A two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints

Abstract

The present application is applicable to the field of positioning and navigation technology, and provides a two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints. Compared with traditional methods, the present application screens out candidate fingerprint sequences that meet the constraints in the geomagnetic reference library based on motion feature constraints and geomagnetic field periodic change feature constraints; matches and calculates the real-time geomagnetic sequence with the candidate fingerprint sequence to obtain the candidate fingerprint sequence with the highest similarity, extracts the position information in the candidate fingerprint sequence with the highest similarity, and the moving carrier completes the established route to obtain the positioning result of the moving carrier on the established route. The complex two-dimensional matching positioning problem is converted into a one-dimensional path matching optimization problem under multi-feature parameter constraints, taking into account the sequence change trend and matching efficiency, thereby improving positioning accuracy and saving more computing power. It is particularly suitable for high-precision autonomous positioning needs in GNSS-denied scenarios such as underground spaces and indoor environments.

Description

Technical Field

[0001] The present application belongs to the field of positioning and navigation technology, and in particular relates to a two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints. Background Art

[0002] As a passive autonomous positioning and navigation technology, geomagnetic positioning and navigation does not rely on external devices such as satellites. Instead, it utilizes the inherent characteristics of the Earth's magnetic field for positioning and navigation, fundamentally solving the positioning problem in GNSS (Global Navigation Satellite System)-denied scenarios. Compared to other traditional positioning methods, geomagnetic positioning and navigation does not suffer from time-accumulated errors, such as inertial navigation. It offers significant advantages such as global uniqueness, strong environmental adaptability, low power consumption, and low cost. In recent years, it has demonstrated its unique value in areas such as autonomous driving, indoor positioning and navigation, and military applications.

[0003] Geomagnetic matching positioning uses a high-precision magnetometer aboard a moving vehicle to measure the geomagnetic field and match it against a pre-prepared geomagnetic map to determine the vehicle's real-time position. Traditional techniques use single-point geomagnetic data matching. However, the geomagnetic field strength at different locations can be highly similar, resulting in low discrimination and a high degree of mismatching, leading to low positioning accuracy. Currently, the mainstream geomagnetic positioning method utilizes geomagnetic sequences with magnetic field variations, collected during the vehicle's continuous motion. These sequences contain the characteristics of geomagnetic field variations and offer rich geomagnetic information, effectively mitigating the impact of low-discrimination environments. Due to the directional nature of these sequences, using geomagnetic sequence matching alone can only achieve high-precision, real-time positioning in one-dimensional scenarios. In practical applications, positioning or navigation often requires two- or even three-dimensional environments. When applied to two-dimensional scenarios, geomagnetic sequence matching lacks angular constraints, resulting in a large matching search range, increased computational complexity, and significant reductions in positioning efficiency. Furthermore, when positioning over large areas, similar geomagnetic sequence features within the geomagnetic map can easily lead to mismatching, significantly reducing accuracy. Summary of the Invention

[0004] The embodiment of the present application provides a two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints to solve the problem of severe reduction in positioning accuracy when geomagnetic sequence matching is applied to a two-dimensional scenario.

[0005] To achieve the above objectives, this application provides the following technical solutions:

[0006] The present application provides a two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints, comprising the following steps:

[0007] Construct a two-dimensional geomagnetic reference map based on measured data, extract magnetic field intensity distribution curves on different paths from the two-dimensional geomagnetic reference map, and form a geomagnetic reference library including spatial coordinates and geomagnetic field intensity;

[0008] Extract the waveform characteristics and spectrum characteristics of the magnetic field intensity distribution curve, and obtain the periodic characteristics of the geomagnetic field on different paths based on the waveform characteristics and spectrum characteristics;

[0009] Collect the real-time geomagnetic sequence of the moving carrier, use the speed and heading information of the moving carrier as motion feature constraints, and judge whether the magnetic field distribution in the current direction of movement of the moving carrier has geomagnetic field periodicity characteristics from the geomagnetic field periodicity characteristics on different paths based on the heading information. If so, the geomagnetic field periodic change feature constraint is triggered;

[0010] According to the motion feature constraints and the periodic change feature constraints of the geomagnetic field, the candidate fingerprint sequences that meet the constraints in the geomagnetic reference library are screened out;

[0011] The real-time geomagnetic sequence is matched with the candidate fingerprint sequence to obtain the candidate fingerprint sequence with the highest similarity, and the position information in the candidate fingerprint sequence with the highest similarity is extracted. The moving carrier completes the predetermined route and obtains the positioning result of the moving carrier on the predetermined route.

[0012] Furthermore, if there is no periodic feature of the geomagnetic field, candidate fingerprint sequences that meet the constraint conditions are screened out from the geomagnetic reference library based on the motion feature constraint.

[0013] Furthermore, the two-dimensional geomagnetic reference map covers the area to be positioned, and the different paths include: horizontal paths and vertical paths extracted at equal intervals along the X-axis and Y-axis directions; parallel oblique paths extracted from the lower left corner to the upper right corner of the two-dimensional geomagnetic reference map and translated and extended at equal intervals in the direction of the main diagonal and the normal of the main diagonal.

[0014] Furthermore, the periodic variation characteristic constraint of the geomagnetic field is to limit the matching range to a specific range, which is expressed as: , For the matching range, is the position of the motion carrier at the previous moment, To match the allowable error, It is the distance corresponding to the change of the Earth's magnetic field within one cycle.

[0015] Furthermore, the distance corresponding to the change in the geomagnetic field within one cycle is determined by the geomagnetic field change cycle. It is obtained by multiplying the velocity of the carrier during mapping.

[0016] Furthermore, the motion feature constraint includes limiting the matching search area to a circular area centered at the previous positioning point through speed constraint; and focusing the matching search area on the possible motion direction through heading information constraint, narrowing the search range to a fan-shaped area.

[0017] Furthermore, the final positioning coordinate range of the motion feature constraint is expressed as:

[0018] ,

[0019] in, To predict the location, Position the location at the last moment. is the time step, To allow the minimum speed, To allow maximum speed, is the heading angle at the previous moment, is the maximum allowable deflection angle.

[0020] Furthermore, the highest similarity means that the cumulative distance between the real-time geomagnetic sequence and the candidate fingerprint sequence is the smallest.

[0021] Furthermore, a dynamic time warping algorithm is used to calculate the cumulative distance between the real-time geomagnetic sequence and the candidate fingerprint sequence.

[0022] Compared with the prior art, the embodiments of the present application have at least the following beneficial effects:

[0023] This application effectively solves the key technical challenges of geomagnetic matching and positioning in a two-dimensional environment by constructing multi-dimensional feature parameter constraints. This approach not only considers the influence of periodic changes in geomagnetic field intensity during the matching process, but also takes into account the kinematic characteristics of the carrier. This improves the problem of traditional positioning methods being limited to one-dimensional regions, effectively avoiding the high mismatch rate and large computational complexity of sequence matching in two-dimensional space, and achieving global optimal matching of continuous trajectories in two-dimensional space.

[0024] This application transforms the complex two-dimensional matching and positioning problem into a one-dimensional path matching optimization problem under multi-feature parameter constraints, taking into account the changing trend of the sequence and the matching efficiency, improving the positioning accuracy and saving more computing power. It is particularly suitable for the high-precision autonomous positioning needs in GNSS-denied scenarios such as underground spaces and indoor environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flowchart of a two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints provided in an embodiment of the present application.

[0026] Figure 2 This is a module block diagram of the two-dimensional geomagnetic matching positioning system in an embodiment of the present application;

[0027] Figure 3 Schematic diagram of a two-dimensional geomagnetic reference map in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0029] The specific implementation of this application is described in detail below in conjunction with specific embodiments.

[0030] The flowchart of the two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints in this application is as follows: Figure 1 As shown,

[0031] A two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints, comprising:

[0032] S1 constructs a two-dimensional geomagnetic reference map based on measured data, extracts magnetic field intensity distribution curves on different paths from the two-dimensional geomagnetic reference map, and forms a geomagnetic reference library including spatial coordinates and geomagnetic field intensity;

[0033] Step S1 involves offline construction of a geomagnetic reference library and a two-dimensional geomagnetic reference map. Measured data refers to geomagnetic data collected in the test area by a non-magnetic vehicle equipped with a high-precision magnetometer. The collected geomagnetic data is preprocessed and spatially mapped to construct a two-dimensional geomagnetic reference map that meets actual needs. This map reflects the spatial distribution of geomagnetic field elements within the test area and provides contour maps of the values ​​of the Earth's basic magnetic field elements and their distribution and variation on the Earth's surface. Geomagnetic field data is obtained through field measurements, and then a gridded geomagnetic reference map is constructed using interpolation methods. Interpolation methods include, but are not limited to, cubic spline interpolation, Kriging interpolation, and Kriging interpolation based on the particle swarm optimization (PSO) algorithm.

[0034] Extract the magnetic field intensity distribution curves on different paths from the two-dimensional geomagnetic reference map, see Figure 3 The different paths in the 2D geomagnetic reference map shown here are horizontal and vertical paths extracted at equal intervals along the X and Y axes. Parallel oblique paths are extracted from the main diagonal and its normal direction, extending the main diagonal at equal intervals, from the lower left corner to the upper right corner of the 2D geomagnetic reference map. The path spacing is determined by the size of the geomagnetic reference map.

[0035] The geomagnetic reference library is a database that stores geomagnetic field characteristic data, which includes spatial coordinates and geomagnetic field intensity.

[0036] S2 extracts the waveform characteristics and spectrum characteristics of the magnetic field intensity distribution curve, and obtains the periodic characteristics of the geomagnetic field on different paths based on the waveform characteristics and spectrum characteristics;

[0037] The purpose of analyzing the waveform characteristics and spectral characteristics of the magnetic field intensity distribution curve is to obtain the periodic characteristics of the geomagnetic field on different paths, which is used to study the variation pattern of the magnetic field within the extraction area. This periodic characteristic of the geomagnetic field is then used as a constraint in positioning.

[0038] Waveform feature extraction mainly extracts key information from time domain data to describe the shape and characteristics of the data. Waveform features include peaks and valleys, mean and variance of the signal; waveform parameters such as period, frequency, amplitude, phase, energy and power of the signal can be achieved using conventional methods.

[0039] Spectral feature extraction is to analyze signals from the frequency domain. Fourier transform can be used to convert data from the time domain to the frequency domain to extract the frequency components of the data, or short-time Fourier transform can be used to divide the data into multiple short segments and perform Fourier transform on each short segment to analyze the time-frequency characteristics of the data; or wavelet basis functions can be used to decompose the data to extract the time-frequency characteristics of the data. Waveform features and spectral characteristics may have periodicity. For periodic spectra, they are discrete and consist of a series of spectral lines. The spectrum of non-periodic signals is continuous and has no obvious periodicity. This periodicity is a periodic characteristic of the geomagnetic field on different paths.

[0040] S3 collects the real-time geomagnetic sequence of the moving carrier, uses the speed and heading information of the moving carrier as motion feature constraints, and determines whether the magnetic field distribution in the current motion direction of the moving carrier has geomagnetic field periodicity characteristics based on the heading information and the geomagnetic field periodicity characteristics on different paths. If so, the geomagnetic field periodic change feature constraint is triggered;

[0041] Starting from step S3, it is the online matching and positioning stage. The tester controls the non-magnetic vehicle equipped with a high-precision magnetometer to collect geomagnetic data in real time along a predetermined trajectory in the test area. Whenever geomagnetic data is collected over a period of time, a real-time geomagnetic sequence is formed. Here, the real-time geomagnetic sequence includes a timestamp and geomagnetic field strength.

[0042] The heading information is compared with the close path in the two-dimensional geomagnetic reference map. From the magnetic field intensity distribution curve of the path, it can be determined whether the magnetic field distribution in the current moving direction of the moving carrier has periodic characteristics of the geomagnetic field.

[0043] S4 selects candidate fingerprint sequences that meet the constraints in the geomagnetic reference library based on the motion feature constraints and the geomagnetic field periodic change feature constraints;

[0044] In step S4, when the presence of periodic geomagnetic field characteristics is determined in step S3, two constraints are applied to filter candidate fingerprint sequences from the geomagnetic reference library. Multiple candidate fingerprint sequences may meet the constraints. A candidate fingerprint sequence refers to multiple different geomagnetic field intensity data with spatial coordinates that meet the constraints.

[0045] S5 matches the real-time geomagnetic sequence with the candidate fingerprint sequence to obtain the candidate fingerprint sequence with the highest similarity, extracts the position information in the candidate fingerprint sequence with the highest similarity, and obtains the positioning result of the moving carrier on the established route after the moving carrier completes the established route.

[0046] Using the dynamic time warping (DTW) algorithm, the real-time geomagnetic sequence collected is matched against candidate fingerprint sequences. The candidate fingerprint sequence with the highest similarity is extracted and determined to be the optimal match. The location information corresponding to the optimal match is then output. This process is repeated until the vehicle has completed the designated route, and the vehicle's positioning results for that route are output.

[0047] In one embodiment, if there is no periodic feature of the geomagnetic field, candidate fingerprint sequences that meet the constraint conditions are screened out from the geomagnetic reference library based on the motion feature constraint.

[0048] In one embodiment, the periodic variation characteristic constraint of the geomagnetic field is to limit the matching range to a specific range, which is expressed as: , For the matching range, is the position of the motion carrier at the previous moment, To match the allowable error, It is the distance corresponding to the change of the Earth's magnetic field within one cycle.

[0049] Earth's magnetic field cycle The distance corresponding to the change in the Earth's magnetic field within one cycle The coupling relationship is modeled as follows: , is the period of geomagnetic field variation, is the carrier movement speed during mapping.

[0050] If the magnetic field in the current moving direction or the nearest moving direction of the moving carrier changes periodically, the periodic change characteristic constraint of the geomagnetic field will be triggered, and the matching range will be Restricted to a specific range.

[0051] When performing geomagnetic positioning, constraints based on the carrier's motion characteristics are added. The onboard motion sensor outputs real-time speed and heading information to dynamically constrain the matching search area. Speed ​​information limits the matching search area to a circular area centered on the previous positioning point. The maximum and minimum speed ranges can be set based on the current situation. The heading information constraint focuses the matching search area on possible motion directions, further narrowing the search range to a sector-shaped area.

[0052] The speed information and heading information work together to form motion constraints. The mathematical form of the final positioning coordinate range is as follows:

[0053] ,

[0054] in, To predict the location, Position the location at the last moment. is the time step, To allow the minimum speed, To allow maximum speed, is the heading angle at the previous moment, is the maximum allowable deflection angle.

[0055] During positioning, the geomagnetic field along the path of the current movement direction may have specific periodic changes. If there are periodic changes, the geomagnetic field periodic change feature constraint is activated to limit the matching range to one cycle of the magnetic field change (the horizontal axis of the geomagnetic reference image time domain waveform is distance). Then, using the movement speed, heading angle and other information of the moving carrier, the motion feature constraint further limits the screening area, selects the path segment with similar movement direction and speed, and finally selects a batch of magnetic fingerprint sequence fragments that meet these conditions as the sequence library to be matched at the current moment. The real-time measured geomagnetic sequence is matched with the screened sequence library to be matched, and the dynamic time warping algorithm is used to calculate the similarity between the two. The calculation formula is:

[0056] ;

[0057] ;

[0058] ;

[0059] ;

[0060] ;

[0061] in, and Indicates the difference between the real-time geomagnetic sequence collected and the candidate sequence in the geomagnetic reference library. and sampling points, Represents the Euclidean distance between the two. When calculating the cumulative distance matrix, we must follow the three principles of boundary, continuity and monotonicity. It represents the Euclidean distance from the first sampling point in the real-time geomagnetic sequence to the first sampling point in the candidate fingerprint sequence in the geomagnetic reference library. Indicates the first The cumulative distance from the sampling point to the first sampling point in the candidate fingerprint sequence, Indicates the distance from the first sampling point in the real-time geomagnetic sequence to the first sampling point in the candidate fingerprint sequence. The cumulative distance of the sampling points, Indicates the real-time geomagnetic sequence The sampling point and the candidate fingerprint sequence The cumulative distance of the sampling points, Indicates the real-time geomagnetic sequence The sampling point and the candidate fingerprint sequence The cumulative distance of the sampling points, Indicates the first The sampling point and the candidate fingerprint sequence The cumulative distance of the sampling points, Indicates the first The sampling point and the candidate fingerprint sequence The cumulative distance of the sampling points, They represent the total length of the real-time geomagnetic sequence and the total length of the candidate fingerprint sequence, respectively.

[0062] Final step-by-step calculation ,until The calculation is completed and the obtained It is the cumulative distance between two geomagnetic sequences, that is, the comparison of their similarity.

[0063] After traversing and calculating the cumulative distance between the collected real-time geomagnetic sequence and the candidate fingerprint sequence, the two geomagnetic sequences with the smallest cumulative distance have the highest similarity. The candidate sequence with the highest similarity is extracted and determined to be the optimal matching sequence. Each time a segment of real-time geomagnetic sequence is collected and matched, a positioning result is output until the positioning is completed. The positioning results of each segment are output as the final positioning trajectory.

[0064] See also Figure 2 The structural block diagram of the two-dimensional geomagnetic matching positioning system shown in the figure is a two-dimensional geomagnetic matching positioning system, comprising:

[0065] A geomagnetic reference data processing module is used to obtain measured data and construct a two-dimensional geomagnetic reference map based on the measured data, extract magnetic field intensity distribution curves on different paths from the two-dimensional geomagnetic reference map, and form a geomagnetic reference library including spatial coordinates and geomagnetic field intensity;

[0066] The feature extraction module is used to extract the waveform characteristics and spectrum characteristics of the magnetic field intensity distribution curve, and obtain the periodic characteristics of the geomagnetic field on different paths based on the waveform characteristics and spectrum characteristics;

[0067] The real-time acquisition and constraint judgment module is used to collect the real-time geomagnetic sequence of the moving carrier, use the speed and heading information of the moving carrier as the motion feature constraints, and judge whether the magnetic field distribution in the current motion direction of the moving carrier has geomagnetic field periodicity characteristics from the geomagnetic field periodicity characteristics on different paths based on the heading information. If so, the geomagnetic field periodic change feature constraint is triggered;

[0068] A screening module is used to screen out candidate fingerprint sequences that meet the constraints in the geomagnetic reference library based on the motion feature constraints and the geomagnetic field periodic change feature constraints;

[0069] The positioning module is used to match and calculate the real-time geomagnetic sequence with the candidate fingerprint sequence to obtain the candidate fingerprint sequence with the highest similarity, extract the position information in the candidate fingerprint sequence with the highest similarity, and obtain the positioning result of the moving carrier on the predetermined route after the moving carrier completes the predetermined route.

[0070] The embodiment of the present application constructs multi-dimensional feature parameters, including motion feature constraints and geomagnetic field periodic change feature constraints, to effectively solve the problem that the matching search range is too large due to the lack of angle constraints in geomagnetic matching positioning in a two-dimensional regional environment, resulting in increased computational complexity and serious impact on positioning efficiency. In addition, the similar geomagnetic sequence features existing in the geomagnetic map are also very likely to cause mismatching during large-scale positioning, resulting in a serious reduction in accuracy. It not only takes into account the influence of the periodic change of the geomagnetic field intensity during the matching process, but also takes into account the kinematic characteristics of the carrier, improves the problem that the traditional positioning method is limited to a one-dimensional area, effectively avoids the problems of high mismatching rate and large sequence matching computational complexity in two-dimensional space, and realizes the global optimal matching of continuous trajectories in two-dimensional space.

[0071] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0072] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0073] The above is only a preferred embodiment of the present application. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application. These should also be regarded as the scope of protection of the present application. These will not affect the effect of the implementation of the present application and the practicality of the patent.

Claims

1. A two-dimensional geomagnetic matching positioning method based on multi-feature parameter constraints, characterized in that: The following steps are involved: Construct a two-dimensional geomagnetic reference map based on measured data, extract magnetic field intensity distribution curves on different paths from the two-dimensional geomagnetic reference map, and form a geomagnetic reference library including spatial coordinates and geomagnetic field intensity; Extract the waveform characteristics and spectrum characteristics of the magnetic field intensity distribution curve, and obtain the periodic characteristics of the geomagnetic field on different paths based on the waveform characteristics and spectrum characteristics; Collect the real-time geomagnetic sequence of the moving carrier, use the speed and heading information of the moving carrier as motion feature constraints, and judge whether the magnetic field distribution in the current direction of movement of the moving carrier has geomagnetic field periodicity characteristics from the geomagnetic field periodicity characteristics on different paths based on the heading information. If so, the geomagnetic field periodic change feature constraint is triggered; According to the motion feature constraints and the periodic change feature constraints of the geomagnetic field, the candidate fingerprint sequences that meet the constraints in the geomagnetic reference library are screened out; The real-time geomagnetic sequence is matched with the candidate fingerprint sequence to obtain the candidate fingerprint sequence with the highest similarity, and the position information in the candidate fingerprint sequence with the highest similarity is extracted. The moving carrier completes the predetermined route and obtains the positioning result of the moving carrier on the predetermined route.

2. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 1 is characterized in that: If there is no periodic feature of the geomagnetic field, the candidate fingerprint sequences that meet the constraints in the geomagnetic reference library are screened out according to the motion feature constraints.

3. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 1 is characterized in that: The two-dimensional geomagnetic reference map covers the area to be positioned, and the different paths include: horizontal paths and vertical paths extracted at equal intervals along the X-axis and Y-axis directions; and parallel oblique paths extracted from the main diagonal and the normal direction of the main diagonal from the lower left corner to the upper right corner of the two-dimensional geomagnetic reference map and extended by equal intervals.

4. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 1, characterized in that: The periodic variation characteristic constraint of the geomagnetic field is to limit the matching range to a specific range, which is expressed as: , For the matching range, is the position of the motion carrier at the previous moment, To match the allowable error, It is the distance corresponding to the change of the Earth's magnetic field within one cycle.

5. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 4 is characterized in that: The distance corresponding to the change of the geomagnetic field within one cycle is determined by the geomagnetic field change cycle. It is obtained by multiplying the velocity of the carrier during mapping.

6. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 1, characterized in that: The motion feature constraints include limiting the matching search area to a circular area centered at the previous moment positioning point through speed constraints; and focusing the matching search area on possible motion directions through heading information constraints, narrowing the search range to a fan-shaped area.

7. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 4 is characterized in that: The final positioning coordinate range of the motion feature constraint is expressed as: ， in, To predict the location, Position the location at the last moment. is the time step, To allow the minimum speed, To allow maximum speed, is the heading angle at the previous moment, is the maximum allowable deflection angle.

8. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 1, characterized in that: The highest similarity means that the cumulative distance between the real-time geomagnetic sequence and the candidate fingerprint sequence is the smallest.

9. The two-dimensional geomagnetic matching positioning method based on multiple feature parameter constraints according to claim 8, characterized in that: The dynamic time warping algorithm is used to calculate the cumulative distance between the real-time geomagnetic sequence and the candidate fingerprint sequence.

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