomagnetic vector information, combined similarity, and continuously shrinking the search range for iterative cycling to achieve improvement of geomagnetic matching accuracy and matching efficiency. Brief Description of the Drawings

[0016] Figure 1 FIG. 1 is a schematic flowchart of a geomagnetic profile matching method provided by an embodiment of the present application; Figure 2 FIG. 2 is a schematic flowchart of another geomagnetic profile matching method provided by an embodiment of the present application; Figure 3 FIG. 3 is a schematic flowchart of a geomagnetic profile matching method provided by another embodiment of the present application; FIG. 4(a) is a schematic diagram of a matching trajectory provided by an embodiment of the present application; FIG. 4(b) is a schematic diagram of another matching trajectory provided by an embodiment of the present application; FIG. 4(c) is a schematic diagram of still another matching trajectory provided by an embodiment of the present application; Figure 5 FIG. 5 is a schematic structural diagram of a geomagnetic profile matching device provided by an embodiment of the present application; Figure 6 FIG. 6 is a schematic structural diagram of a geomagnetic profile matching device provided by another embodiment of the present application.

[0017] The reference numerals are as follows: 50 is a first acquisition module, 51 is a reference sequence acquisition module, 52 is a candidate point screening module, 53 is a processing module, 54 is a matching positioning point acquisition module, 60 is a memory, 61 is a processor, 62 is a display screen, 63 is an input / output interface, 64 is a communication interface, 65 is a power supply, 66 is a communication bus, 601 is a computer program, 602 is an operating system, and 603 is data. Detailed Embodiments

[0018] The terms used in the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. The singular forms "a", "said", and "the" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0019] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0020] Figure 1 The flowchart of a geomagnetic profile matching method provided by an embodiment of the present application is shown as Figure 1 follows. The method includes: S10: Obtain the measured geomagnetic vector sequence and the search space resolution of the search geomagnetic matching area; In an optional embodiment, when the carrier moves to the geomagnetic matching area, the geomagnetic field values of the geomagnetic matching area are collected in real time through a geomagnetic sensor, and after interference compensation, the measured geomagnetic vector sequence, that is, the magnetic field value at the matching and positioning moment, is obtained. It should be noted that the carriers that can perform geomagnetic matching may include, but are not limited to, underwater vehicles, aerial vehicles, vehicles, and robots, and the present application does not limit this.

[0021] When performing geomagnetic navigation matching, in addition to obtaining the measured geomagnetic vector sequence collected by the geomagnetic sensor, it is also necessary to obtain the search space resolution of the search geomagnetic matching area. It can be understood that the search space resolution refers to the accuracy and scale of searching the geomagnetic matching area. Specifically, the search space resolution may include, but is not limited to, the search area and the search step size.

[0022] S11: Perform a grid search on the geomagnetic matching area under the condition of the search space resolution to obtain the points to be matched; and generate a reference geomagnetic vector sequence based on the points to be matched; Further, with the inertial navigation system as the center, under the condition of the obtained search space resolution, perform a grid search on the geomagnetic matching area, and take the points at the grid intersections as the points to be matched, and then generate a reference geomagnetic vector sequence based on the points to be matched.

[0023] Specifically, with the inertial navigation system as the center, a grid of points to be matched is uniformly generated within the search area according to the search step size, and the grid intersections are taken as the points to be matched. Calculate the displacement increment between the current moment and the previous moment (i.e., adjacent points) of the inertial navigation system, that is, determine the inertial navigation trajectory of the inertial navigation system. Further, according to this displacement increment, starting from the point to be matched, generate a matching trajectory identical to the inertial navigation trajectory. Thus, finally, multiple matching trajectories identical to the inertial navigation trajectory and starting from the points to be matched can be obtained.

[0024] Further, query the geomagnetic vector information of the matching trajectory from the pre-stored geomagnetic map, so as to obtain a reference geomagnetic vector sequence corresponding to the measured geomagnetic vector sequence.

[0025] S12: Determine the combined similarity of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence in terms of direction and intensity; and screen out the candidate points corresponding to the combined similarity greater than the similarity threshold; After obtaining the measured geomagnetic vector sequence and the reference geomagnetic vector sequence, the combined similarity between the two vector sequences in terms of direction and intensity is determined. From this, the similarity between the two vector sequences can be determined based on the combined similarity.

[0026] Furthermore, the points with a combined similarity greater than the similarity threshold are selected as candidate points. In a specific embodiment, the points greater than the similarity threshold can be understood as having a relatively high similarity and may be candidate points for the actual movement trajectory points of the carrier.

[0027] S13: Reduce the search space resolution and repeat steps S11 to S13 until the preset iteration condition is met. The preset iteration condition includes reaching a given number of iterations; It can be understood that the search space resolution obtained in step S10 is the search step size of the initially set search area. In addition, in a specific embodiment, under the condition of the initially obtained search space resolution, there are often multiple candidate points screened in step S12. At this time, in order to improve the accuracy of geomagnetic matching and ensure the real-time performance of matching, the search space resolution is reduced for cyclic search.

[0028] Specifically, reducing the search space resolution means reducing the search range and / or the search step size, and taking the candidate points screened in step S12 as the center to perform grid search to obtain new points to be matched. And based on the new points to be matched, a new reference geomagnetic vector sequence is generated.

[0029] Furthermore, according to the combined similarity between the new reference geomagnetic vector sequence and the measured geomagnetic vector sequence, new candidate points are further screened. In this way, cyclic iterative search is performed until the given number of iterations is reached.

[0030] That is to say, based on the pyramid search strategy, after obtaining candidate points through each grid search, taking these candidate points as the center and entering the next layer of the pyramid (a smaller search space resolution) for search to obtain new candidate points. Until cycling to the last layer of the pyramid (that is, reaching the specified number of iterations).

[0031] S14: Take the candidate point corresponding to the one with the largest combined similarity obtained after step S13 as the matching positioning point.

[0032] After the loop ends, if there are multiple candidate points finally obtained in step S13, then take the candidate point corresponding to the one with the largest combined similarity as the matching positioning point, that is, take the point with the highest similarity as the matching positioning point.

[0033] It can be understood that by cyclically executing steps S10 to S14 at each moment, a matching positioning point can be obtained. Connecting the matching positioning points at different moments, that is, the matching movement trajectory of the carrier can be obtained, which is also the matching trajectory close to the real movement trajectory.Figure 2 The flowchart of another geomagnetic profile matching method provided by the embodiments of the present application. To make it clearer for those skilled in the art to understand the technical solutions provided by the present application, the following will be combined with Figure 2 for further description.

[0034] As Figure 2 shown, in an alternative embodiment, the entire geomagnetic matching process can be divided into a rough search stage and a fine search stage. Among them, the fine search stage can include multiple stages. Specifically, before the search, search initialization is performed through step S20, that is, the measured sequence measured in real time (that is, the measured geomagnetic vector sequence obtained in step S10) is obtained. In addition, the parameters of the rough search stage need to be initialized, that is, the initial search space resolution is obtained.

[0035] Furthermore, step S21 and step S22 are executed for the first time, that is, the rough search step is performed. Specifically, centered on the inertial navigation system, under the condition of the initially obtained search space resolution, a grid search is performed on the geomagnetic matching area to obtain the points to be matched, and a reference sequence (that is, the reference geomagnetic vector sequence obtained in step S11) is generated based on the points to be matched.

[0036] Then, the combined similarity between the measured sequence and the reference sequence is calculated, and the candidate points greater than the similarity threshold are screened according to the combined similarity. And through step S23, it is judged whether the current candidate point is one, and / or whether the number of current iterations reaches the specified number of iterations. If any of the conditions is met, the loop can be ended and the matching positioning point can be obtained by entering step S25.

[0037] If none of the conditions in step S23 are met, then step S24 is executed to reduce the search space resolution, and return to step S21 and execute the subsequent steps. It can be understood that except for the first search performed under the condition of the initial search space resolution, which is regarded as the rough search stage, each time the search space resolution is reduced, it is a search that is finer than the previous search.

[0038] Thus, under the multi-scale inverted triangular pyramid search strategy, the search starts from the top layer of the pyramid (the largest search space resolution), and sequentially moves to the next layer of the pyramid, continuously reducing the search space for cyclic search until the preset iteration condition is met.

[0039] It should be noted that, in an optional embodiment, if there are no points greater than the similarity threshold when the candidate points are screened for the first time in step S12, the similarity threshold can be appropriately lowered. After lowering the threshold by the first preset number of times, for example, after lowering it twice, there are still no candidate points that meet the similarity threshold. At this time, the search range can be appropriately expanded, that is, the resolution of the search space initially acquired is adjusted. Similarly, after expanding by the second preset number of times, for example, after expanding it twice, there are still no candidate points that meet the requirements. At this time, the matching result of the previous moment is maintained, and when searching at the next moment, the search range is expanded and the similarity threshold is lowered.

[0040] Of course, in another optional embodiment, when screening candidate points for the first time, the search range can be expanded first, and then a decision can be made whether to lower the similarity threshold based on the result of the expanded search range. In other words, either expanding the search space resolution or lowering the similarity threshold can be performed first, and the other can be used as a search adjustment plan when the former does not exist.

[0041] Therefore, the geomagnetic contour matching method provided in the embodiment of the present application, by making full use of geomagnetic vector information, and determining the similarity of the two sequences based on the combined similarity of the geomagnetic sequence direction and intensity in multiple dimensions, to screen the points to be matched obtained by the search, thereby improving the geomagnetic contour matching accuracy. In addition, a multi-scale search strategy is adopted, and a cyclic search is performed from top to bottom by continuously reducing the search space resolution, thereby improving the matching efficiency while meeting the real-time requirements of navigation and further improving the matching accuracy. That is, the present application is based on geomagnetic vector information, combined similarity, and continuously narrowing the search range iterative cycle to achieve improved geomagnetic matching accuracy and matching efficiency.

[0042] In an optional embodiment, determining the combined similarity of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence in terms of direction and intensity includes: Determine the direction similarity, intensity similarity and matching quality index of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; Determine a weight coefficient pair including a direction weight coefficient and an intensity weight coefficient according to the matching quality index; Based on the weight coefficient pair, the direction similarity and the intensity similarity, the combined similarity is determined.

[0043] In order to further improve the matching accuracy, in an optional embodiment, a combined similarity calculation method with adaptive weights is proposed, which achieves a better matching effect by dynamically adjusting the weights of direction similarity and intensity similarity.

[0044] It can be understood that the combined similarity provided by this application is a combination in terms of direction and intensity, that is, a combined similarity composed of direction similarity and intensity similarity. In different geomagnetic matching regions, the proportions of direction and intensity are different. When the direction of the geomagnetic vector sequence is more reliable, the direction similarity should be appropriately increased. Of course, if the intensity of the geomagnetic vector sequence is more reliable, the intensity similarity should be appropriately increased.

[0045] In a specific embodiment, when determining the combined similarity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence, it is necessary to first determine the direction similarity and intensity similarity of the two sequences respectively. At the same time, it is necessary to determine the matching quality index, which is used to characterize the quality of geomagnetic matching. The matching quality index can also be understood as an index for determining the direction weight coefficient and the intensity weight coefficient. Specifically, the calculation formula is formula (1): (1) Wherein, is the measured geomagnetic vector sequence and the reference geomagnetic vector sequence of the combined similarity, is the direction weight coefficient, is the intensity weight coefficient, is the measured geomagnetic vector sequence and the reference geomagnetic vector sequence of the direction similarity, is the measured geomagnetic vector sequence and the reference geomagnetic vector sequence of the intensity similarity.

[0046] In a specific embodiment, according to the matching quality index, the weight coefficient pair including the direction weight coefficient and the intensity weight coefficient can be determined. Based on the matching quality index, the dynamic adjustment of the direction weight coefficient and the intensity weight coefficient is realized.

[0047] Furthermore, after determining the direction weight coefficient , the intensity weight coefficient , the weight coefficient pair, the direction similarity and the intensity similarity , according to formula (1), the determined combined similarity of the two sequences can be calculated.

[0048] As an alternative embodiment, when the matching quality index is larger, the direction weight coefficient is larger and the intensity weight coefficient is smaller; and the sum of the direction weight coefficient and the intensity weight coefficient is equal to 1.

[0049] It can be understood that the sum of the direction weight coefficient and the intensity weight coefficient is equal to 1, while the specific values of the direction weight coefficient and the intensity weight coefficient need to be determined according to the matching quality index.

[0050] Specifically, it is determined according to formula (2): (2) Wherein, is the matching quality index, and the value range is .

[0051] In an alternative embodiment, according to formula (2), it can be seen that a segmented dynamic adjustment of the weight coefficient pair is adopted. Specifically, is used as a reference. At this time, the matching quality is average, and a relatively balanced weight distribution ratio can be adopted, that is, the direction weight coefficient is 0.3, and the intensity weight coefficient is 0.7.

[0052] Taking as a reference, when the matching quality index , it indicates that the matching quality is relatively high, indicating that the geomagnetic field characteristics of the geomagnetic matching area are obvious. At this time, the direction similarity is more reliable, and the direction weight coefficient is appropriately increased.

[0053] When the matching quality index , it indicates that the matching quality is poor, indicating that the geomagnetic field characteristics of the geomagnetic matching area are not obvious. At this time, the intensity feature is more reliable, and the intensity weight coefficient can be appropriately increased.

[0054] It should be noted that the above specific values are examples of an alternative embodiment. When setting the dynamically adjusted direction weight coefficient and the intensity weight coefficient , it can be set according to the strategy that the larger the matching quality index, the larger the direction weight coefficient and the smaller the intensity weight coefficient.

[0055] In addition, it should be noted that the direction weight coefficient and the intensity weight coefficient are not only related to the value of the matching quality index , but also related to factors such as the spatial distribution characteristics of the geomagnetic matching area, noise, the motion state of the carrier, and the geomagnetic gradient characteristics of the matching area.

[0056] Specifically, when the geomagnetic field distribution is relatively uniform, the direction information is more reliable. At this time, the direction weight coefficient When the local magnetic field is unevenly distributed, the intensity information is more reliable, and the intensity weight coefficient can be appropriately increased. .

[0057] Since noise has a great influence on directional information, in an optional embodiment, when the measured noise is large, the directional weight coefficient can be appropriately reduced. On the contrary, when the noise is small, the directional weight coefficient can be appropriately increased. .

[0058] When the carrier's motion state is stable, the attitude measurement is more accurate. At this time, the direction weight coefficient can be appropriately increased. When the carrier moves violently, that is, when it is unstable, the intensity weight coefficient can be appropriately increased. .

[0059] When the geomagnetic gradient is large, the intensity weight coefficient can be appropriately increased. , in order to make full use of the intensity change information. When the geomagnetic gradient is small, appropriately increase the directional weight coefficient , to enhance the role of directional information.

[0060] Therefore, the geomagnetic contour matching method provided in the embodiment of the present application dynamically adjusts the direction weight coefficient and the intensity weight coefficient according to the matching quality index, further improving the matching accuracy of the geomagnetic contour and thus improving the navigation accuracy.

[0061] Figure 3 A schematic flow chart of a geomagnetic contour matching method provided in another embodiment of the present application, as an optional embodiment, such as Figure 3 As shown, the direction similarity, intensity similarity and matching quality index of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence are determined, including: S30: determining direction similarity and intensity similarity based on the cosine distance and normalized Euclidean distance of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence, respectively; In an optional embodiment, the directional consistency of two geomagnetic vector sequences can be quantified by cosine similarity. and the reference geomagnetic vector sequence The cosine distance determines the direction similarity , the specific calculation formula is formula (3): (3) Among them, the measured geomagnetic vector sequence By vector Composition, reference geomagnetic vector sequence By vector constitute, For vector The cosine similarity of the sum vector , where is the sequence length. And it is calculated according to formula (4): (4) Among them, is the cosine similarity of vector and vector , is the dot product of vector and vector , is the Euclidean norm of vector , is the Euclidean norm of vector .

[0062] In addition, in another alternative embodiment, the intensity consistency of two geomagnetic vector sequences can be quantified by the normalized Euclidean distance. Therefore, specifically, the intensity similarity can be determined according to the normalized Euclidean distance between the measured geomagnetic vector sequence and the reference geomagnetic vector sequence , and the specific calculation formula is formula (5): (5) Among them, is the Euclidean distance between vector and vector , is the Euclidean norm of vector , is the Euclidean norm of vector .

[0063] Thus, the direction similarity and the intensity similarity can be calculated according to formulas (3) to (5).

[0064] S31: Obtain the preset direction similarity threshold and intensity similarity threshold; S32: Determine the direction quality component and intensity quality component according to the direction similarity threshold and intensity similarity threshold; In an alternative embodiment, when determining the matching quality index , it is necessary to first determine the roles of the direction information and intensity information in the matching process, that is, to determine the direction quality component and intensity quality component. The direction quality component is used to characterize the matching quality of the sequence in terms of direction, and the intensity quality component is used to characterize the matching quality of the sequence in terms of intensity.

[0065] In a specific embodiment, the direction quality component and the intensity quality component can be determined according to the direction similarity threshold and the intensity similarity threshold. Specifically, the direction quality component is determined according to formula (6), and the intensity quality component is determined according to formula (7): (6) (7) Wherein, is the direction quality component, is the intensity quality component, is the direction similarity threshold, is the intensity similarity threshold.

[0066] In an alternative embodiment, the direction similarity threshold can be set to 0.85, and the intensity similarity threshold can be set to 0.15.

[0067] S33: Determine the matching quality index according to the direction quality component and the intensity quality component; Furthermore, in an alternative embodiment, according to the direction quality component and the intensity quality component , the matching quality index is determined. Specifically, the formula is formula (8): (8) Wherein, is the quality component weight coefficient, which is used to determine the proportion of the direction quality component and the intensity quality component in calculating the matching quality index . In an alternative embodiment, the initial default value of the quality component weight coefficient is 0.4.

[0068] It can be understood that the quality component weight coefficient determines the relative contributions of the direction quality component and the intensity quality component in the matching quality index . When the direction information is considered more reliable or important, the value of the quality component weight coefficient can be increased, so that the direction quality component has a greater impact on the matching quality index . When the intensity information is considered more reliable or important, the value of the quality component weight coefficient can be decreased, so that the intensity quality component has a greater impact on the matching quality index .

[0069] In another alternative embodiment, the magnitude of the quality component weight coefficient is also related to the geomagnetic field characteristics of the geomagnetic matching region. Specifically, in a region where the magnetic field direction changes significantly but the intensity changes little, a relatively high quality component weight coefficient value can be set to rely more on the direction information for matching. In a region where the magnetic field intensity changes significantly but the direction changes little, a relatively low quality component weight coefficient value can be set to rely more on the intensity information for matching.

[0070] In still another alternative embodiment, the magnitude of the quality component weight coefficient is also related to the noise characteristics of the geomagnetic sensor. If the noise of the direction sensor is large, it may reduce the quality component weight coefficient value to reduce the influence of direction error on the matching quality. If the noise of the intensity sensor is large, it may increase the quality component weight coefficient value to reduce the influence of intensity error on the matching quality.

[0071] In a specific embodiment, through experience and experimental data, it is determined that the default value of the set quality component weight coefficient can be 0.4. However, in practical applications, the quality component weight coefficient can be dynamically adjusted according to the specific application scenario and data characteristics to obtain a better matching effect. For example, in an alternative embodiment, the optimal quality component weight coefficient can be determined by comparing the matching accuracy and robustness under different quality component weight coefficient

[0072] conditions. Specifically, the setting of the quality component weight coefficient is designed to balance the roles of direction and intensity information in the matching process, and the specific value of the quality component weight coefficient

[0073] can be adjusted according to the geomagnetic field characteristics, sensor performance, and actual application requirements.

[0074] Based on the above embodiments, in order to further ensure the real-time performance of geomagnetic matching, in an optional embodiment, an early termination mechanism is set to reduce the amount of calculation and improve the matching efficiency.

[0075] Specifically, the preset iteration conditions include at least one of the following: there is only one remaining candidate point, a given number of iterations is reached, and the difference between the maximum value and the second maximum value of the combined similarity is greater than a preset difference.

[0076] It can be understood that during the normal matching process, the search space resolution is continuously reduced to obtain the best candidate point. When the iteration reaches the given number of iterations, that is, when iterating to the last layer of the pyramid, the maximum value of the combined phase velocity is used as the matching positioning point. In order to improve the matching efficiency and ensure the real-time performance of the matching, an early termination mechanism is added.

[0077] Specifically, in an optional embodiment, the early termination mechanism includes: in any iteration, if the combined similarity corresponding to a candidate point is much greater than the combined similarities of other candidate points, it indicates that this candidate point can be used as the matching positioning point. At this time, regardless of which iteration it is, the iteration ends, and the candidate point corresponding to the maximum combined similarity is used as the matching positioning point.

[0078] In another optional embodiment, the early termination mechanism includes: in any iteration, if there is only one remaining candidate point, the iteration ends, and this remaining candidate point is used as the matching positioning point.

[0079] Specifically, in still another optional embodiment, it may include the above two early termination mechanisms. One early termination mechanism is that if there exists , such that , where is the similarity value of candidate point . The other early termination mechanism is that if , is the set of candidate points. That is, when there is only one remaining candidate point, this remaining candidate point is the matching positioning point.

[0080] That is to say, in an optional embodiment, during the loop iteration process, the preset iteration conditions include three. Specifically, there is only one remaining candidate point, a given number of iterations is reached, and the difference between the maximum value and the second maximum value of the combined similarity is greater than the preset difference. As long as any one of the three conditions is met, the iteration loop ends.

[0081] Thus, the geomagnetic profile matching method provided by the embodiments of the present application further ensures the matching efficiency and the real-time performance of the matching by setting the early termination mechanism.

[0082] In an alternative embodiment, the search space resolution includes a search area and a search step size. Obtaining the search space resolution for searching the geomagnetic matching area includes: Obtaining a preset reference step size, the motion speed of the carrier, the drift error of the inertial navigation system, and the geomagnetic characteristics of the geomagnetic matching area; Determining the search step size according to the preset reference step size and the motion speed; wherein, the greater the motion speed, the greater the search step size; Determining the search area according to the drift error; wherein, the greater the drift error, the greater the search area; the more obvious the geomagnetic characteristics, the greater the search area.

[0083] It can be understood that the search space resolution is used to determine the search range and search accuracy for the geomagnetic matching area. In an alternative embodiment, the search space resolution may include a search area and a search step size.

[0084] In a specific embodiment, the search step size is related to the motion speed of the carrier. To further ensure the search accuracy and matching accuracy, the initial search step size can be determined according to the preset reference step size and the motion speed of the carrier. The specific calculation formula is formula (9): (9) Wherein, is the search step size, is the preset reference step size, is the motion speed of the carrier. In an alternative embodiment, the preset reference step size can be set to 100 meters (m).

[0085] It can be understood that when the motion speed is greater, in order to ensure the search real-time performance, the search step size is greater. However, it should be noted that when adjusting the search step size according to the motion speed, the increase amplitude cannot be too large, otherwise the matching accuracy will be reduced. Therefore, in an alternative embodiment, a linear growth function can be used to adjust the search step size. For example, for every 100 m / s increase in speed, the search step size is increased by 10%. Thus, a balance is achieved between real-time performance and accuracy.

[0086] It can be understood that the search step size is the initially obtained search step size, that is, the step size condition for the first grid search. After the search step size , for each iterative search, a more refined search can be achieved by reducing the search step size . Specifically, in the pyramid search strategy, the top layer is the search step size , and thereafter, for each iterative loop, that is, when searching to the next lower layer of the pyramid, the search step size can be reduced according to a certain ratio.

[0087] Specifically, in an alternative embodiment, the search step size for the next iteration can be a preset multiple of the search step size of the previous iteration, and the preset multiple is less than 1. For example, it can be one-third of the search step size of the previous iteration.

[0088] In addition to determining the search step size, it is also necessary to determine the search area. The search area is used to represent the search range and is related to the drift error of the inertial navigation system, the geomagnetic characteristics of the geomagnetic matching area, etc. To ensure the search accuracy, an initial search area can be set according to the drift error of the inertial navigation system and the geomagnetic characteristics of the geomagnetic matching area.

[0089] Specifically, the drift error of the inertial navigation system is related to the gyro zero bias, the accelerometer zero bias, and the operating duration of the inertial navigation system. When the gyro zero bias is larger, the drift error of the inertial navigation system is larger, and the search area is larger. When the accelerometer zero bias is larger, the drift error of the inertial navigation system is larger, and the search area is larger. In addition, when the operating duration of the inertial navigation system is longer, the accumulated error is larger, and the corresponding search area is larger at this time.

[0090] In another alternative embodiment, when the geomagnetic characteristics are more obvious, the search area can be reduced in duration, and when the geomagnetic characteristics are less obvious, the search area can be appropriately enlarged.

[0091] In addition, in addition to the drift error of the inertial navigation system and the geomagnetic characteristics of the geomagnetic matching area affecting the setting of the search area, the search area is also related to the motion characteristics of the carrier, where the motion characteristics include the motion speed and the maneuverability. Specifically, when the motion speed of the carrier is larger, a larger search area is required to cover more possible positions. When the maneuverability is stronger, a larger search area is required to adapt to turning.

[0092] Therefore, the geomagnetic profile matching method provided by the embodiments of the present application, based on the setting mechanism of the dynamic search step size and the search area, ensures the matching of the search efficiency and the motion characteristics of the carrier, and further guarantees the matching real-time performance.

[0093] In an alternative embodiment, the geomagnetic profile matching method provided by the present application further includes: Obtaining the influence factors for a given number of iterations; wherein, the influence factors include the motion characteristic parameters of the carrier, the spatial distribution characteristic parameters of the geomagnetic matching area, and the matching real-time instruction; Determining the given number of iterations according to the influence factors; wherein, when the motion characteristic parameters characterize that the motion of the carrier is more complex, the given number of iterations is larger; when the spatial distribution characteristic parameters characterize that the geomagnetic distribution is more complex, the given number of iterations is larger; when the matching real-time instruction characterizes that the real-time requirement is higher, the given number of iterations is smaller.

[0094] It can be understood that in addition to the search area and search step size affecting the matching accuracy, the number of loop iterations, that is, the given number of iterations, which is also the number of pyramid layers, also has an important impact on the matching accuracy. Different matching requirements, different carrier motion characteristics, different spatial distribution characteristics of the geomagnetic matching area, and other factors will affect the setting of the given number of iterations.

[0095] Therefore, in an optional embodiment, in order to obtain the optimal given number of iterations and thus improve the matching accuracy, the current given number of iterations is determined according to the influencing factors of the given number of iterations. Specifically, when the motion characteristic parameters of the carrier indicate more complex motion, the given number of iterations is larger, that is, the number of pyramid layers is more, and the obtained matching accuracy is higher. Among them, the motion characteristic parameters of the carrier can include but are not limited to acceleration, turning frequency, and turning amplitude.

[0096] When the spatial distribution characteristic parameters indicate more complex geomagnetic distribution, the given number of iterations is larger, that is, the number of pyramid layers is more, and the obtained matching accuracy is higher. When the matching real-time instruction indicates a higher current real-time requirement for navigation, the given number of iterations should be set smaller to ensure real-time performance.

[0097] Table 1 is a schematic table showing the corresponding relationship between a search parameter, update frequency, and matching accuracy provided by an embodiment of the present application. For ease of understanding, the following will be described in conjunction with Table 1. In Table 1, the search parameters include a coarse search step size, a fine search step size, a combined similarity threshold, and a given number of iterations. The update frequency represents the matching real-time performance, and the matching accuracy is measured using the root mean square error distance (RMES).

[0098] Table 1 Corresponding relationship table of search parameters, update frequency, and matching accuracy

[0099] In an optional embodiment, after a real matching experiment is carried out based on the geomagnetic profile matching method provided by the present application, the data shown in Table 1 is obtained. According to Table 1, it can be seen that the number of pyramid layers (that is, the given number of iterations) has a certain impact on the matching accuracy. When reducing the number of layers, for example, based on the reference combination, the pyramid is reduced from 3 layers to 2 layers, that is, the number of iterations is reduced from 3 times to 2 times, the update frequency is increased from 2.87 Hertz (Hz) to 3.68 Hz. However, the RMSE increases from 52.48 m to 58.70 m, that is, the matching accuracy decreases. When the number of iterations is increased from 3 times to 4 times, that is, the number of pyramid layers is increased from 3 layers to 4 layers, the RMSE is reduced from 52.48 m to 52.28 m, but the update frequency is reduced from 2.87 Hz to 2.39 Hz.

[0100] In addition, according to Table 1, it can be seen that the coarse search step size has the greatest impact on the matching performance. Specifically, increasing the coarse search step size can improve the update frequency, but it will significantly reduce the positioning accuracy. For example, based on the benchmark combination, when the coarse search step size increases from 100m to 200m, the update frequency increases from 2.87Hz to 4.06Hz, but the RMSE only slightly increases to 54.46m. However, when the coarse search step size further increases to 300m, although the update frequency remains at 4.04Hz, the RMSE sharply rises to 154.02m, that is, the matching accuracy significantly decreases. The combined similarity threshold has a relatively small impact on the matching performance. Changing the threshold (for example, from 0.7 to 0.9) has no effect on the RMSE (both are 52.48m) and has a slight effect on the update frequency (from 2.92Hz to 2.82Hz).

[0101] In summary, in an alternative embodiment, in order to balance both the matching real-time performance and the matching accuracy, the given number of iterations can be set to 3 times, that is, the number of pyramid layers is set to 3 layers.

[0102] Figure 4(a) is a schematic diagram of a matching trajectory provided by an embodiment of the present application. Figure 4(b) is a schematic diagram of another matching trajectory provided by an embodiment of the present application. Figure 4(c) is a schematic diagram of still another matching trajectory provided by an embodiment of the present application. To make the technical solution of the present application clearer to those skilled in the art, the following will be described in conjunction with Figures 4(a) to 4(c), where the dashed line is the true motion trajectory of the carrier, and the solid line is the matching trajectory obtained by the geomagnetic contour matching method provided by the present application.

[0103] In an alternative embodiment, when navigating through the geomagnetic contour matching method provided by the present application to obtain the carrier motion trajectory, as can be seen from Figures 4(a) to 4(c), the technical solution provided by the present application has a good matching effect on different types of motion trajectories.

[0104] Among them, as shown in Figure 4(a), a diagonal straight-line trajectory is matched. As shown in Figure 4(b), a curved trajectory with a radius of curvature of 25km is matched. As shown in Figure 4(c), a composite trajectory including a straight-line segment and a turning segment is matched.

[0105] Therefore, the geomagnetic contour matching method provided by the present application has high adaptability and reliability under different types of trajectories, realizing high-precision and high-real-time geomagnetic matching navigation.

[0106] In the above embodiment, the geomagnetic contour matching method has been described in detail. The present application also provides an embodiment corresponding to a geomagnetic contour matching device.

[0107] Figure 5The following is a schematic structural diagram of a geomagnetic contour matching device provided by an embodiment of the present application. As Figure 5 shown, the device includes: A first acquisition module 50, configured to acquire a measured geomagnetic vector sequence and a search space resolution for searching a geomagnetic matching region; A reference sequence acquisition module 51, configured to perform grid search on the geomagnetic matching region under the condition of the search space resolution to obtain points to be matched; and generate a reference geomagnetic vector sequence based on the points to be matched; A candidate point screening module 52, configured to determine the combined similarity in direction and intensity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; and screen out candidate points corresponding to a combined similarity greater than a similarity threshold; A processing module 53, configured to reduce the search space resolution, and repeatedly call the reference sequence acquisition module and the candidate point screening module until a preset iteration condition is met. The preset iteration condition includes reaching a given number of iterations; A matching positioning point acquisition module 54, configured to use the candidate point corresponding to the maximum combined similarity obtained after the processing module as the matching positioning point.

[0108] In addition, the geomagnetic contour matching device provided by an embodiment of the present application further includes: A first determination module, configured to determine the direction similarity, intensity similarity, and matching quality index between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; A weight coefficient pair determination module, configured to determine a weight coefficient pair including a direction weight coefficient and an intensity weight coefficient according to the matching quality index; A combined similarity determination module, configured to determine the combined similarity according to the weight coefficient pair, direction similarity, and intensity similarity.

[0109] A third determination module, configured to respectively determine the direction similarity and intensity similarity based on the cosine distance and normalized Euclidean distance between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; A similarity threshold acquisition module, configured to acquire a preset direction similarity threshold and intensity similarity threshold; A second determination module, configured to determine a direction quality component and an intensity quality component according to the direction similarity threshold and the intensity similarity threshold; A matching quality index determination module, configured to determine the matching quality index according to the direction quality component and the intensity quality component.

[0110] A second acquisition module, configured to acquire a preset reference step size, the movement speed of the carrier, the drift error of the inertial navigation system, and the geomagnetic characteristics of the geomagnetic matching region; A search step determination module, configured to determine a search step according to a preset reference step and a motion speed; wherein, the greater the motion speed, the greater the search step. A search area determination module, configured to determine a search area according to a drift error; wherein, the greater the drift error, the greater the search area; and the more obvious the geomagnetic feature, the greater the search area.

[0111] An influence factor acquisition module, configured to acquire influence factors for a given number of iterations; wherein, the influence factors include motion characteristic parameters of the carrier, spatial distribution characteristic parameters of the geomagnetic matching area, and a matching real-time instruction. A given number of iterations determination module, configured to determine a given number of iterations according to the influence factors; wherein, the more complex the motion of the carrier characterized by the motion characteristic parameters, the greater the given number of iterations; the more complex the geomagnetic distribution characterized by the spatial distribution characteristic parameters, the greater the given number of iterations; and the higher the real-time requirement characterized by the matching real-time instruction, the smaller the given number of iterations.

[0112] Figure 6 The following is a schematic structural diagram of a geomagnetic profile matching device provided in another embodiment of the present application. As Figure 6 shown, the geomagnetic profile matching device includes: a memory 60, configured to store a computer program. A processor 61, configured to implement the steps of the geomagnetic profile matching method mentioned in the above embodiment when executing the computer program.

[0113] The geomagnetic profile matching device provided in this embodiment may include, but is not limited to, a laptop computer or a desktop computer, etc.

[0114] Among them, the processor 61 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 61 may be implemented in at least one of the following hardware forms: Digital Signal Processor (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 61 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the wake state, also known as the Central Processing Unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 61 may be integrated with a Graphics Processing Unit (GPU), and the GPU is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 61 may further include an Artificial Intelligence (AI) processor, which is used to process computational operations related to machine learning.

[0115] The memory 60 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 60 may further include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash storage devices. In this embodiment, the memory 60 is at least used to store the following computer program 601. After the computer program is loaded and executed by the processor 61, it can implement the relevant steps of the geomagnetic profile matching method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 60 may further include an operating system 602 and data 603, etc., and the storage method may be transient storage or permanent storage. Among them, the operating system 602 may include Windows, Unix, Linux, etc. The data 603 may include, but is not limited to, the relevant data involved in the geomagnetic profile matching method.

[0116] In some embodiments, the geomagnetic profile matching device may further include a display screen 62, an input / output interface 63, a communication interface 64, a power supply 65, and a communication bus 66.

[0117] Those skilled in the art can understand that Figure 6 the structure shown in

[0118] The geomagnetic profile matching device provided by the embodiments of the present application includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the geomagnetic profile matching method in the above embodiments.

[0119] It should be noted that although the operations are depicted in a specific order in the drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or requiring all of the illustrated operations to be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of the various system modules and components in the above embodiments should not be construed as required in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Claims

1. A geomagnetic contour matching method, characterized in that: The method comprises: S10: obtaining the measured geomagnetic vector sequence and the search space resolution of the search geomagnetic matching area; S11: performing a grid search on the geomagnetic matching area under the search space resolution condition to obtain points to be matched; and generating a reference geomagnetic vector sequence based on the points to be matched; S12: determining the combined similarity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence in terms of direction and intensity; and screening out candidate points corresponding to the combined similarity being greater than a similarity threshold; S13: reducing the search space resolution, and repeatedly performing steps S11 to S13 until a preset iteration condition is met, wherein the preset iteration condition includes reaching a given number of iterations; S14: taking the candidate point corresponding to the combination with the largest similarity obtained after step S13 as the matching positioning point.

2. The geomagnetic contour matching method according to claim 1, characterized in that: Determining the combined similarity between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence in terms of direction and intensity includes: Determining the direction similarity, intensity similarity and matching quality index of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence; Determining a weight coefficient pair including a direction weight coefficient and an intensity weight coefficient according to the matching quality indicator; The combined similarity is determined according to the weight coefficient pair, the direction similarity and the intensity similarity.

3. The geomagnetic contour matching method according to claim 2, characterized in that: When the matching quality index is larger, the direction weight coefficient is larger and the intensity weight coefficient is smaller; and the sum of the direction weight coefficient and the intensity weight coefficient is equal to 1.

4. The geomagnetic contour matching method according to claim 2, characterized in that: The determining of the direction similarity, intensity similarity and matching quality index of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence comprises: Based on the cosine distance and the normalized Euclidean distance between the reference geomagnetic vector sequence and the measured geomagnetic vector sequence, respectively determining the direction similarity and the intensity similarity; Obtaining a preset direction similarity threshold and intensity similarity threshold; Determining a direction quality component and an intensity quality component according to the direction similarity threshold and the intensity similarity threshold; The matching quality index is determined according to the directional quality component and the intensity quality component.

5. The geomagnetic contour matching method according to claim 1, characterized in that: The preset iteration condition includes at least one of the following: there is one candidate point remaining, the given number of iterations is reached, and the difference between the maximum value and the second largest value of the combined similarity is greater than a preset difference.

6. The geomagnetic contour matching method according to claim 1, characterized in that: The search space resolution includes the search area and the search step size. Obtaining the search space resolution of the search geomagnetic matching area includes: Acquiring a preset reference step length, a moving speed of the carrier, a drift error of the inertial navigation system, and geomagnetic characteristics of the geomagnetic matching area; Determining the search step length according to the preset reference step length and the movement speed; wherein, when the movement speed is greater, the search step length is greater; The search area is determined according to the drift error; wherein, when the drift error is larger, the search area is larger; when the geomagnetic feature is more obvious, the search area is larger.

7. The geomagnetic contour matching method according to claim 1 or 5, characterized in that: The method further comprises: Obtaining the influencing factors of the given number of iterations; wherein the influencing factors include the motion characteristic parameters of the carrier, the spatial distribution characteristic parameters of the geomagnetic matching area and the matching real-time instructions; The given number of iterations is determined according to the influencing factor; wherein, when the motion characteristic parameter represents that the motion of the carrier is more complex, the given number of iterations is greater; when the spatial distribution characteristic parameter represents that the geomagnetic distribution is more complex, the given number of iterations is greater; and when the matching real-time instruction represents a higher real-time requirement, the given number of iterations is smaller.

8. A geomagnetic profile matching device, characterized in that: The device comprises: The first acquisition module is used to acquire the measured geomagnetic vector sequence and the search space resolution of the geomagnetic matching area; A reference sequence acquisition module, used to perform a grid search on the geomagnetic matching area under the search space resolution condition to obtain points to be matched; and to generate a reference geomagnetic vector sequence based on the points to be matched; A candidate point screening module is used to determine the combined similarity of the reference geomagnetic vector sequence and the measured geomagnetic vector sequence in terms of direction and intensity; and screen out candidate points corresponding to the combined similarity being greater than a similarity threshold; A processing module, used to reduce the search space resolution and repeatedly call the reference sequence acquisition module and the candidate point screening module until a preset iteration condition is met, wherein the preset iteration condition includes reaching a given number of iterations; The matching positioning point acquisition module is used to use the candidate point corresponding to the combination with the largest similarity obtained by the processing module as the matching positioning point.

9. A geomagnetic profile matching device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the program, the steps of the geomagnetic contour matching method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the geomagnetic contour matching method described in any one of claims 1 to 7 are implemented.

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