Geomagnetic contour matching method, device and medium based on combined space constraints

Abstract

The present application discloses a geomagnetic contour matching method, device and medium based on combined spatial constraints. The method includes: obtaining possible matching points and navigation and positioning parameters including a reference magnetic field vector, a measured magnetic field vector and matching point position information. According to the navigation and positioning parameters, determining the combined spatial constraint similarity of the possible matching points; and taking the possible matching point corresponding to the minimum similarity value as a candidate point. The constituent elements of the combined spatial constraint similarity include a magnetic field difference similarity and a continuity similarity. Narrowing the search area centered on the candidate point and performing iterative loops until the iteration condition is satisfied; taking the candidate point obtained in the last iteration as the target matching position. Thus, when calculating the similarity, the combined spatial constraints in multiple aspects such as magnetic field difference and spatial continuity are comprehensively considered, so as to determine candidate points closer to the actual trajectory, thereby enhancing the spatial continuity of the matching result and improving the accuracy and reliability of geomagnetic matching navigation.

Description

Technical Field

[0001] This application relates to the field of navigation technology, and in particular, to a geomagnetic contour matching method, device, and medium based on combined spatial constraints. Background Art

[0002] The geomagnetic contour matching technology is a technology that uses the unique distribution characteristics of the earth's magnetic field for positioning and navigation. Since the geomagnetic contour matching technology does not need to rely on external radio signals, it can be widely applied to scenarios where satellite signals cannot cover, such as underwater, underground, and urban canyons with high-rise buildings.

[0003] The current geomagnetic contour matching technology mainly realizes accurate position matching by comparing the similarity between the measured geomagnetic data obtained by the sensor in real time and the pre-stored reference geomagnetic data. In the current matching method, only the difference information between the magnetic field measurement value and the reference value is considered during the matching process, and the spatial constraint information between the matching points is not considered. For example, the spatial continuity between the matching points is not considered, resulting in poor continuity of the final matching trajectory, unstable matching results, and low navigation accuracy.

[0004] Therefore, how to enhance the spatial continuity of the matching result, improve the matching accuracy, and thus improve the navigation accuracy is a technical problem that needs to be solved urgently 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 based on combined spatial constraints, and the method includes:

[0006] Performing grid search around the inertial navigation system to obtain multiple possible matching points;

[0007] Obtaining navigation positioning parameters; wherein, the navigation positioning parameters include the reference magnetic field vector, measured magnetic field vector, and matching point position information of the possible matching points;

[0008] According to the navigation positioning parameters, determining the combined spatial constraint similarity of the possible matching points; the constituent elements of the combined spatial constraint similarity include a magnetic field difference similarity for characterizing the magnetic field difference and a continuity similarity for characterizing the spatial position continuity;

[0009] Taking the possible matching point corresponding to the minimum value of the combined spatial constraint similarity as the candidate point;

[0010] Centering on the candidate point, narrowing the search area, and performing iterative search until the iteration condition is met; and taking the candidate point obtained in the last iteration as the target matching position.

[0011] Optionally, the navigation and positioning parameters further include the inertial navigation position information of the inertial navigation system; the constituent elements further include an inertial navigation trajectory difference similarity for characterizing the difference between the matching trajectory and the inertial navigation trajectory.

[0012] Optionally, determining the combined spatial constraint similarity according to the navigation and positioning parameters includes:

[0013] Determining the magnetic field difference similarity according to the reference magnetic field vector and the measured magnetic field vector;

[0014] Determining the continuity similarity according to the target matching position at the previous moment and the matching point position information;

[0015] Determining the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information;

[0016] Determining the combined spatial constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity.

[0017] Optionally, determining the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information includes:

[0018] Respectively obtaining the inertial navigation position coordinates at the current moment and the previous moment according to the inertial navigation position information; and determining the inertial navigation displacement increment according to the inertial navigation position coordinates;

[0019] Determining the matching point displacement increment corresponding to each possible matching point according to the target matching position at the previous moment and the matching point position information;

[0020] Determining the inertial navigation trajectory difference similarity according to the inertial navigation displacement increment and the matching point displacement increment.

[0021] Optionally, determining the combined spatial constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity includes:

[0022] Assigning corresponding weights to the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity respectively;

[0023] Performing a weighted sum of the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity based on the weights to obtain the combined spatial constraint similarity.

[0024] Optionally, the sum of the weights is 1, the weight corresponding to the continuity similarity is greater than the weight corresponding to the magnetic field difference similarity, and the weight corresponding to the magnetic field difference similarity is equal to the weight corresponding to the inertial navigation trajectory difference similarity.

[0025] Optionally, the geomagnetic contour matching method based on combined spatial constraints further includes:

[0026] Optimizing the target matching position through Kalman filtering to obtain the target navigation position.

[0027] Another aspect of the present application provides a geomagnetic contour matching device based on combined spatial constraints, and the device includes:

[0028] A possible matching point acquisition module, configured to perform grid search around an inertial navigation system to obtain a plurality of possible matching points;

[0029] A positioning parameter acquisition module, configured to acquire navigation positioning parameters; wherein, the navigation positioning parameters include a reference magnetic field vector, a measured magnetic field vector, and matching point position information of the possible matching points;

[0030] A similarity determination module, configured to determine the combined spatial constraint similarity of the possible matching points according to the navigation positioning parameters; the constituent elements of the combined spatial constraint similarity include a magnetic field difference similarity for characterizing magnetic field differences and a continuity similarity for characterizing spatial position continuity;

[0031] A candidate point acquisition module, configured to use the possible matching point corresponding to the minimum value of the combined spatial constraint similarity as a candidate point;

[0032] A loop control module, configured to take the candidate point as the center, shrink the search area, and perform loop iterative search until the iterative condition is met; and use the candidate point obtained in the last iteration as the target matching position.

[0033] Another aspect of the present application provides a geomagnetic contour matching device based on combined spatial constraints, including a memory and a processor. 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 based on combined spatial constraints are implemented.

[0034] 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 based on combined spatial constraints are implemented.

[0035] The beneficial effects produced by the geomagnetic contour matching method, device, and medium based on combined spatial constraints provided by the present application are as follows: when calculating the similarity of possible matching points, the combined spatial constraints in multiple aspects such as magnetic field differences and spatial continuity are comprehensively considered to determine candidate points closer to the actual trajectory, thereby enhancing the spatial continuity of the matching result and improving the accuracy and reliability of geomagnetic matching navigation. Description of the Drawings

[0036] Figure 1 It is a schematic flowchart of a geomagnetic contour matching method based on combined spatial constraints provided by an embodiment of the present application;

[0037] Figure 2 It is a schematic diagram of the principle of a geomagnetic contour matching method based on combined spatial constraints provided by an embodiment of the present application;

[0038] Figure 3 It is a schematic flowchart of a geomagnetic contour matching method based on combined spatial constraints provided by another embodiment of the present application;

[0039] Figure 4 It is a schematic diagram of a navigation trajectory of a geomagnetic contour matching method based on combined spatial constraints provided by an embodiment of the present application;

[0040] Figure 5 It is an error analysis diagram of a geomagnetic contour matching method based on combined spatial constraints provided by an embodiment of the present application;

[0041] Figure 6 It is a schematic structural diagram of a geomagnetic contour matching device based on combined spatial constraints provided by an embodiment of the present application;

[0042] Figure 7 It is a schematic structural diagram of a geomagnetic contour matching device based on combined spatial constraints provided by another embodiment of the present application.

[0043] The reference numerals are as follows: 40 is a possible matching point acquisition module, 41 is a positioning parameter acquisition module, 42 is a similarity determination module, 43 is a candidate point acquisition module, 44 is a loop control module, 50 is a memory, 51 is a processor, 52 is a display screen, 53 is an input / output interface, 54 is a communication interface, 55 is a power supply, 56 is a communication bus, 501 is a computer program, 502 is an operating system, and 503 is data. Detailed Embodiments

[0044] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms "a", "the", and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0045] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this 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 a determination".

[0046] Figure 1 As shown in the flowchart of a geomagnetic contour matching method based on combined spatial constraints provided by an embodiment of this application, Figure 1 as shown, this method includes:

[0047] S10: Conduct a grid search around the inertial navigation system to obtain multiple possible matching points;

[0048] In a specific embodiment, when the carrier conducts navigation during movement, a search grid is established with the inertial navigation system as the center, and possible matching points are uniformly sampled within the initial search radius. Among them, the possible matching points refer to the set of points that may be points on the actual trajectory. At the same time, the geomagnetic field data of the area to be matched is obtained in real time to establish a geomagnetic database.

[0049] When establishing the geomagnetic database, specifically, read the geomagnetic field data file, which contains the three-component magnetic field data at the longitude and latitude grid points. Further, establish a magnetic field data interpolator for calculating the reference magnetic field vector at any position and record the effective range of the geomagnetic map.

[0050] It should be noted that the carrier in the embodiments of this application may include, but is not limited to, underwater vehicles, aerial vehicles, vehicles, and robots. When conducting the initial grid search, parameters related to the search range need to be obtained, including but not limited to the initial search radius, the minimum search radius, the maximum search radius, and the initial search step size.

[0051] For example, in an optional embodiment, the initial search radius can be set to 1.5 kilometers, the minimum search radius can be set to 1.0 kilometer, the maximum search radius can be set to 5.0 kilometers, and the initial search step size can be set to 0.1 kilometer.

[0052] S11: Obtain navigation and positioning parameters; among them, the navigation and positioning parameters include the reference magnetic field vector, the measured magnetic field vector, and the position information of the matching point of the possible matching point;

[0053] After obtaining the possible matching points, obtain the navigation and positioning parameters through step S11. Specifically, the navigation and positioning parameters include the reference magnetic field vector, the measured magnetic field vector, and the position information of the matching point of the possible matching point.

[0054] Among them, the reference magnetic field vector of the possible matching point can be directly obtained from the geomagnetic field database, and the measured magnetic field vector can be collected in real time through a geomagnetic sensor. The matching point position information includes the longitude and latitude coordinates of the possible matching point.

[0055] S12: Determine the combined spatial constraint similarity of the possible matching points according to the navigation and positioning parameters; the constituent elements of the combined spatial constraint similarity include the magnetic field difference similarity used to characterize the magnetic field difference and the continuity similarity used to characterize the spatial position continuity;

[0056] S13: Take the possible matching point corresponding to the minimum value of the combined spatial constraint similarity as the candidate point;

[0057] Furthermore, in order to determine the best matching point among the possible matching points in the current search and matching cycle, calculate the combined spatial constraint similarity of each possible matching point through step S12. In order to improve the geomagnetic matching accuracy and the continuity of the matching position, therefore, in an optional embodiment, when calculating the similarity of the possible matching points, comprehensively consider the constraint information in multiple aspects such as magnetic field difference and spatial position connection.

[0058] Specifically, calculate the magnetic field difference similarity used to characterize the magnetic field difference between the reference magnetic field vector and the measured magnetic field vector, and at the same time calculate the continuity similarity used to characterize the continuity between the matching point position information at the current moment and the target matching position at the previous moment. Further, the combined spatial constraint similarity can be determined according to the magnetic field difference similarity and the continuity similarity.

[0059] It should be noted that the continuity similarity is used to reflect the position continuity between each currently obtained possible matching point and the target matching position of the final matching result in the previous round (that is, the final navigation position of the navigation and positioning at the previous moment). Thus, it can be understood that the combined spatial constraint similarity is used to determine the point with the best performance in terms of both magnetic field difference and spatial position continuity among multiple possible matching points.

[0060] In an optional embodiment, the smaller the combined spatial constraint similarity, the closer the possible matching point is to the true trajectory. Therefore, take the possible matching point corresponding to the minimum value of the combined spatial constraint similarity in the current search and matching as the candidate point. It can be understood that the candidate point is the best matching point under the relevant parameter conditions of the current search range.

[0061] S14: Take the candidate point as the center, narrow the search area, and perform cyclic iterative search until the iterative condition is met; and take the candidate point obtained in the last iteration as the target matching position.

[0062] Further, centering on the candidate points obtained in step S13, narrow the search area (including but not limited to narrowing the search radius and increasing the search step size), and perform iterative search in a loop, that is, loop through steps S11 to S13 until the iteration condition is met. The candidate point obtained in the last iteration is the point closest to the true trajectory at the current moment, denoted as the target matching position.

[0063] In an alternative embodiment, after obtaining the target matching position, record the longitude and latitude position information of the target matching position and the corresponding combined space constraint similarity. In addition, in an alternative embodiment, to improve the matching efficiency, use a thread pool to perform parallel evaluation of multiple possible matching points, that is, call multi-threaded parallel computing for combined space constraint similarity. Among them, set the maximum number of threads to the number of CPU cores of the system to implement a thread-safe data access mechanism.

[0064] It should be noted that, in an alternative embodiment, the iteration condition can be a preset number of iterations, that is, stop the loop search after reaching the number of iterations. In addition, it should also be noted that, in an alternative embodiment, continuously store and update the current search results and relevant parameters of the search range to provide a reference for subsequent searches, thereby further improving the matching efficiency and accuracy.

[0065] Thus, the geomagnetic contour matching method based on combined space constraints provided by the embodiments of the present application comprehensively considers the combined space constraints in multiple aspects such as magnetic field differences and spatial continuity when calculating the similarity of possible matching points, so as to determine candidate points closer to the actual trajectory, thereby enhancing the spatial continuity of the matching result and improving the accuracy and reliability of geomagnetic matching navigation.

[0066] To further improve the geomagnetic contour matching accuracy and ensure that the matching trajectory does not deviate too far from the inertial navigation system trajectory, in an alternative embodiment, the navigation and positioning parameters may further include the inertial navigation position information of the inertial navigation system, and the constituent elements of the combined space constraint similarity may further include the inertial navigation trajectory difference similarity used to characterize the difference between the matching trajectory and the inertial navigation trajectory.

[0067] Figure 2 This is a schematic diagram of the principle of a geomagnetic contour matching method based on combined space constraints provided by the embodiments of the present application, as Figure 2 shown. In a specific embodiment, add the constraint condition of the inertial navigation trajectory difference similarity to avoid the matching trajectory deviating too far from the inertial navigation trajectory, that is, the difference between the matching trajectory and the inertial navigation trajectory is within an acceptable range.

[0068] In an alternative embodiment, the constituent elements of the combined space constraint similarity include at least two of the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity.

[0069] As Figure 2 shown, in a specific embodiment, the system initialization includes establishing geomagnetic field data. After initialization, a cyclic iterative grid search is performed around the inertial navigation system, and navigation and positioning parameters are obtained in real time. In each cyclic iteration, according to the obtained navigation and positioning parameters, the combined spatial constraint similarity is calculated by at least two of the magnetic field difference similarity, the inertial navigation trajectory difference similarity, and the continuity similarity.

[0070] In each iteration cycle, the minimum value of the combined spatial constraint similarity is used as the candidate point. When entering the next iteration, with the candidate point of the previous iteration as the center, the search range is narrowed and the search is performed again. This cycle continues until the iteration condition is met, and the candidate point obtained in the last iteration is used as the target matching position.

[0071] Thus, the geomagnetic contour matching method based on combined spatial constraints provided by the embodiments of the present application comprehensively considers the magnetic field difference constraint, the spatial continuity constraint, and the inertial navigation constraint. While further improving the matching accuracy, it improves the smoothness of the matching trajectory and enhances the anti-interference ability of the system.

[0072] Figure 3 FIG. is a schematic flow chart of a geomagnetic contour matching method based on combined spatial constraints provided by another embodiment of the present application. On the basis of the above embodiment, as an optional embodiment, as Figure 3 shown, according to the navigation and positioning parameters, determining the combined spatial constraint similarity of possible matching points includes:

[0073] S30: Determine the magnetic field difference similarity according to the reference magnetic field vector and the measured magnetic field vector;

[0074] In an optional embodiment, the Euclidean distance between the measured magnetic field vector and the reference magnetic field vector in the geomagnetic field database can be used to measure the magnetic field difference of each possible matching point. In a specific embodiment, each possible matching point can correspond to a collected measured magnetic field vector and a corresponding reference magnetic field vector . Further, the magnetic field difference similarity is calculated according to formula (1):

[0075] (1)

[0076] where is the magnetic field difference similarity, is the measured magnetic field vector , is the reference magnetic field vector .

[0077] S31: Determine the continuity similarity according to the target matching position and the matching point position information at the previous moment;

[0078] As an optional embodiment, the matching point position information includes the matching point coordinates, and the target matching position includes the target position coordinates. Therefore, the continuity similarity can be measured by the Euclidean distance between the target position coordinates at the previous moment and the matching point position coordinates. The specific calculation formula is formula (2):

[0079] (2)

[0080] Wherein, is the continuity similarity, is the matching point position coordinates at the current moment, and is the target position coordinates at the previous moment.

[0081] In a specific embodiment, the continuity similarity can be calculated between the position coordinates of each possible matching point and the target position coordinates at the previous moment. The continuity similarity is used to constrain the continuity between two points within the expected range.

[0082] It should be noted that when , it indicates that the current matching is the first-round matching of the target matching position at the current moment. At this time, the continuity similarity is not calculated.

[0083] S32: Determine the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information;

[0084] In an optional embodiment, when calculating the inertial navigation trajectory difference similarity, as Figure 3 shown, the following steps are included:

[0085] S320: Obtain the inertial navigation position coordinates at the current moment and the previous moment respectively according to the inertial navigation position information; and determine the inertial navigation displacement increment according to the inertial navigation position coordinates;

[0086] In a specific embodiment, the spatial difference between the matching trajectory and the inertial navigation trajectory is measured by the displacement increment. Specifically, the inertial navigation coordinates at the current moment , and the inertial navigation position coordinates at the previous moment can be obtained respectively according to the inertial navigation position information. Thus, the inertial navigation displacement increment can be obtained.

[0087] S321: Determine the matching point displacement increment corresponding to each possible matching point according to the target matching position and the matching point position information at the previous moment;

[0088] Meanwhile, the displacement increment of each possible matching point can be determined according to the target matching position and the matching point position information at the previous moment. Specifically, calculate the position coordinates of the possible matching points and the target position coordinates of the target matching position at the previous moment to determine the displacement increment of the matching point , that is .

[0089] S322: Determine the inertial navigation trajectory difference similarity according to the inertial navigation displacement increment and the matching point displacement increment.

[0090] Furthermore, the inertial navigation trajectory difference similarity can be calculated according to formula (3):

[0091] (3)

[0092] Wherein is the inertial navigation trajectory difference similarity is the displacement increment of the matching point is the inertial navigation displacement increment.

[0093] S33: Determine the combined space constraint similarity based on the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity.

[0094] In summary, the combined space constraint similarity can be determined by the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity. Specifically, in an optional embodiment , wherein is the combined space constraint similarity.

[0095] Based on the above embodiment, in order to further improve the matching accuracy, the combined space constraint similarity is determined based on the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity, including:

[0096] Assign corresponding weights to the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity respectively

[0097] Based on the weights, perform weighted summation on the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity to obtain the combined space constraint similarity.

[0098] It can be understood that in the actual navigation process, the influence degrees of the magnetic field difference similarity, the continuity similarity and the inertial navigation trajectory difference similarity on the matching result are different. Therefore, in order to achieve the optimal matching. In an optional embodiment, corresponding weights are assigned to different constraints. And based on the weights, weighted summation is performed to obtain the combined space constraint similarity. The specific calculation formula is formula (4):

[0099] (4)

[0100] Among them, is the weight corresponding to the magnetic field difference similarity, is the weight corresponding to the continuity similarity, is the weight corresponding to the INS trajectory difference similarity.

[0101] On the basis of the above embodiments, in order to ensure that the relative contribution degrees of different information sources in the matching and positioning always maintain a reasonable proportional relationship, therefore, the sum of the weights is 1. That is, .

[0102] In order to balance the contributions of various constraints in the matching and considering that the influence degree of spatial continuity on the matching and positioning accuracy is higher, therefore, in an alternative embodiment, the weight corresponding to the continuity similarity can be set to be greater than the weight corresponding to the magnetic field difference similarity, and the weight corresponding to the magnetic field difference similarity is equal to the weight corresponding to the INS trajectory difference similarity.

[0103] For example, in an alternative embodiment, the weight corresponding to the continuity similarity , the weight corresponding to the magnetic field difference similarity , the weight corresponding to the INS trajectory difference similarity . As Figure 2 shown, during the matching time, the system initialization further includes setting the combined space constraint parameters, specifically including setting each weight value.

[0104] Of course, in another alternative embodiment, due to the complex and changeable navigation environment, therefore, in order to improve the adaptability of the navigation to the complex environment, the weight corresponding to the magnetic field difference similarity , the weight corresponding to the continuity similarity and the weight corresponding to the INS trajectory difference similarity can be dynamically adjusted according to the environmental changes.

[0105] Specifically, the weight corresponding to the magnetic field difference similarity can be adjusted by the gradient characteristics generated by the magnetic field, the weight corresponding to the continuity similarity can be adjusted by observing the motion state of the carrier, and the weight corresponding to the INS trajectory difference similarity can be adjusted by the error accumulation time generated by the inertial navigation. Therefore, in the specific embodiment, the measured magnetic field vector, the carrier motion information and the INS time information can be obtained to dynamically adjust the weights.

[0106] In an alternative embodiment, adjusting the current weight coefficient by influencing parameters includes:

[0107] Determine the magnetic field gradient eigenvalue according to the measured magnetic field vector; and adjust the weight corresponding to the magnetic field difference similarity according to the magnetic field gradient eigenvalue ; the greater the magnetic field gradient eigenvalue, the weight corresponding to the magnetic field difference similarity is greater;

[0108] Determine the motion state index value used to reflect the stability of the carrier motion state according to the carrier motion information; adjust the weight corresponding to the continuity similarity according to the motion state index value ;

[0109] Determine the error accumulation time of the inertial navigation system according to the inertial navigation time information; and adjust the weight corresponding to the inertial navigation trajectory difference similarity according to the error accumulation time , the greater the error accumulation time, the weight corresponding to the inertial navigation trajectory difference similarity is smaller.

[0110] In an alternative embodiment, when adjusting the weight corresponding to the inertial navigation trajectory difference similarity , the inertial navigation time information obtained in real time includes the current time and the last reset time of the inertial navigation system, and thus the error accumulation time can be determined according to the formula . Among them, is the error accumulation time, is the current time, is the last reset time of the inertial navigation system.

[0111] When adjusting the weight corresponding to the inertial navigation trajectory difference similarity according to the error accumulation time , obtain the preset maximum error accumulation time and the weight maximum value corresponding to the inertial navigation trajectory difference similarity , and then the weight corresponding to the inertial navigation trajectory difference similarity can be obtained Adjustment function formula . Among them, is the weight maximum value corresponding to the inertial navigation trajectory difference similarity, is the maximum error accumulation time.

[0112] In an alternative embodiment, the carrier motion information includes the motion speed and heading angle of the carrier; determine the motion state index value according to the carrier motion information, including:

[0113] Determine the speed change increment between the current moment and the previous moment through the motion speed, that is, . Among them, is the motion speed at the current moment, is the motion speed at the previous moment.

[0114] Determine the heading change increment between the current moment and the previous moment through the heading angle, that is, , where is the heading angle at the current moment, and

[0115] uses the current motion speed of the carrier as the weight of the heading change increment; based on the weight of the heading change increment, calculates the weighted sum of the speed change increment and the heading change increment to obtain the motion state index value. That is, . Where is the motion state index value, is the speed change increment, is the heading change increment.

[0116] Considering that the heading angle has a greater impact on the position change, that is, the heading change has a greater impact on the motion stability. Therefore, in an alternative embodiment, the current motion speed is introduced as the weight in the heading change increment. Thus, based on the weight of the heading change increment, performing a weighted sum calculation on the speed change increment and the heading change increment can obtain the motion state index value .

[0117] In an alternative embodiment, according to the motion state index value, adjusts the weight corresponding to the continuity similarity, including:

[0118] When the motion state index value is greater than the index threshold, obtains the preset weight adjustment rate and the spatial continuity weight extreme value;

[0119] Based on the weight adjustment rate and the motion state index value, adjusts the weight corresponding to the continuity similarity within the range of the spatial continuity weight extreme value; where the greater the motion state index value, the greater the weight corresponding to the continuity similarity.

[0120] Specifically, it can be according to the formula: , adjusts the weight corresponding to the continuity similarity. Where is the minimum value of the spatial continuity weight, is the maximum value of the spatial continuity weight, and constitute the spatial continuity weight extreme value, is the weight adjustment rate. Using a weight adjustment function in the form of exponential decay can achieve a smooth weight transition and avoid mutations.

[0121] Start to adjust the weight corresponding to the continuity similarity , in an alternative embodiment, can be set to . In a specific embodiment, the motion state index value is greater than the index threshold When, the weight corresponding to the continuity similarity will be adjusted at a weight adjustment rate towards the maximum value of the weight corresponding to the continuity similarity That is, the larger the value of the motion state index the larger the weight corresponding to the continuity similarity will be.

[0122] If the value of the motion state index is not greater than the index threshold then it will decay towards the minimum value of the weight corresponding to the continuity similarity In fact, the index threshold is used to distinguish between a stable motion state and a violent motion state, triggering different weight adjustment directions.

[0123] In an alternative embodiment, based on the measured magnetic field vector, determining the magnetic field gradient eigenvalue includes:

[0124] Obtaining a preset gradient feature extreme value and a magnetic field weight extreme value;

[0125] Determining the gradient vector between adjacent measured magnetic field vectors;

[0126] Based on the gradient feature extreme value, the magnetic field weight extreme value, and the gradient vector, determining the initial gradient feature;

[0127] Normalizing the initial gradient feature to obtain the magnetic field gradient eigenvalue.

[0128] In a specific embodiment, based on the gradient feature extreme value, the magnetic field weight extreme value, and the gradient vector, the initial gradient feature can be calculated, and the specific formula is .

[0129] where, is the initial gradient feature, is the gradient vector between adjacent measured magnetic field vectors, and the gradient vector can be expressed as: . represents the Frobenius norm.

[0130] Furthermore, normalizing the initial gradient feature to obtain the magnetic field gradient eigenvalue, specifically, normalizing the initial gradient feature to the range [0, 1], and the specific formula is: .

[0131] where, is the magnetic field gradient eigenvalue, is the minimum value of the gradient feature, is the maximum value of the gradient feature, and Form gradient feature extreme values. In an alternative embodiment, the minimum value of the gradient feature can be set to 0.1, and the maximum value of the gradient feature can be set to 0.5.

[0132] Furthermore, a weight adjustment function corresponding to the magnetic field difference similarity can be generated based on the magnetic field gradient feature value , specifically, the specific formula is: . .

[0133] Wherein, is the minimum value of the magnetic field weight, is the maximum value of the magnetic field weight, and constitute the extreme values of the magnetic field weight.

[0134] In an alternative embodiment, as Figure 2 shown, in order to further improve the navigation accuracy, the geomagnetic contour matching method based on combined space constraints provided by the present application further includes:

[0135] Optimizing the target matching position through Kalman filtering to obtain the target navigation position.

[0136] In a specific embodiment, as Figure 2 shown, the system initialization further includes initializing the Kalman filter. When the grid search loop iteration reaches the iteration condition, the candidate point corresponding to the last iteration is used as the target matching position. At this time, the target matching position is optimized through Kalman filtering to obtain the final target navigation position. Furthermore, connecting the target navigation positions matched at each moment can obtain the matching trajectory.

[0137] When optimizing the target matching position through Kalman filtering, as Figure 2 shown, the system initialization further includes initializing the Kalman filter. Specifically, in an alternative embodiment, the state vector dimension is set, the observation vector dimension is set, and the state transition matrix is initialized:

[0138]

[0139] The observation matrix is initialized:

[0140]

[0141] The process noise covariance matrix and the observation noise covariance matrix are configured.

[0142] Further, the state vector is defined as: , which includes position information and velocity information . The state transition equation is: , where is the state transition matrix, is the process noise.

[0143] The observation equation is: , where is the observation matrix, is the observation noise. In a specific embodiment, through the recursive mechanism of prediction update, the smoothing optimization of the matching trajectory can be achieved.

[0144] During processing, state prediction includes predicting the state vector , and the predicted covariance matrix . Where is the noise covariance matrix.

[0145] Further, the observation update includes:

[0146] Calculating the Kalman gain: ;

[0147] Updating the state estimate: ;

[0148] Updating the covariance matrix: .

[0149] Where is the observation equation, is the Kalman gain, is the observation noise covariance matrix.

[0150] In an alternative embodiment, the filtering result sequence is stored to implement the forward-backward smoothing algorithm, thereby outputting the final smooth trajectory.

[0151] In an alternative embodiment, the navigation system of the vehicle can be displayed in real time. Specifically, it includes the real-time display of the geomagnetic contour map, the display of the drawn real trajectory, inertial navigation trajectory and matching trajectory, the real-time display of the current position and matching error information, and also includes dynamically updating the display range.

[0152] In another alternative embodiment, the matching results and data are stored and managed in real time. Specifically, the matching results and data are stored in a CSV file, the detailed matching process log is recorded, and the trajectory and error statistical charts are saved.

[0153] As an alternative embodiment, the matching performance can be evaluated. Specifically, it includes precision evaluation and real-time analysis. Among them, the precision evaluation includes calculating the position matching RMS error, analyzing the trajectory continuity index, and evaluating the algorithm convergence performance. The real-time analysis includes counting the single-point matching time, calculating the system update rate, and evaluating the parallel computing efficiency.

[0154] Figure 4 The following is a schematic diagram of the navigation trajectory of a geomagnetic contour matching method based on combined space constraints provided by an embodiment of the present application, as Figure 4 shown, which shows the navigation trajectories under three navigation methods. Among them, the red solid line is the satellite navigation trajectory, the blue dashed line is the inertial navigation trajectory, and the yellow solid line is the geomagnetic navigation trajectory. Correspondingly, the red circle is the current position of satellite navigation, that is, the sampling position of the satellite navigation system. The blue circle is the current position of inertial navigation, that is, the sampling position of the inertial navigation system. The yellow circle is the current position of geomagnetic navigation, that is, the sampling position of the geomagnetic navigation system. The background is a blue contour map showing terrain information. The abscissa is longitude and the ordinate is latitude, expressed in kilometers (km). In an alternative embodiment, Figure 4 the cumulative RMS error (mean square error) is shown, where the cumulative geomagnetic navigation RMS error is 24.37 m, and the cumulative inertial navigation RMS error is 3956.43 m.

[0155] Figure 5 The following is an error analysis diagram of a geomagnetic contour matching method based on combined space constraints provided by an embodiment of the present application, as Figure 5 shown. The abscissa represents the data point serial number (above 0 - 8000), the left vertical axis represents the geomagnetic matching error (yellow bar chart), and the right vertical axis shows the inertial navigation error (blue dashed line). In an alternative embodiment, the current window geomagnetic navigation RMS error is 10.67 m, and the inertial navigation RMS error is 4716.97 m.

[0156] Combined with Figure 4 and Figure 5 it can be seen that the inertial navigation system has obvious cumulative errors and drifts greatly over time. Compared with the inertial navigation system, the geomagnetic navigation system improves the navigation accuracy, has smaller errors, and shows good stability throughout the process.

[0157] Therefore, the geomagnetic contour matching method based on combined space constraints provided by the embodiments of the present application optimizes the matching result by combining a Kalman filter on the basis of comprehensively considering multiple constraints such as the difference between the magnetic field measurement value and the reference value, the spatial continuity constraint, and the inertial navigation constraint, further improving the matching accuracy and reliability.

[0158] In the above embodiments, the geomagnetic contour matching method based on combined space constraints has been described in detail. The present application also provides an embodiment corresponding to a geomagnetic contour matching device based on combined space constraints.

[0159] Figure 6 FIG. is a schematic structural diagram of a geomagnetic contour matching device based on combined space constraints provided by an embodiment of the present application. As Figure 6 shown, the device includes:

[0160] A possible matching point acquisition module 40, configured to perform grid search around an inertial navigation system to obtain a plurality of possible matching points;

[0161] A positioning parameter acquisition module 41, configured to acquire navigation positioning parameters; wherein, the navigation positioning parameters include a reference magnetic field vector, a measured magnetic field vector, and matching point position information of a possible matching point;

[0162] A similarity determination module 42, configured to determine a combined space constraint similarity of possible matching points according to the navigation positioning parameters; the constituent elements of the combined space constraint similarity include a magnetic field difference similarity for characterizing a magnetic field difference and a continuity similarity for characterizing spatial position continuity;

[0163] A candidate point acquisition module 43, configured to use the possible matching point corresponding to the minimum value of the combined space constraint similarity as a candidate point;

[0164] A loop control module 44, configured to take the candidate point as a center, narrow the search area, and perform loop iterative search until the iteration condition is met; and use the candidate point obtained in the last iteration as the target matching position.

[0165] In addition, the geomagnetic contour matching device based on combined space constraints provided by an embodiment of the present application further includes:

[0166] A magnetic field difference similarity determination module, configured to determine a magnetic field difference similarity according to the reference magnetic field vector and the measured magnetic field vector;

[0167] A continuity similarity determination module, configured to determine a continuity similarity according to the target matching position at the previous moment and the matching point position information;

[0168] An inertial navigation trajectory difference similarity determination module, configured to determine an inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information;

[0169] A first determination module, configured to determine a combined space constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity.

[0170] An inertial navigation displacement increment determination module, configured to obtain inertial navigation position coordinates at the current moment and the previous moment respectively according to inertial navigation position information; and determine an inertial navigation displacement increment according to the inertial navigation position coordinates.

[0171] A matching point displacement increment determination module, configured to determine a matching point displacement increment corresponding to each possible matching point according to the target matching position and matching point position information at the previous moment.

[0172] A second determination module, configured to determine an inertial navigation trajectory difference similarity according to the inertial navigation displacement increment and the matching point displacement increment.

[0173] A weight assignment module, configured to assign corresponding weights to the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity respectively.

[0174] A weighted summation module, configured to perform weighted summation on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity based on the weights to obtain a combined space constraint similarity.

[0175] An optimization module, configured to optimize the target matching position through Kalman filtering to obtain a target navigation position.

[0176] Figure 7 The structural schematic diagram of a geomagnetic contour matching device based on combined space constraints provided by another embodiment of the present application is as Figure 7 shown. The geomagnetic contour matching device based on combined space constraints includes: a memory 50, configured to store a computer program;

[0177] A processor 51, configured to implement the steps of the geomagnetic contour matching method based on combined space constraints mentioned in the above embodiment when executing the computer program.

[0178] The geomagnetic contour matching device based on combined space constraints provided in this embodiment may include, but is not limited to, a laptop computer or a desktop computer, etc.

[0179] Among them, the processor 51 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 51 may be implemented in at least one hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 51 may also include a main processor and a coprocessor. The main processor is a processor used to process data in the wake state, also known as the central processing unit (CPU); the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 51 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 51 may further include an artificial intelligence (AI) processor, and the AI processor is used to process computational operations related to machine learning.

[0180] The memory 50 may include one or more computer-readable storage media, and the computer-readable storage media may be non-transitory. The memory 50 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 50 is at least used to store the following computer program 501. After the computer program is loaded and executed by the processor 51, it can implement the relevant steps of the geomagnetic contour matching method based on combined space constraints disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 50 may further include an operating system 502 and data 503, etc., and the storage method may be transient storage or permanent storage. Among them, the operating system 502 may include Windows, Unix, Linux, etc. The data 503 may include, but is not limited to, the relevant data involved in the geomagnetic contour matching method based on combined space constraints.

[0181] In some embodiments, the geomagnetic contour matching device based on combined space constraints may further include a display screen 52, an input / output interface 53, a communication interface 54, a power supply 55, and a communication bus 56.

[0182] Those skilled in the art can understand that Figure 7 the structure shown in

[0183] The geomagnetic contour matching device based on combined space constraints provided by the embodiment 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 contour matching method based on combined space constraints in the above embodiment.

[0184] It should be noted that although the operations are depicted in a specific order in the drawings, this should not be construed as requiring the 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 requiring such separation 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 based on combined spatial constraints, characterized in that The method includes: Performing a grid search around the inertial navigation system to obtain multiple possible matching points; Obtaining navigation positioning parameters; wherein, the navigation positioning parameters include the reference magnetic field vector, the measured magnetic field vector, and the matching point position information of the possible matching points; Determining the combined spatial constraint similarity of the possible matching points according to the navigation positioning parameters; the constituent elements of the combined spatial constraint similarity include a magnetic field difference similarity for characterizing the magnetic field difference and a continuity similarity for characterizing the spatial position continuity; Taking the possible matching point corresponding to the minimum value of the combined spatial constraint similarity as the candidate point; Centering on the candidate point, narrowing the search area, and performing iterative search until the iteration condition is met; and taking the candidate point obtained in the last iteration as the target matching position; The navigation positioning parameters further include the inertial navigation position information of the inertial navigation system; the constituent elements further include an inertial navigation trajectory difference similarity for characterizing the difference between the matching trajectory and the inertial navigation trajectory; The determining the combined spatial constraint similarity of the possible matching points according to the navigation positioning parameters includes: Determining the magnetic field difference similarity according to the reference magnetic field vector and the measured magnetic field vector; Determining the continuity similarity according to the target matching position at the previous moment and the matching point position information; Determining the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information; Determining the combined spatial constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity.

2. The geomagnetic contour matching method based on combined space constraints according to claim 1, characterized in that The determining the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information includes: Respectively obtaining the inertial navigation position coordinates at the current moment and the previous moment according to the inertial navigation position information; and determining the inertial navigation displacement increment according to the inertial navigation position coordinates; Determining the matching point displacement increment corresponding to each of the possible matching points according to the target matching position at the previous moment and the matching point position information; Determining the inertial navigation trajectory difference similarity according to the inertial navigation displacement increment and the matching point displacement increment.

3. The geomagnetic contour matching method based on combined space constraints according to claim 1, characterized in that The determining the combined spatial constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity includes: Assigning corresponding weights to the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity respectively; Based on the weights, performing weighted summation on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity to obtain the combined spatial constraint similarity.

4. The geomagnetic contour matching method based on combined spatial constraints according to claim 3, wherein The sum of the weights is 1, the weight corresponding to the continuity similarity is greater than the weight corresponding to the magnetic field difference similarity, and the weight corresponding to the magnetic field difference similarity is equal to the weight corresponding to the inertial navigation trajectory difference similarity.

5. The geomagnetic contour matching method based on combined spatial constraints according to claim 1, characterized in that The method further includes: Optimizing the target matching position through Kalman filtering to obtain the target navigation position.

6. A geomagnetic contour matching device based on combined spatial constraints, characterized in that, The device includes: A possible matching point acquisition module, configured to perform a grid search around the inertial navigation system to obtain multiple possible matching points; A positioning parameter acquisition module, configured to acquire navigation positioning parameters; wherein, the navigation positioning parameters include the reference magnetic field vector, the measured magnetic field vector, and the matching point position information of the possible matching points; A similarity determination module, configured to determine the combined spatial constraint similarity of the possible matching points according to the navigation positioning parameters; the constituent elements of the combined spatial constraint similarity include a magnetic field difference similarity for characterizing the magnetic field difference and a continuity similarity for characterizing the spatial position continuity; the navigation positioning parameters further include the inertial navigation position information of the inertial navigation system; the constituent elements further include an inertial navigation trajectory difference similarity for characterizing the difference between the matching trajectory and the inertial navigation trajectory; A candidate point acquisition module, configured to use the possible matching point corresponding to the minimum value of the combined spatial constraint similarity as the candidate point; A loop control module, configured to take the candidate point as the center, shrink the search area, and perform loop iterative search until the iterative condition is met; and use the candidate point obtained in the last iteration as the target matching position; A magnetic field difference similarity determination module, configured to determine the magnetic field difference similarity according to the reference magnetic field vector and the measured magnetic field vector; A continuity similarity determination module, configured to determine the continuity similarity according to the target matching position at the previous moment and the matching point position information; An inertial navigation trajectory difference similarity determination module, configured to determine the inertial navigation trajectory difference similarity according to the inertial navigation position information and the matching point position information; A first determination module, configured to determine the combined spatial constraint similarity based on the magnetic field difference similarity, the continuity similarity, and the inertial navigation trajectory difference similarity.

7. A geomagnetic contour matching device based on combined space constraints, comprising a memory and a processor, wherein a computer program that can run on the processor is stored on the memory, and is characterized in that When the processor executes the program, it implements the steps of the geomagnetic contour matching method based on combined spatial constraints according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the geomagnetic contour matching method based on combined spatial constraints according to any one of claims 1 to 5.

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