A method of joint magnetic field matching of multiple magnetic sensors based on inertial navigation assistance

Abstract

The present invention relates to a method for joint magnetic field matching of multiple magnetic sensors based on inertial navigation assistance, and relates to the field of positioning and navigation technology. The present application establishes a reference magnetic map database; by traversing the reference magnetic map database, the best matching point with the highest matching degree with the environmental magnetic field information measured by each magnetic sensor at present is determined based on the Euclidean criterion as the initialization position; the azimuth information of the best matching point is used to initialize the inertial navigation attitude matrix, and a pure inertial navigation attitude update solution is performed; the output data of each magnetic sensor is collected in real time, and the surrounding magnetic field environment information at the current moment is obtained. Based on the azimuth information obtained by the pure inertial navigation attitude update, the surrounding magnetic field environment information at the current moment is correlated and matched with the magnetic map data near the best matching point to obtain the correlation coefficient; when the correlation coefficient is less than the set threshold, the inertial navigation attitude matrix is ​​initialized again; otherwise, the best matching point is updated, and the output positioning information result is updated synchronously.

Description

Technical Field

[0001] The present invention relates to the field of positioning and navigation technology, and in particular to a method for combining magnetic field matching of multiple magnetic sensors based on inertial navigation assistance. Background Art

[0002] In geomagnetic navigation, especially in the field of aviation geomagnetic navigation and positioning technology, when the aircraft carrier is flying in the air, due to the various interferences far away from the ground, it can only sense and measure the stable geomagnetic field generated by the earth, and the basic magnetic field of the earth changes very slowly, with an annual change rate of less than one thousandth, so the overall geomagnetic navigation effect is relatively ideal. However, when geomagnetic navigation technology is applied to the ground environment, the magnetic sensor senses the environmental magnetic field information in real time.

[0003] The traditional magnetic contour matching (MAGCOM) algorithm is based on the application of the TERCOM algorithm in the field of geomagnetic matching. It is based on the pure translation model. The carrier obtains the characteristic value sequence of the geomagnetic field through the sensor during operation. Then, the local standard geomagnetic field database is searched according to the position information output by the inertial navigation to obtain a new sequence, and the correlation matching calculation is performed. The best sequence determined by the two sets of sequences is the best matching position. The correlation measurement criteria in the MAGCOM algorithm mainly include production correlation (PROD), mean absolute difference (MAD), mean square difference (MSD), normalized production correlation (NPROD), etc., and the correlation measurement is achieved by calculating the similarity or difference between the two. Although the MAGCOM algorithm is simple in design and can quickly complete the matching degree search, the overall accuracy is poor, and the heading error cannot be corrected, which is limited to translation search. In order to increase the heading search capability and realize global search, the ICCP algorithm was proposed. Although the ICCP algorithm takes rotation factors into consideration, can complete translational search and rotational search, has good globality, increases the adaptability to heading errors, and can correct heading errors, the overall efficiency of the algorithm is relatively low, and the use conditions are harsh. It requires that the initial error cannot be too large, otherwise it will cause matching failure and may fall into local optimality, increasing the computational complexity. In addition, both MAGCOM and ICCP methods need to obtain relatively high-precision relative trajectory information to achieve high-precision matching results. In addition to the fixed geomagnetic field generated by the earth, the environmental magnetic field information may also contain magnetic interference information caused by the surrounding environment or buildings, especially some random magnetic interference, which changes more complexly, bringing great challenges to the application of geomagnetic navigation technology. Although the magnetic field matching of multiple magnetic sensors can effectively reduce interference, when performing relevant matching, as the dimension of geomagnetic data increases, the timeliness of matching is affected, and the practicality of navigation is poor. Summary of the invention

[0004] In order to solve the above technical problem or at least partially solve the above technical problem, the present invention provides a method for combining magnetic field matching of multiple magnetic sensors based on inertial navigation assistance.

[0005] The present invention provides a method for combining magnetic field matching of multiple magnetic sensors based on inertial navigation assistance, comprising: establishing a reference magnetic map database, wherein the magnetic map in the reference magnetic map database establishes a one-to-one correspondence between geographic coordinate information and environmental magnetic field information;

[0006] By traversing the reference magnetic spectrum database, based on the Euclidean criterion, the best matching point with the highest matching degree with the environmental magnetic field information currently measured by each magnetic sensor is determined as the initialization position;

[0007] Use the azimuth information of the best matching point to initialize the inertial navigation attitude matrix and perform pure inertial navigation attitude update solution;

[0008] Collect the output data of each magnetic sensor in real time to obtain the current surrounding magnetic field environment information; based on the azimuth information obtained by pure inertial navigation attitude update, perform correlation matching analysis on the current surrounding magnetic field environment information and the magnetic spectrum data near the best matching point to obtain the correlation coefficient;

[0009] When the correlation coefficient shows a non-high correlation, the position and inertial navigation attitude matrix are reinitialized; otherwise, the best matching point is updated and the output positioning information result is updated synchronously.

[0010] Furthermore, the process of traversing the reference magnetic spectrum database and determining the best matching point with the highest matching degree with the magnetic field information currently measured by each magnetic sensor as the initialization position based on the Euclidean criterion is as follows:

[0011] The east component, north component and vertical component of the northeast celestial coordinate system where the magnetic field is located are selected as the characteristic quantities for matching the environmental magnetic field information;

[0012] Collect output data from each magnetic sensor ;

[0013] According to the roll angle and pitch angle of the multi-magnetic sensor hardware platform, the output data of each magnetic sensor is The components of the R, F and D axes projected to the horizontal ground coordinate system are recorded as:

[0014] , Indicates the first OK The components of the three axes R, F and D of the magnetic sensors in the horizontal ground coordinate system are shown in the column; wherein the F axis is the horizontal plane projection axis of the forward direction, R is the right axis orthogonal to the horizontal projection axis of the forward direction, and the R and F axes form a horizontal plane, and D is the gravity direction perpendicular to the horizontal plane;

[0015] Match the magnetic spectra in the benchmark magnetic spectra database with all the magnetic sensors sensed by the multi-magnetic sensor hardware platform The best matching point with the smallest Euclidean distance is used as the initial position, expressed as: ;

[0016] in, Indicates the norm symbol for finding the Euclidean distance; and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information of the magnetic sensor hardware platform; Indicates the searched magnetic field sensed by all magnetic sensors on the multi-magnetic sensor hardware platform The coordinate position information and azimuth information of the best matching point with the smallest Euclidean distance.

[0017] Furthermore, according to the roll angle and pitch angle of the multi-magnetic sensor hardware platform, the output data of each magnetic sensor is converted into The formulas for the R, F, and D axes projected to the horizontal ground coordinate system are:

[0018] ,

[0019] ;

[0020] in, They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively.

[0021] Furthermore, the azimuth information of the best matching point is used to initialize the inertial navigation attitude matrix:

[0022] ;

[0023] in Represents the attitude matrix from the navigation coordinate system to the carrier coordinate system at the time of initialization. is the correction matrix, represents the navigation coordinate system, represents the carrier coordinate system; Represents the horizontal attitude matrix of the carrier coordinate system, represents the horizontal ground coordinate system, where the horizontal attitude matrix of the carrier coordinate system can be expressed as:

[0024] ,

[0025] ;

[0026] They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively;

[0027] Assumptions For a small angle, then:

[0028] ,

[0029] By azimuth Determined correction matrix It can be expressed as:

[0030] .

[0031] Furthermore, after the inertial navigation attitude matrix is ​​initialized, the process of pure inertial navigation attitude update solution includes:

[0032] ;

[0033] in, and Respectively and The strapdown attitude matrix at the moment;

[0034] Using the two-sample cone error compensation algorithm, we have:

[0035] ;

[0036] in, ,

[0037] and The gyroscope of the inertial navigation unit is in the time period The angular increment of two equally spaced samples taken within:

[0038] ,

[0039] ;

[0040] in, Represents the carrier coordinate system measured by the gyroscope Angular velocity information relative to the inertial coordinate system;

[0041] Represents the operational relationship about the equivalent rotation vector, Represents the carrier coordinate system The equivalent rotation vector relative to the inertial coordinate system; Represents the carrier coordinate system The elementary rotation matrix corresponding to the equivalent rotation vector relative to the inertial coordinate system;

[0042] The data update frequency of inertial navigation is relatively high, and it is considered that the data caused by speed and position within the period T The change is small and is considered constant , so we have:

[0043] ;

[0044] in, Represents the angular velocity between the navigation coordinate system and the inertial coordinate system.

[0045] Furthermore, the process of collecting the output data of each magnetic sensor in real time, obtaining the surrounding magnetic field environment information at the current moment, and performing correlation matching analysis on the surrounding magnetic field environment information at the current moment and the magnetic spectrum data near the best matching point includes:

[0046] The cross-correlation algorithm is used to convert the surrounding magnetic field environment information at the current moment Magnetic spectrum data near the best matching point Perform correlation matching analysis and calculate the correlation coefficient according to the following formula :

[0047] ;

[0048] Among them, the inertial navigation attitude solution is obtained and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution; Indicates the azimuth The correction amount; A relevant match search threshold set based on the quality of magnetic spectra in the benchmark magnetic spectra database; A statistic used to reflect the degree of linear correlation between two signals. The closer its value is to 1, the stronger the signal correlation is.

[0049] Furthermore, highly correlated and non-highly correlated highly correlated thresholds are preset, and when the correlation coefficient is greater than the highly correlated threshold, it is determined that the surrounding magnetic field environment information at the current moment is highly correlated with the magnetic spectrum data near the best matching point.

[0050] Furthermore, the process of updating the best matching point and synchronously updating the output positioning information result includes:

[0051] Update the position and azimuth information of the best matching point:

[0052] The formula for the new best matching point position information is:

[0053] ;

[0054] The formula for the new azimuth information is:

[0055] ;

[0056] in, Represents the new best matching point position coordinates, Indicates the azimuth information of the new best matching point;

[0057] The position information of the best matching point is compensated for by the arm to obtain the center position of the multi-magnetic sensor hardware platform, and the center position of the multi-magnetic sensor hardware platform is used as the positioning information result:

[0058] ;

[0059] in, and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution, Indicates the azimuth The correction amount, and Indicates the center position of the multi-magnetic sensor hardware platform, that is, the positioning result information.

[0060] In a second aspect, the present invention provides a multi-magnetic sensor combined magnetic field matching device based on inertial navigation assistance, comprising: at least one processing unit, the processing unit, the storage unit, the inertial navigation unit and the multi-magnetic sensor hardware platform are interconnected through a bus unit, the multi-magnetic sensor hardware platform magnetic field information, and the inertial navigation unit performs azimuth angle resolution; the storage unit stores a computer program, and when the computer program is executed by the processing unit, the method of multi-magnetic sensor combined magnetic field matching based on inertial navigation assistance is implemented.

[0061] In a third aspect, the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the method of multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance.

[0062] The above technical solution provided by the embodiment of the present invention has the following advantages compared with the prior art:

[0063] This method focuses on solving the feasibility and accuracy problems of multi-magnetic sensor solutions in the field of magnetic field matching in practical engineering applications. It is mainly in complex environments such as inertial navigation that cannot provide high-precision trajectory information or abnormal magnetic field environment, and the algorithm cannot effectively and quickly perform magnetic field matching, and the algorithm falls into the local optimal problem when the matching algorithm fails. A method for multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance is proposed. This application uses a magnetic sensor array composed of multiple magnetic sensors to form a multi-magnetic sensor hardware platform. The multi-magnetic sensor hardware platform collects the surrounding environmental magnetic field information and then performs magnetic field matching jointly. Solve the single point failure problem that a single magnetic sensor is prone to as a sensor for measuring the magnetic field, and accelerate geomagnetic matching. In addition, the azimuth information of the best matching point is introduced into the algorithm. The connection between the geographic coordinate information, the multi-magnetic sensor hardware platform and the environmental magnetic field information is determined by the azimuth information, supporting the search in the translation and rotation directions, and enhancing the global search capability. In addition, by introducing the azimuth information obtained by pure inertial navigation solution, the convergence speed of the magnetic field matching algorithm can be accelerated, the efficiency, feasibility and accuracy of the algorithm can be improved, and a fast global search and matching positioning solution is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0065] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0066] Figure 1 A flowchart of a method for multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance provided by an embodiment of the present invention;

[0067] Figure 2 A schematic diagram of coordinate system transformation of each magnetic sensor provided by an embodiment of the present invention;

[0068] Figure 3 A schematic diagram of a multi-magnetic sensor hardware platform provided by an embodiment of the present invention;

[0069] Figure 4 A schematic diagram of a multi-magnetic sensor combined magnetic field matching device based on inertial navigation assistance provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0072] Example 1

[0073] like Figure 1 As shown, the present application provides a method for multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance, which uses the magnetic field information measured by multiple magnetic sensors to obtain the best matching information from the pre-built magnetic map database, and uses the azimuth information in the best matching information to initialize the attitude matrix, solving the initial alignment problem of the inertial navigation and providing the attitude matrix for the subsequent pure inertial navigation solution. When performing COR algorithm calculations, the azimuth information obtained by the pure inertial navigation attitude update solution is used to narrow the search range of the relevant matching algorithm and accelerate the efficiency of the algorithm.

[0074] The steps of a method for multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance provided in this application include:

[0075] Step S1, establishing a reference magnetic spectrum database.

[0076] The magnetic spectra in the benchmark magnetic spectra database are used Indicates that geographic coordinate information has been established The one-to-one correspondence between the magnetic field and the environmental magnetic field information. The east component, north component and vertical component of the northeast celestial coordinate system where the magnetic field is located are selected as the characteristic quantities for matching the environmental magnetic field information. The east component and north component of the northeast celestial coordinate system determine a horizontal plane.

[0077] Step 2: traverse the magnetic map database spectrum, and based on the Euclidean distance criterion, find the best matching point in the magnetic map database that has the highest matching degree with the magnetic field information measured by the current magnetic sensor as the initialization position.

[0078] In the specific implementation process, the process of step 2 includes:

[0079] Collect output data from each magnetic sensor ,That Indicates the first OK The magnetic field information measured by the magnetic sensors in the X-axis, Y-axis and Z-axis directions of the magnetic sensor coordinate system is shown in the figure. Figure 2 As shown, the output data of each magnetic sensor is projected onto the R, F and D axes of the horizontal ground coordinate system. The RFD axes are orthogonal to each other. The F axis is the horizontal plane projection axis of the forward direction. R is the right axis orthogonal to the horizontal projection axis of the forward direction. The R and F axes form a horizontal plane. D is the gravity direction perpendicular to the horizontal plane. The formula is:

[0080] ,

[0081] ;

[0082] in, They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively; Indicates the first OK The components of the three axes R, F and D of the horizontal ground coordinate system of the magnetic sensors in the column are recorded as follows:

[0083] ;

[0084] Match the magnetic spectra in the benchmark magnetic spectra database with all the magnetic sensors sensed by the multi-magnetic sensor hardware platform The best matching point with the smallest Euclidean distance is used as the initial position, expressed as: ;

[0085] in The norm symbol for finding the Euclidean distance is shown in the following example: Figure 3 As shown, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information of the magnetic sensor hardware platform; the horizontal ground coordinate system and the northeast sky coordinate system actually rotate relative to the azimuth , Indicates the searched magnetic field sensed by all magnetic sensors on the multi-magnetic sensor hardware platform The position information and azimuth information of the best matching point with the smallest Euclidean distance;

[0086] Step 3: Use the azimuth information of the best matching point to initialize the inertial navigation attitude matrix:

[0087] ;

[0088] in Represents the attitude matrix from the navigation coordinate system to the carrier coordinate system at the time of initialization. is the correction matrix, represents the navigation coordinate system, represents the carrier coordinate system; Represents the horizontal attitude matrix of the carrier coordinate system, represents the horizontal ground coordinate system, where the horizontal attitude matrix of the carrier coordinate system can be expressed as:

[0089] ,

[0090] ;

[0091] They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively;

[0092] Assumptions For a small angle, then:

[0093] .

[0094] By azimuth Determined correction matrix It can be expressed as:

[0095] .

[0096] Step 4: After initializing the inertial navigation attitude matrix, perform pure inertial navigation attitude update solution based on the inertial navigation data.

[0097] ;

[0098] in, and Respectively and The strapdown attitude matrix at the moment.

[0099] Using the two-sample cone error compensation algorithm, we have:

[0100] ;

[0101] in, ,

[0102] and The gyroscope of the inertial navigation unit is in the time period The angular increment of two equally spaced samples taken within:

[0103] ,

[0104] ;

[0105] in, Represents the carrier coordinate system measured by the gyroscope Angular velocity information relative to the inertial coordinate system.

[0106] Represents the operational relationship about the equivalent rotation vector, Represents the carrier coordinate system The equivalent rotation vector relative to the inertial coordinate system;

[0107] Usually, the data update frequency of the inertial navigation is relatively high, so the period T is relatively small. It can be considered that the period T is caused by the speed and position. The change is very small and can be regarded as a constant, expressed as , so we have:

[0108] ;

[0109] in, Represents the angular velocity between the navigation coordinate system and the inertial coordinate system.

[0110] Step 5: Collect the output data of each magnetic sensor in real time , get the current surrounding magnetic field environment information Based on the azimuth information obtained from the pure inertial navigation attitude update, the surrounding magnetic field environment information at the current moment is The best matching point Nearby magnetic map data Perform correlation matching analysis to obtain the correlation coefficient .

[0111] The cross-correlation algorithm is used to analyze the surrounding magnetic field environment information at the current moment The best matching point Nearby magnetic map data Perform correlation matching analysis and calculate the correlation coefficient according to the following formula :

[0112] ;

[0113] Among them, the inertial navigation attitude solution is obtained and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution; Indicates the azimuth The correction value of is limited by the relevant matching retrieval threshold; is a relevant matching retrieval threshold set based on the magnetic spectrum quality in the reference magnetic spectrum database. ; A statistic used to reflect the degree of linear correlation between two signals. The closer its value is to 1, the stronger the signal correlation is.

[0114] Step 6: Determine whether the current surrounding magnetic field environment information is highly correlated with the magnetic spectrum data near the best matching point based on the correlation coefficient. If the correlation coefficient shows that it is not highly correlated, re-initialize the position and inertial navigation attitude matrix; otherwise, execute step 7 to update the best matching point and synchronously update the output positioning information result.

[0115] A highly correlated threshold value is set in advance for high correlation and non-high correlation, and the correlation coefficient is greater than the highly correlated threshold value to determine that the current surrounding magnetic field environment information is highly correlated with the magnetic spectrum data near the best matching point. , it indicates a slight correlation; when , it indicates low correlation; if , then it is significantly correlated; if , it indicates high correlation. The high correlation threshold is 0.8. , it means that the matching effect is not ideal and the position and inertial navigation attitude matrix need to be reinitialized; that is, jump to step 2.

[0116] Step 7: Update the best matching point and simultaneously update the output positioning information results, including:

[0117] Update the position and azimuth information of the best matching point:

[0118] The formula for the new best matching point position information is:

[0119] ;

[0120] The formula for the new azimuth information is:

[0121] ;

[0122] in, Represents the new best matching point position coordinates, Indicates the azimuth information of the new best matching point;

[0123] Since the best matching point is the position information of the magnetic sensor in the upper left corner of the multi-magnetic sensor matrix, the position information of the best matching point is compensated for by the arm to obtain the center position of the multi-magnetic sensor hardware platform, and the center position of the multi-magnetic sensor hardware platform is used as the positioning information result:

[0124] ;

[0125] in, and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution, Indicates the azimuth The correction amount is and Indicates the center position of the multi-magnetic sensor hardware platform, that is, the positioning result information.

[0126] In order to improve the practicality of the entire system in engineering and increase the robustness of the system in complex environments, this method focuses on solving the feasibility and accuracy problems of the multi-magnetic sensor solution in the field of magnetic field matching in actual engineering applications. The main problems are that a single magnetic sensor cannot effectively and quickly perform magnetic field matching in complex environments such as inertial navigation cannot provide high-precision trajectory information or the magnetic field environment is abnormal, and the algorithm falls into the local optimum when the matching algorithm fails. A method of multi-magnetic sensor combined magnetic field matching based on inertial navigation is proposed. The overall design of the algorithm is simple, and it can achieve fast and effective magnetic field matching while ensuring accuracy, improve the reliability of the entire algorithm, and effectively solve the problems of efficiency, feasibility and accuracy of magnetic field matching. By combining magnetic field matching with multiple magnetic sensors, the problem of the algorithm falling into the local optimum due to matching failure is effectively avoided. By introducing the heading angle information of the inertial navigation, a global magnetic field matching search in a specific direction is realized, which improves the efficiency and accuracy of the algorithm. By introducing the attitude information and azimuth information provided by the inertial navigation, the adaptability to the heading error is increased, and the heading error can be corrected, solving the problem of poor matching accuracy in complex environments.

[0127] Example 2

[0128] See also Figure 4 As shown, an embodiment of the present invention provides a drivable area and lane line detection device, including: at least one processing unit, the processing unit, the storage unit, the multi-magnetic sensor hardware platform and the inertial navigation unit are interconnected through a bus unit, the multi-magnetic sensor hardware platform collects lane environment images, and the storage unit is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as the software programs, computer executable programs and modules corresponding to the method of multi-magnetic sensor combined magnetic field matching based on inertial navigation assistance in an embodiment of the present invention. The processing unit implements the method of multi-magnetic sensor combined magnetic field matching based on inertial navigation assistance by running the software programs, computer executable programs and modules stored in the storage unit, including:

[0129] Establishing a reference magnetic map database, in which the magnetic maps in the reference magnetic map database establish a one-to-one correspondence between geographic coordinate information and environmental magnetic field information;

[0130] By traversing the reference magnetic spectrum database, based on the Euclidean criterion, the best matching point with the highest matching degree with the environmental magnetic field information currently measured by each magnetic sensor is determined as the initialization position;

[0131] Use the azimuth information of the best matching point to initialize the inertial navigation attitude matrix and perform pure inertial navigation attitude update solution;

[0132] Collect the output data of each magnetic sensor in real time to obtain the current surrounding magnetic field environment information; based on the azimuth information obtained by pure inertial navigation attitude update, perform correlation matching analysis on the current surrounding magnetic field environment information and the magnetic spectrum data near the best matching point to obtain the correlation coefficient;

[0133] When the correlation coefficient shows a non-high correlation, the position and inertial navigation attitude matrix are reinitialized; otherwise, the best matching point is updated and the output positioning information result is updated synchronously.

[0134] Of course, the computer program stored in the storage unit of the drivable area and lane line detection device provided in an embodiment of the present invention is not limited to the method operations described above, and can also execute related operations in the method of multi-magnetic sensor combined magnetic field matching based on inertial navigation assistance provided in any embodiment of the present invention.

[0135] Example 3

[0136] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the method for combining magnetic field matching of multiple magnetic sensors based on inertial navigation assistance is implemented, including:

[0137] Establishing a reference magnetic map database, in which the magnetic maps in the reference magnetic map database establish a one-to-one correspondence between geographic coordinate information and environmental magnetic field information;

[0138] By traversing the reference magnetic spectrum database, based on the Euclidean criterion, the best matching point with the highest matching degree with the environmental magnetic field information currently measured by each magnetic sensor is determined as the initialization position;

[0139] Use the azimuth information of the best matching point to initialize the inertial navigation attitude matrix and perform pure inertial navigation attitude update solution;

[0140] Collect the output data of each magnetic sensor in real time to obtain the current surrounding magnetic field environment information; based on the azimuth information obtained by pure inertial navigation attitude update, perform correlation matching analysis on the current surrounding magnetic field environment information and the magnetic spectrum data near the best matching point to obtain the correlation coefficient;

[0141] When the correlation coefficient shows a non-high correlation, the position and inertial navigation attitude matrix are reinitialized; otherwise, the best matching point is updated and the output positioning information result is updated synchronously.

[0142] A computer-readable storage medium provided in an embodiment of the present invention stores a computer program which is not limited to the method operations described above, but can also execute related operations in a method for inertial navigation-assisted multi-magnetic sensor joint magnetic field matching provided in any embodiment of the present invention.

[0143] In the embodiments provided by the present invention, it should be understood that the disclosed structures and methods can be implemented in other ways. For example, the structural embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, structures or units, which can be electrical, mechanical or other forms.

[0144] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0146] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for combining magnetic field matching of multiple magnetic sensors based on inertial navigation assistance, characterized in that: include: Establishing a reference magnetic map database, in which the magnetic maps in the reference magnetic map database establish a one-to-one correspondence between geographic coordinate information and environmental magnetic field information; By traversing the reference magnetic spectrum database, based on the Euclidean criterion, the best matching point with the highest matching degree with the environmental magnetic field information currently measured by each magnetic sensor is determined as the initialization position; The azimuth information of the best matching point is used to initialize the inertial navigation attitude matrix, and a pure inertial navigation attitude update solution is performed; among them, the azimuth information of the best matching point is used to initialize the inertial navigation attitude matrix: ； in Represents the attitude matrix from the navigation coordinate system to the carrier coordinate system at the time of initialization. is the correction matrix, represents the navigation coordinate system, represents the carrier coordinate system; Represents the horizontal attitude matrix of the carrier coordinate system, represents the horizontal ground coordinate system, where the horizontal attitude matrix of the carrier coordinate system can be expressed as: ， ； They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively; Assumptions For a small angle, then: ， By azimuth Determined correction matrix It can be expressed as: ； After initializing the inertial navigation attitude matrix, the process of pure inertial navigation attitude update solution includes: ； in, and Respectively and The strapdown attitude matrix at the moment; Using the two-sample cone error compensation algorithm, we have: ； in, , and The gyroscope of the inertial navigation unit is in the time period The angular increment of two equally spaced samples taken within: ， ； in, Represents the carrier coordinate system measured by the gyroscope Angular velocity information relative to the inertial coordinate system; Represents the operational relationship about the equivalent rotation vector, Represents the carrier coordinate system The equivalent rotation vector relative to the inertial coordinate system; Represents the carrier coordinate system The elementary rotation matrix corresponding to the equivalent rotation vector relative to the inertial coordinate system; The data update frequency of inertial navigation is relatively high, and it is considered that the data caused by speed and position within the period T The change is small and is considered constant , so we have: ； in, Represents the angular velocity between the navigation coordinate system and the inertial coordinate system; Collect the output data of each magnetic sensor in real time to obtain the current surrounding magnetic field environment information; based on the azimuth information obtained by pure inertial navigation attitude update, perform correlation matching analysis on the current surrounding magnetic field environment information and the magnetic spectrum data near the best matching point to obtain the correlation coefficient, including: using the cross-correlation algorithm to match the current surrounding magnetic field environment information Magnetic spectrum data near the best matching point Perform correlation matching analysis and calculate the correlation coefficient according to the following formula : ； Among them, the inertial navigation attitude solution is obtained and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution; Indicates the azimuth The correction value of is limited by the relevant matching retrieval threshold; A relevant match search threshold set based on the quality of magnetic spectra in the benchmark magnetic spectra database; A statistic used to reflect the degree of linear correlation between two signals. The closer its value is to 1, the stronger the signal correlation is. When the correlation coefficient shows a non-high correlation, the position and inertial navigation attitude matrix are reinitialized; otherwise, the best matching point is updated and the output positioning information result is updated synchronously.

2. The method for combining multiple magnetic sensors with inertial navigation-assisted magnetic field matching according to claim 1 is characterized in that: The process of traversing the reference magnetic spectrum database and determining the best matching point with the highest matching degree with the magnetic field information currently measured by each magnetic sensor as the initialization position based on the Euclidean criterion is as follows: The east component, north component and vertical component of the northeast celestial coordinate system where the magnetic field is located are selected as the characteristic quantities for matching the environmental magnetic field information; Collect output data from each magnetic sensor ; According to the roll angle and pitch angle of the multi-magnetic sensor hardware platform, the output data of each magnetic sensor is The components projected onto the R, F and D axes of the horizontal ground coordinate system are recorded as: , Indicates the first OK The magnetic sensors in the column are respectively in the R, F and D three-axis components of the horizontal ground coordinate system; wherein the F axis is the horizontal plane projection axis of the forward direction, R is the right axis orthogonal to the horizontal projection axis of the forward direction, and the R and F axes form a horizontal plane, and D is the gravity direction perpendicular to the horizontal plane; Match the magnetic spectra in the benchmark magnetic spectra database with all the magnetic sensors sensed by the multi-magnetic sensor hardware platform The best matching point with the smallest Euclidean distance is used as the initial position, expressed as: ; in, Indicates the norm symbol for finding the Euclidean distance; and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information of the magnetic sensor hardware platform; Indicates the searched magnetic field sensed by all magnetic sensors on the multi-magnetic sensor hardware platform The coordinate position information and azimuth information of the best matching point with the smallest Euclidean distance.

3. The method for combining multiple magnetic sensors with inertial navigation-assisted magnetic field matching according to claim 2 is characterized in that: According to the roll angle and pitch angle of the multi-magnetic sensor hardware platform, the output data of each magnetic sensor is converted into The formulas for the R, F and D axes of the horizontal ground coordinates projected onto the magnetic map are: ， ； in, They are the roll angle and pitch angle of the multi-magnetic sensor hardware platform respectively.

4. The method for combining multiple magnetic sensors with inertial navigation-assisted magnetic field matching according to claim 1 is characterized in that: Highly correlated and non-highly correlated highly correlated thresholds are preset, and when the correlation coefficient is greater than the highly correlated threshold, it is determined that the surrounding magnetic field environment information at the current moment is highly correlated with the magnetic spectrum data near the best matching point.

5. The method for combining multiple magnetic sensors with inertial navigation-assisted magnetic field matching according to claim 1 is characterized in that: The process of updating the best matching point and synchronously updating the output positioning information results includes: Update the position and azimuth information of the best matching point: The formula for the new best matching point position information is: ； The formula for the new azimuth information is: ； in, Represents the new best matching point position coordinates, Indicates the azimuth information of the new best matching point; The position information of the best matching point is compensated for by the arm to obtain the center position of the multi-magnetic sensor hardware platform, and the center position of the multi-magnetic sensor hardware platform is used as the positioning information result: ； in, and are the offsets of the magnetic field matrix series in the X and Y axis directions of the magnetic sensor coordinate system, and Respectively represent the total number of rows and columns of magnetic sensors in the multi-magnetic sensor hardware platform, and Represents the distance between adjacent magnetic sensors in the column direction and the distance between adjacent magnetic sensors in the row direction in the multi-magnetic sensor hardware platform. Indicates the azimuth information obtained by inertial navigation attitude solution, Indicates the azimuth The correction amount, and Indicates the center position of the multi-magnetic sensor hardware platform, that is, the positioning result information.

6. A multi-magnetic sensor combined magnetic field matching device based on inertial navigation assistance, characterized in that: include: At least one processing unit, the processing unit, the storage unit, the inertial navigation unit and the multi-magnetic sensor hardware platform are interconnected through a bus unit, the multi-magnetic sensor hardware platform receives magnetic field information, and the inertial navigation unit performs azimuth angle resolution; the storage unit stores a computer program, and when the computer program is executed by the processing unit, the method for multi-magnetic sensor joint magnetic field matching based on inertial navigation assistance as described in any one of claims 1-5 is implemented.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for combined magnetic field matching of multiple magnetic sensors based on inertial navigation assistance as described in any one of claims 1 to 5 is implemented.

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