CN112461223B - Magnetometer zero-bias independent magnetic field fingerprint database generation method - Google Patents

Magnetometer zero-bias independent magnetic field fingerprint database generation method Download PDF

Info

Publication number
CN112461223B
CN112461223B CN202011247148.7A CN202011247148A CN112461223B CN 112461223 B CN112461223 B CN 112461223B CN 202011247148 A CN202011247148 A CN 202011247148A CN 112461223 B CN112461223 B CN 112461223B
Authority
CN
China
Prior art keywords
magnetic field
magnetometer
grid
coordinate system
local
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202011247148.7A
Other languages
Chinese (zh)
Other versions
CN112461223A (en
Inventor
旷俭
牛小骥
李泰宇
刘韬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuhan University WHU
Original Assignee
Wuhan University WHU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wuhan University WHU filed Critical Wuhan University WHU
Priority to CN202011247148.7A priority Critical patent/CN112461223B/en
Publication of CN112461223A publication Critical patent/CN112461223A/en
Application granted granted Critical
Publication of CN112461223B publication Critical patent/CN112461223B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C17/00—Compasses; Devices for ascertaining true or magnetic north for navigation or surveying purposes
    • G01C17/38—Testing, calibrating, or compensating of compasses
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases

Landscapes

  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Measurement Of Length, Angles, Or The Like Using Electric Or Magnetic Means (AREA)

Abstract

A method for generating a magnetometer null-bias independent magnetic field fingerprint database. The invention provides a grid-form magnetic field fingerprint database generation method based on the assumption that the intensity components of the geomagnetic field in local regions are the same and the mean value of magnetic field interference is zero. Compared with the existing database building technology, the method is simple and efficient, has no requirement on the posture of the mobile phone, does not need to calibrate the zero bias of the magnetometer, does not need a complex model building and calculating method, can well solve the problem that the magnetic field database is inaccurate due to the zero bias of the magnetometer, and enables the magnetic field database to be more accurate.

Description

Magnetometer zero-bias independent magnetic field fingerprint database generation method
Technical Field
The invention belongs to the technical field of indoor positioning, and particularly relates to a magnetic field fingerprint database generation method.
Background
The magnetic field matching positioning is widely concerned in the navigation positioning field due to the characteristics of being ubiquitous, not needing extra arrangement, having good concealment and the like, and has been developed in the military field for decades. In recent years, due to the popularization of sensors based on micro-electro-mechanical systems technology and the increase of demand of people for location services in indoor scenes, indoor positioning systems based on magnetic field fingerprint matching are rapidly developed. The higher the magnetic field information dimension is, the larger the amount of information contained, and the higher the magnetic field matching positioning accuracy is. In the actual construction work of the magnetic field fingerprint database, the magnetic field fingerprint database is often inaccurate due to the fact that magnetometer calibration is forgotten to be performed, the magnetometer calibration result is inaccurate, and the like. Therefore, how to quickly and efficiently construct an accurate magnetic field fingerprint database is a key point and an urgent problem to be solved.
According to limited research, the method for establishing the magnetic field fingerprint database mainly comprises point-by-point acquisition and walking acquisition respectively. The point-by-point acquisition is carried out on a plurality of positions through static acquisition and interpolation to obtain a magnetic field database, the fingerprint database has high precision but low database building efficiency and cannot reflect whether zero offset of the magnetic field database is correctly compensated or not; the walking acquisition and warehouse building efficiency is high, but the calibration work of the magnetometer is complicated. Both the two database building methods have certain disadvantages, and a method for building the magnetic field fingerprint database with both accuracy and efficiency meeting requirements still needs to be provided.
In summary, a library construction method capable of simultaneously satisfying the efficiency and accuracy of magnetic fingerprint library construction is urgently needed. The invention establishes the grid magnetic field database under the condition of knowing the walking track coordinates and the attitude angles during library establishment, does not need to calibrate the magnetometer in advance, and provides a quick and efficient high-dimensional magnetic field fingerprint database generation method including but not limited to the application scene.
Disclosure of Invention
The invention provides a magnetometer null-bias irrelevant magnetic field fingerprint database generation method, which aims at solving the problem of complicated magnetometer calibration in an ambulatory acquisition database building method. And respectively obtaining the reference magnetic field intensity under the local coordinate system and the magnetometer observation true value under the carrier coordinate system through attitude angle projection, and then obtaining the zero offset of the magnetometer. And after the observation value of the compensation magnetometer obtains the accurate environment magnetic field intensity observation value of the known position, establishing a grid magnetic field fingerprint database by combining data acquisition track coordinates. The method does not need any external equipment or parameter setting, is simple and efficient, has good universality, and can meet the requirements of high-precision and high-dimensionality fingerprint libraries.
The invention adopts the following technical scheme: a magnetometer null-bias independent magnetic field fingerprint library generation method requires that the course angle of a walking track traverses different directions (such as a walking closed rectangular track or a S-shaped track), obtains the magnetometer null bias through attitude projection under the assumption that the local region-based geomagnetic field intensity components are the same and the mean value of magnetic field interference is zero, and establishes a magnetic field fingerprint library; the technical scheme comprises the following steps:
step 1, traversing tracks in different directions at a region walking course angle for establishing a magnetic field fingerprint library, and obtaining coordinates, high-precision attitude angles and magnetic field information of all positions in the walking tracks through sensor data acquired by intelligent equipment;
step 2, projecting the magnetometer original observed values of all positions to a local horizontal coordinate system by using the sensor attitude angles obtained in the step 1, and averaging the magnetic field projection components of all positions to obtain the reference magnetic field strength in the local horizontal coordinate system;
step 3, projecting the reference magnetic field strength to a carrier coordinate system by combining the reference magnetic field strength and the sensor attitude angle to obtain a magnetometer reference observation value; the original observed values and the reference observed values of the magnetometers at all positions are subjected to difference, and the difference value of each position is averaged to obtain the zero offset of the magnetometers; using the acquired magnetometer zero offset to compensate the magnetometer original observed values, and acquiring accurate environment magnetic field intensity observed values of all positions;
step 4, setting a minimum matrix covering a magnetic field database area based on the acquired track coordinates, dividing the minimum matrix into grids with equal size, and smoothing the magnetic field intensity in the same grid; and (4) performing interpolation filling on the non-collected region by using the magnetic field intensity values of the surrounding grids, and finally establishing a magnetic field grid fingerprint database under a local coordinate system.
Further, the positions in the step 1 are three-dimensional positions, namely a north position, an east position and a vertical position; and the attitude angle is a roll angle, a pitch angle and a course angle.
Further, the implementation of step 2 comprises the following sub-steps,
21) projecting the magnetic field intensity of all the positions in the carrier coordinate to a local coordinate system to obtain the magnetic field intensity of each position in the local coordinate system,
Figure BDA0002770388080000021
22) based on the assumption that the average value of the magnetic field interference formed by the manual facilities and the equipment in the local area is zero, the average value of the magnetic field intensity of each position in the local coordinate system is used as the reference magnetic field intensity,
Figure BDA0002770388080000022
in the above formula, the subscript n represents a local coordinate n system, the n system takes the inertial sensor IMU phase center as an origin, the x axis is parallel to the local horizontal plane and points to true north, the y axis is parallel to the local horizontal plane and points to true east, the z axis is perpendicular to the local horizontal plane and points downwards, and the three form a right-handed system; b represents a system b of a carrier coordinate system, the system b takes an inertial sensor IMU phase center as an origin, an x axis points to the advancing direction of the carrier, a y axis is perpendicular to the x axis and points to the right side of the carrier, and a z axis is perpendicular to the x axis and the y axis and forms a right-hand system; i represents the ith position, and j is total;
Figure BDA0002770388080000023
an attitude rotation matrix from the local coordinate system to the carrier coordinate system for each position; mn,iRepresenting the magnetic field strength of the ith position under the n system; mb,iRepresenting the magnetic field intensity of the ith position under the b system; mn_refRepresenting the reference magnetic field strength in the local coordinate system n.
Further, in step 3, the magnetometer original observation value is the fusion magnetic field strength of the magnetometer zero offset, the earth magnetic field and the magnetic field interference formed by the artificial equipment or facilities; the reference magnetic field strength is a projection value of the earth magnetic field strength under a local horizontal coordinate system; the magnetometer reference observed value is a projection value of the earth magnetic field under the carrier coordinate.
Further, the implementation of step 3 comprises the following sub-steps,
31) projecting the reference magnetic field intensity to a magnetometer reference observation value of each position in a carrier coordinate system through an attitude angle,
Figure BDA0002770388080000031
Mn_refrepresenting the reference magnetic field strength under a local coordinate system n system;
32) taking the mean value of the difference between the reference observation value of the magnetometer and the original observation value of the magnetometer in the carrier coordinate system as the zero offset of the magnetometer, and compensating the observation value of the magnetometer to obtain the accurate magnetic field intensity; the specific calculation method is as follows:
Figure BDA0002770388080000032
Figure BDA0002770388080000033
in the formula (I), the compound is shown in the specification,
Figure BDA0002770388080000034
representing the reference observation of the magnetometer under system b, Mb,iA raw output representing the magnetometer at the ith position; bias represents the zero bias error of the magnetometer;
Figure BDA0002770388080000035
represents the magnetometer observations after the i-th position compensation zero offset.
Further, in step 4, the magnetic field strength in the same grid is smoothed, and the smoothing method includes: averaging, weighted averaging, median, maximum-minimum averaging, averaging after eliminating the maximum and minimum, and gaussian model.
Further, in step 4, the non-collected region is interpolated and filled by using the magnetic field intensity values of the surrounding grids, and the interpolation method includes a linear interpolation method, a bilinear interpolation method, a cubic spline interpolation method, a nearest neighbor method, a gaussian model method and a kriging method.
Further, the specific implementation manner of step 4 includes the following sub-steps,
41) projecting the magnetometer observation value after compensating zero offset to a local coordinate system through an attitude angle;
42) dividing the reservoir building area into uniform grids according to the east-west direction and the south-north direction under a local coordinate system, and building a local coordinate system;
43) projecting the three-dimensional position information of the acquisition track into a local coordinate system, and recording a grid corresponding to each position point on the acquisition track;
44) averaging the magnetic field information of all position points in a single grid to obtain high-dimensional magnetic field information of the grid, and forming a magnetic field fingerprint together with the positions of the grid;
45) traversing all the grids, if a certain grid does not contain magnetic field information, interpolating by using the magnetic field information of surrounding grids to fill the magnetic field information of the grid, wherein the interpolation method specifically comprises the following steps:
a) drawing a circle by taking the center of a grid to be interpolated as the center of a circle and n meters as the radius, wherein the grid completely contained in the circle is taken as a grid to be selected, and the grid containing magnetic field information in the grid to be selected is taken as an effective grid;
b) traversing 8 directions of the grid to be interpolated, namely true east, true west, true south, true north, east south, east north, west south and west north, if and only if an effective grid exists in the true east and true west direction or an effective grid exists in the true south and north direction, allowing interpolation operation, and if not, considering the grid to be interpolated as an invalid region in the magnetic field fingerprint library;
c) if the interpolation operation can be carried out, respectively taking out the effective grids which are closest to the grid to be interpolated in 8 directions; if no effective grid exists in a certain direction, the grid in the opposite direction is determined to be ineffective;
d) carrying out weighted average processing on the magnetic field information in the effective grid, wherein the weight is the reciprocal of the distance from the center of the effective grid to the center of the grid to be interpolated, and carrying out normalization processing on the weight to obtain the magnetic field information in the effective grid;
at this point, the generation of the magnetic field fingerprint library is completed.
The invention has the following beneficial effects:
(1) the invention constructs the high-dimensional magnetic field fingerprint database in the north direction, the east direction and the height direction by the walking acquisition method, has high database construction efficiency, simple and easy operation and high information dimensionality of the fingerprint database.
(2) According to the invention, magnetometer calibration is not required to be carried out in advance, and the zero offset of the magnetometer is obtained through attitude projection under the assumption that the components of the magnetic field intensity in a local area are the same and the mean value of magnetic field interference is zero, so that the complicated magnetometer calibration process is omitted, the calibration effect is good, and the operation is further simplified.
(3) The method is simple to operate, easy to realize, simple and feasible, has good universality, does not need any external equipment or parameter setting, and can meet the requirements of a high-precision magnetic field fingerprint library.
Drawings
Fig. 1 is a schematic diagram of a walking track.
FIG. 2 is a diagram of linear interpolation of a magnetic fingerprint library.
Detailed Description
The technical solution of the present invention is further explained with reference to the drawings and the embodiments.
Step 1, holding the mobile phone in a random initial posture, and traversing tracks in different directions (0-360 degrees) at a walking course angle in a region for establishing a magnetic field library. For example, in an open area, walking the route (S-shaped track) in the shape of (a) and (b) in the attached figure 1, and determining the track interval according to the interpolation distance during library building; for a long and narrow corridor, a circle of walking is needed to go along the outer circle of the corridor, if the width of the corridor is larger, an acquisition route is needed to be added in the middle according to the interpolation distance during library building, and the walking tracks are as shown in (c) and (d) (rectangular tracks) in the attached figure 1. Acquiring coordinates of each position in a line-shaped track by using the method of the patent 'acquisition method of indoor positioning fingerprints'; acquiring high-precision attitude angles of the mobile phone at various positions in the walking process by the method of the MEMS gyroscope automatic calibration method; keeping the mobile phone posture stable during the library building period, and completing the acquisition of magnetic field information;
step 2, obtaining the reference magnetic field intensity under the local coordinate system through attitude projection according to the attitude angle obtained in the step 1;
furthermore, the implementation of step 2 comprises the following sub-steps,
21) projecting the magnetic field intensity of all the positions in the carrier coordinate to a local coordinate system to obtain the magnetic field intensity of each position in the local coordinate system,
Figure BDA0002770388080000051
22) based on the assumption that the average value of the magnetic field interference formed by the manual facilities and the equipment in the local area is zero, taking the average value of the magnetic field intensity of each position in the local coordinate system as the reference magnetic field intensity,
Figure BDA0002770388080000052
in the above formula, the subscript n represents a local coordinate n system, the n system takes the inertial sensor IMU phase center as an origin, the x axis is parallel to the local horizontal plane and points to true north, the y axis is parallel to the local horizontal plane and points to true east, the z axis is perpendicular to the local horizontal plane and points downwards, and the three form a right-handed system; b represents a system b of a carrier coordinate system, the system b takes an inertial sensor IMU phase center as an origin, an x axis points to the advancing direction of the carrier, a y axis is perpendicular to the x axis and points to the right side of the carrier, and a z axis is perpendicular to the x axis and the y axis and forms a right-hand system; i represents the ith position, and j is total;
Figure BDA0002770388080000053
an attitude rotation matrix from the local coordinate system to the carrier coordinate system for each position; mn,iRepresenting the magnetic field strength of the ith position under the n system; mb,iA raw output representing the magnetometer at the ith position; mn_refRepresenting the reference magnetic field strength in the local coordinate system n.
Step 3, obtaining a magnetometer reference observation value according to the reference magnetic field intensity in the local horizontal coordinate system obtained in the step 2, solving the magnetometer zero bias and compensating the magnetometer observation value;
furthermore, the implementation of step 3 comprises the following sub-steps,
31) projecting the reference magnetic field intensity to a magnetometer reference observation value of each position in a carrier coordinate system through an attitude angle,
Figure BDA0002770388080000054
in the formula (I), the compound is shown in the specification,
Figure BDA0002770388080000055
is the attitude rotation matrix from the local coordinate system to the carrier coordinate system.
32) And taking the mean value of the difference between the reference observation value of the magnetometer and the original observation value of the magnetometer in the carrier coordinate system as the zero offset of the magnetometer, and compensating the observation value of the magnetometer to obtain the accurate magnetic field intensity. The specific calculation method is as follows:
Figure BDA0002770388080000061
Figure BDA0002770388080000062
in the formula (I), the compound is shown in the specification,
Figure BDA0002770388080000063
representing magnetometer reference observations under system b; bias represents the zero bias error of the magnetometer;
Figure BDA0002770388080000064
represents the magnetometer observations after the i-th position compensation zero offset.
Therefore, a relatively accurate magnetometer observed value is obtained.
And 4, setting a minimum matrix covering the magnetic field database area according to the data acquisition track coordinates, and dividing the reservoir building area into grids with equal size. Averaging the magnetic field intensity in the grids, interpolating the magnetic field intensity of the adjacent grids in the area where the magnetic field intensity is not acquired, and establishing a magnetic field grid fingerprint database under a local coordinate system;
furthermore, the implementation of step 4 comprises the following sub-steps,
41) projecting the magnetometer observation value after compensating zero offset to a local coordinate system through an attitude angle;
42) dividing the reservoir building area into uniform grids according to the east-west direction and the south-north direction under a local coordinate system, and building a local coordinate system;
43) projecting the three-dimensional position information of the acquisition track into a local coordinate system, and recording a grid corresponding to each position point on the acquisition track;
44) averaging the magnetic field information of all position points in a single grid to obtain high-dimensional magnetic field information of the grid, and forming a magnetic field fingerprint together with the positions of the grid;
45) traversing all the grids, if a certain grid does not contain magnetic field information, interpolating by using the magnetic field information of surrounding grids to fill the magnetic field information of the grid, wherein the interpolation method specifically comprises the following steps:
a) the center of the grid to be interpolated is taken as the center of a circle, a circle is drawn by taking 1.5 meters as the radius, the grid completely contained in the circle is taken as a grid to be selected, and the grid containing magnetic field information in the grid to be selected is taken as an effective grid. Assuming the central non-numbered gray grid in fig. 2 as the grid to be interpolated, the radius of the circle is 1.5 m. The grids 1 to 8 are candidate grids, wherein the grids 1 to 6 with gray numbers contain magnetic field information and are effective grids; the grids 7 to 8 with black numbers do not contain magnetic field information and are invalid grids.
b) And traversing 8 directions of the grid to be interpolated, namely true east, true west, true south, true north, east south, east north, west south and west north, if and only if an effective grid exists in the true east and true west direction or an effective grid exists in the true south and north direction, allowing the interpolation operation, and if not, considering the grid to be interpolated as an invalid region in the magnetic field fingerprint library. Grid 2 (due north) and grid 6 (due south) in fig. 2 are both active grids and interpolation operations can be performed.
c) If the interpolation operation can be carried out, respectively taking out the effective grids which are closest to the grid to be interpolated in 8 directions; if no valid grid exists in a certain direction, the grid in the opposite direction is considered invalid. In FIG. 2, grids 1-6 contain magnetic field information, but according to the rule in c, grids 1, 2, 5, 6 satisfy the relative relationship, and are effective grids; the grids 7 and 8 corresponding to the grids 3 and 4 are invalid grids, and do not satisfy the relative relationship, so that the grids are removed from the valid grids.
d) And carrying out weighted average processing on the magnetic field information in the effective grid, wherein the weight is the reciprocal of the distance from the center of the effective grid to the center of the grid to be interpolated. And carrying out normalization processing on the weight to obtain the magnetic field information in the effective grid.
At this point, the generation of the magnetic field fingerprint library is completed.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.

Claims (8)

1. A magnetometer null-bias independent magnetic field fingerprint database generation method is characterized by comprising the following steps:
step 1, walking in a region for establishing a magnetic field fingerprint database, acquiring walking tracks by data each time, traversing different directions by a course angle, and acquiring coordinates, high-precision attitude angles and magnetic field information of all positions in the walking tracks through sensor data acquired by intelligent equipment;
step 2, projecting the original observation values of the magnetometers at all positions to a local horizontal coordinate system by using the attitude angles obtained in the step 1, and averaging the magnetic field projection components at all positions to obtain the reference magnetic field intensity in the local horizontal coordinate system;
step 3, projecting the reference magnetic field strength to a carrier coordinate system by combining the reference magnetic field strength and the attitude angle to obtain a reference observation value of the magnetometer; the original observed values and the reference observed values of the magnetometers at all positions are subjected to difference, and the difference value of each position is averaged to obtain the zero offset of the magnetometers; using the acquired magnetometer zero offset to compensate the magnetometer original observed values, and acquiring accurate ambient magnetic field intensity observed values of all positions;
step 4, setting a minimum matrix covering a magnetic field database area based on the walking track coordinate, dividing the minimum matrix into grids with equal size, and smoothing the magnetic field intensity in the same grid; and (4) performing interpolation filling on the non-collected region by using the magnetic field intensity values of the surrounding grids, and establishing a magnetic field grid fingerprint database under a local coordinate system.
2. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: the positions in the step 1 are three-dimensional positions, namely a north position, an east position and a vertical position; and the attitude angle is a roll angle, a pitch angle and a course angle.
3. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: the implementation of step 2 comprises the following sub-steps,
21) projecting the magnetic field intensity of all the positions in the carrier coordinate system to a local coordinate system to obtain the magnetic field intensity of each position in the local coordinate system,
Figure FDA0003124302940000011
22) based on the assumption that the average value of the magnetic field interference formed by the manual facilities and the equipment in the local area is zero, the average value of the magnetic field intensity of all the positions under the local coordinate system is taken as the reference magnetic field intensity,
Figure FDA0003124302940000012
in the above formula, the subscript n represents a local coordinate n system, the n system takes the inertial sensor IMU phase center as an origin, the x axis is parallel to the local horizontal plane and points to true north, the y axis is parallel to the local horizontal plane and points to true east, the z axis is perpendicular to the local horizontal plane and points downwards, and the three form a right-handed system; b represents a carrier coordinate system b system, the b system takes the IMU phase center of the inertial sensor as an origin, the x axis points to the advancing direction of the carrier, and the y axis is vertical to the carrierPointing to the right side of the carrier on the x axis, wherein the z axis is vertical to the x axis and the y axis and forms a right-handed system; i represents the ith position, and j is total;
Figure FDA0003124302940000021
an attitude rotation matrix from a local coordinate system to a carrier coordinate system for the ith position; mn，iRepresenting the magnetic field strength of the ith position under the n system; mb，iA raw output representing the magnetometer at the ith position; mn_refRepresenting the reference magnetic field strength in the local coordinate system n.
4. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: in step 3, the magnetometer original observation value is the fusion magnetic field intensity of magnetometer zero bias, the earth magnetic field and magnetic field interference formed by artificial equipment or facilities; the reference magnetic field strength is a projection value of the earth magnetic field strength under a local horizontal coordinate system; the magnetometer reference observed value is a projection value of the earth magnetic field under the coordinates of the carrier.
5. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: the implementation of step 3 comprises the following sub-steps,
31) projecting the reference magnetic field intensity to a magnetometer reference observation value of each position in a carrier coordinate system through an attitude angle,
Figure FDA0003124302940000022
Mn_refrepresenting the reference magnetic field strength under a local coordinate system n system;
32) taking the mean value of the difference between the reference observation value of the magnetometer and the original observation value of the magnetometer in the carrier coordinate system as the zero offset of the magnetometer, and compensating the observation value of the magnetometer to obtain the accurate magnetic field intensity; the specific calculation method is as follows:
Figure FDA0003124302940000023
Figure FDA0003124302940000024
in the formula (I), the compound is shown in the specification,
Figure FDA0003124302940000025
representing a reference observation of the magnetometer in the b-frame of the support, Mb，iA raw output representing the magnetometer at the ith position; bias represents the zero bias error of the magnetometer;
Figure FDA0003124302940000026
represents the magnetometer observations after the i-th position compensation zero offset.
6. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: in step 4, smoothing is carried out on the magnetic field intensity in the same grid, and the smoothing method comprises the following steps: averaging, weighted averaging, median, maximum-minimum averaging, averaging after eliminating the maximum and minimum, and gaussian model.
7. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: and 4, carrying out interpolation filling on the non-collected region by using the magnetic field intensity values of the surrounding grids, wherein the interpolation method comprises a linear interpolation method, a bilinear interpolation method, a cubic spline interpolation method, a nearest neighbor method, a Gaussian model method and a Krigin method.
8. The method for generating a magnetometer null-bias independent magnetic field fingerprint database according to claim 1, wherein the method comprises the following steps: a specific implementation of step 4 comprises the following sub-steps,
41) projecting the magnetometer observation value after compensating zero offset to a local coordinate system through an attitude angle;
42) dividing the reservoir building area into uniform grids according to the east-west direction and the south-north direction under a local coordinate system, and building a local coordinate system;
43) projecting the three-dimensional position information of the acquisition track into a local coordinate system, and recording a grid corresponding to each position point on the acquisition track;
44) averaging the magnetic field information of all position points in a single grid to obtain high-dimensional magnetic field information of the grid, and forming a magnetic field fingerprint together with the positions of the grid;
45) traversing all the grids, if a certain grid does not contain magnetic field information, interpolating by using the magnetic field information of surrounding grids to fill the magnetic field information of the grid, wherein the interpolation method specifically comprises the following steps:
a) drawing a circle by taking the center of a grid to be interpolated as the center of a circle and n meters as the radius, wherein the grid completely contained in the circle is taken as a grid to be selected, and the grid containing magnetic field information in the grid to be selected is taken as an effective grid;
b) traversing 8 directions of the grid to be interpolated, namely true east, true west, true south, true north, east south, east north, west south and west north, if and only if an effective grid exists in the true east and true west direction or an effective grid exists in the true south and north direction, allowing interpolation operation, and if not, considering the grid to be interpolated as an invalid region in the magnetic field fingerprint library;
c) if the interpolation operation can be carried out, respectively taking out the effective grids which are closest to the grid to be interpolated in 8 directions; if no effective grid exists in a certain direction, the grid in the opposite direction is determined to be ineffective;
d) and carrying out weighted average processing on the magnetic field information in the effective grid, wherein the weight is the reciprocal of the distance from the center of the effective grid to the center of the grid to be interpolated, and carrying out normalization processing on the weight to obtain the magnetic field information in the effective grid.
CN202011247148.7A 2020-11-10 2020-11-10 Magnetometer zero-bias independent magnetic field fingerprint database generation method Active CN112461223B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011247148.7A CN112461223B (en) 2020-11-10 2020-11-10 Magnetometer zero-bias independent magnetic field fingerprint database generation method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011247148.7A CN112461223B (en) 2020-11-10 2020-11-10 Magnetometer zero-bias independent magnetic field fingerprint database generation method

Publications (2)

Publication Number Publication Date
CN112461223A CN112461223A (en) 2021-03-09
CN112461223B true CN112461223B (en) 2021-08-03

Family

ID=74825484

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011247148.7A Active CN112461223B (en) 2020-11-10 2020-11-10 Magnetometer zero-bias independent magnetic field fingerprint database generation method

Country Status (1)

Country Link
CN (1) CN112461223B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115406467B (en) * 2022-11-01 2023-03-21 北京开拓航宇导控科技有限公司 Automatic calibration method for MEMS gyroscope

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2582389A1 (en) * 1985-05-21 1986-11-28 Lanchier Jean Marc Method and device for plotting the position of an observer on a map
CN102339310A (en) * 2011-09-15 2012-02-01 北京地拓科技发展有限公司 Method for generating raster interpolation and device
CN102506898A (en) * 2011-11-03 2012-06-20 中国科学院自动化研究所 Genetic algorithm-based calibration method for inertial/geomagnetic sensors
CN104215238A (en) * 2014-08-21 2014-12-17 北京空间飞行器总体设计部 Indoor positioning method of intelligent mobile phone
CN104897154A (en) * 2015-04-29 2015-09-09 中测高科（北京）测绘工程技术有限责任公司 Mobile phone-based indoor geomagnetic navigation method and apparatus thereof
CN105043387A (en) * 2015-06-26 2015-11-11 武汉科技大学 Personal indoor positioning system based on inertial navigation aiding geomagnetism
CN105676302A (en) * 2015-11-12 2016-06-15 东南大学 Magnetometer random noise error compensation method based on improved least square method
WO2016126786A1 (en) * 2015-02-03 2016-08-11 The Regents Of The University Of Michigan Last-mile navigation using smartphones
CN105975791A (en) * 2016-05-20 2016-09-28 南京信息工程大学 Sparse region rainfall estimation fusion method based on dual-smoothing method
CN106441302A (en) * 2016-09-23 2017-02-22 上海交通大学 Indoor localization method for large open type area

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100571795B1 (en) * 2004-02-06 2006-04-18 삼성전자주식회사 Geomagnetic sensor for detecting dip angle and method thereof
BR102012017360A2 (en) * 2012-07-13 2014-03-25 Crbs Tech Com De Eletro Eletronico Ltda GEO POSITIONING AND NAVIGATION DEVICE

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2582389A1 (en) * 1985-05-21 1986-11-28 Lanchier Jean Marc Method and device for plotting the position of an observer on a map
CN102339310A (en) * 2011-09-15 2012-02-01 北京地拓科技发展有限公司 Method for generating raster interpolation and device
CN102506898A (en) * 2011-11-03 2012-06-20 中国科学院自动化研究所 Genetic algorithm-based calibration method for inertial/geomagnetic sensors
CN104215238A (en) * 2014-08-21 2014-12-17 北京空间飞行器总体设计部 Indoor positioning method of intelligent mobile phone
WO2016126786A1 (en) * 2015-02-03 2016-08-11 The Regents Of The University Of Michigan Last-mile navigation using smartphones
CN104897154A (en) * 2015-04-29 2015-09-09 中测高科（北京）测绘工程技术有限责任公司 Mobile phone-based indoor geomagnetic navigation method and apparatus thereof
CN105043387A (en) * 2015-06-26 2015-11-11 武汉科技大学 Personal indoor positioning system based on inertial navigation aiding geomagnetism
CN105676302A (en) * 2015-11-12 2016-06-15 东南大学 Magnetometer random noise error compensation method based on improved least square method
CN105975791A (en) * 2016-05-20 2016-09-28 南京信息工程大学 Sparse region rainfall estimation fusion method based on dual-smoothing method
CN106441302A (en) * 2016-09-23 2017-02-22 上海交通大学 Indoor localization method for large open type area

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
《Indoor positioning based on pedestrian dead reckoning and magnetic field matching for smartphones》;Jian Kuang等;《Sensors》;20181126;全文 *
《半参数模型在载体干扰磁场补偿中的应用研究》;李季等;《仪器仪表学报》;20130930;第34卷(第9期);全文 *
《惯性/地磁匹配组合导航相关技术研究》;朱占龙;《中国博士学位论文全文数据库（电子期刊） 信息科技辑》;20160815;全文 *

Also Published As

Publication number Publication date
CN112461223A (en) 2021-03-09

Similar Documents

Publication Publication Date Title
Pei et al. Optimal heading estimation based multidimensional particle filter for pedestrian indoor positioning
US5774826A (en) Optimization of survey coordinate transformations
CN107179086A (en) A kind of drafting method based on laser radar, apparatus and system
CN110057354B (en) Geomagnetic matching navigation method based on declination correction
CN110187375A (en) A kind of method and device improving positioning accuracy based on SLAM positioning result
CN109708632B (en) Laser radar/INS/landmark-pine combined navigation system and method for mobile robot
CN104897154A (en) Mobile phone-based indoor geomagnetic navigation method and apparatus thereof
CN103578141A (en) Method and device for achieving augmented reality based on three-dimensional map system
CN112461224B (en) Magnetometer calibration method based on known attitude angle
CN110412596A (en) A kind of robot localization method based on image information and laser point cloud
CN112614219B (en) Space coordinate conversion method based on identification points for map navigation positioning
Han et al. A matching algorithm based on the nonlinear filter and similarity transformation for gravity-aided underwater navigation
Wang et al. A Delaunay triangulation-based matching area selection algorithm for underwater gravity-aided inertial navigation
CN115272596A (en) Multi-sensor fusion SLAM method oriented to monotonous texture-free large scene
CN111121758B (en) Rapid modeling and credible positioning method for indoor magnetic map
CN111765879A (en) Three-dimensional electronic compass device and practical calibration method
CN112461223B (en) Magnetometer zero-bias independent magnetic field fingerprint database generation method
Zhao et al. Review of slam techniques for autonomous underwater vehicles
CN116758234A (en) Mountain terrain modeling method based on multipoint cloud data fusion
CN113324544A (en) Indoor mobile robot co-location method based on UWB/IMU (ultra wide band/inertial measurement unit) of graph optimization
CN113536412A (en) BIM and GIS-based high-precision fusion method for three-dimensional live-action model
CN113375664B (en) Autonomous mobile device positioning method based on dynamic loading of point cloud map
CN110542418A (en) Indoor pipeline positioning method integrating two-dimensional code and inertial sensor
CN111080795A (en) Gravity field three-dimensional model construction method based on Delaunay triangulation network
CN109387196B (en) Remote underwater geomagnetic bionic navigation method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant