CN111076717A - Geomagnetic-assisted inertial navigation simulation system and method based on global geomagnetic abnormal field - Google Patents

Geomagnetic-assisted inertial navigation simulation system and method based on global geomagnetic abnormal field Download PDF

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CN111076717A
CN111076717A CN201911408107.9A CN201911408107A CN111076717A CN 111076717 A CN111076717 A CN 111076717A CN 201911408107 A CN201911408107 A CN 201911408107A CN 111076717 A CN111076717 A CN 111076717A
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田峰敏
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Abstract

The invention discloses a geomagnetic auxiliary inertial navigation simulation system based on a global geomagnetic abnormal field, which comprises a track generation module, an inertial navigation module, a navigation magnetic map generation module, a geomagnetic measurement data generation module, a geomagnetic reckoning data generation module and a filter module, wherein the track generation module is used for generating a navigation magnetic map; the invention also discloses a geomagnetic auxiliary inertial navigation simulation method based on the global geomagnetic abnormal field. Compared with the existing linear interpolation geomagnetic navigation method, the estimated track of the natural adjacent point interpolation geomagnetic navigation simulation method is about 10% smaller than that of the linear interpolation geomagnetic navigation method in the aspects of maximum position error, mean value, variance and root mean square under the condition that the time consumption is basically consistent; the system integrates the existing algorithm and data resources, realizes the full-flow simulation of the geomagnetic-assisted inertial navigation system based on the global geomagnetic abnormal field, has a complete autonomous configuration function, can generate any flight path, sets inertial navigation parameters and magnetometer parameters, and can autonomously extend the magnetic field according to the running height of a carrier.

Description

Geomagnetic-assisted inertial navigation simulation system and method based on global geomagnetic abnormal field
Technical Field
The invention relates to the field of geomagnetic navigation, in particular to a geomagnetic auxiliary inertial navigation simulation system and a geomagnetic auxiliary inertial navigation simulation method based on a global geomagnetic abnormal field.
Background
The carrier usually adopts the combination of a satellite and an inertial measurement unit IMU as a sensing mode of real-time position, but the use of the satellite is limited under certain conditions, and the IMU needs to be continuously corrected due to self accumulated error so as to ensure the accuracy of the measured data. The geophysical field comprises a terrain, a geomagnetic field and a gravity field, which are natural correction information sources, compared with terrain navigation, the geomagnetic navigation and the gravity navigation have the advantages of being passive, all-terrain and all-weather, the gravity and gravity gradient measurement requires the platform to run stably, the geomagnetic measurement has no limitation on the movement of the platform, and the geomagnetic measurement equipment is light and cheap compared with the gravity measurement equipment, and the threshold is low.
The geomagnetic field comprises a stable magnetic field and a variable magnetic field, the stable magnetic field is divided into a geomagnetic main field and a geomagnetic abnormal field, the geomagnetic main field is caused by high-temperature liquid iron-nickel circulation flow of an outer layer of a geocell under a valance, the geomagnetic abnormal field is generated by rocks, minerals and artificial magnetic fields distributed on the surface of a crust, the geomagnetic abnormal field is extremely stable in time and hardly changes along with time, and the geomagnetic abnormal field contains more detailed information than the geomagnetic main field and is suitable for being used as an information source for correcting inertial navigation errors. In the existing technical scheme about geomagnetic navigation, the design of the scheme and short-distance experimental verification are mainly focused, and no research is yet made on geomagnetic navigation adopting a global geomagnetic abnormal field.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems, the invention aims to provide a geomagnetic auxiliary inertial navigation simulation system and a geomagnetic auxiliary inertial navigation simulation method based on a global geomagnetic abnormal field, which are used for researching a geomagnetic navigation theoretical model and algorithm and providing basic verification for development of semi-physical simulation and a principle prototype.
The technical scheme is as follows: the invention provides a global geomagnetic auxiliary inertial navigation simulation system based on a global geomagnetic abnormal field, which comprises a track generation module, an inertial navigation module, a navigation magnetic map generation module, a geomagnetic measurement data generation module, a geomagnetic calculation data generation module and a filter module, wherein the track generation module is in communication connection with the inertial navigation module, the navigation magnetic map generation module and the geomagnetic measurement data generation module, the inertial navigation module is in communication connection with the geomagnetic calculation data generation module, the navigation magnetic map generation module is in communication connection with the geomagnetic measurement data generation module and the geomagnetic calculation data generation module, the geomagnetic measurement data generation module and the geomagnetic calculation data generation module are respectively in communication connection with the filter module, and the filter module is in communication connection with the inertial navigation module.
A geomagnetic auxiliary inertial navigation simulation method based on a global geomagnetic abnormal field comprises the following specific steps:
s1: the track generation module generates track points according to the motion instructions of the carrier;
s2: the inertial navigation module generates inertial navigation measurement data and an indication track according to the track point;
s3: transmitting the modified carrier motion parameters to a state equation of a filter module, wherein the initial motion parameters of the carrier come from the initial state of the carrier and the initial measurement value of inertial navigation;
s4: the navigation magnetic map generating module generates a navigation geomagnetic anomaly map by using the data in the basic geomagnetic anomaly map by using a bit field continuation technology according to the running height of the carrier;
s5: the geomagnetic measurement data generation module is used for generating an abnormal field value by interpolating values in a navigation geomagnetic abnormal graph according to the position information of the track point, substituting the position information and the time information stamp of the track point into an international reference geomagnetic field IGRF model to generate a main magnetic field value, calculating measurement noise, and forming geomagnetic measurement data by the sum of the abnormal field value, the main magnetic field value and the measurement noise;
s6: the geomagnetic estimation data generation module is used for interpolating the corrected track point position information in a navigation geomagnetic anomaly map to generate abnormal field estimation data, the corrected track point position information and a time stamp are substituted into an IGRF (integrated gate-coupled radio frequency) model to generate main magnetic field estimation data, and the sum of the abnormal field estimation data and the main magnetic field estimation data forms geomagnetic estimation data;
s7: and transmitting the geomagnetic measurement data and the geomagnetic reckoning data to an observation equation of a filter module, calculating an estimated value of inertial navigation error by using an unscented Kalman filtering algorithm UKF by the filter module, and circulating to the step S3 to obtain a corrected value of the motion parameter of the carrier.
Further, the inertial navigation motion parameters in step S2 include latitude, altitude, velocity, specific force and frame angular velocity of the carrier.
Further, the specific calculation process of the state equation in step S3 is as follows:
1) establishing state quantities including position errors, speed errors, attitude errors, accelerometer measurement errors and gyroscope measurement errors, wherein the state quantities have 15 orders, namely:
Figure BDA0002349228150000021
wherein, δ L, δ λ and δ h are respectively position errors of latitude, longitude and altitude; δ υe、δυn、δυuRespectively representing the speed errors of the east direction, the north direction and the sky direction under a local coordinate system;
Figure BDA0002349228150000022
▽, which is the attitude error angle, i.e. the angle between the mathematical local system and the true local systemx、▽y、▽zThe first-order Markov drift of the accelerometer under a carrier coordinate system; epsilongx、εgy、εgzThe first-order Markov drift of the gyroscope under a carrier coordinate system;
2) the state equation is:
Figure BDA0002349228150000023
where f (t) is the dynamic matrix of the system at time t, specifically,
Figure BDA0002349228150000024
Finsthe inertial navigation error dynamic matrix is 9 multiplied by 9; fSA transformation matrix for the transformation of the gyroscope and accelerometer errors from the carrier coordinate system to the local coordinate system, in particular,
Figure BDA0002349228150000031
Figure BDA00023492281500000315
a transformation matrix from the carrier coordinate system to a northeast geographic coordinate system; fMFor accelerometers and gyroscopes in first orderA matrix of correlation time constants of the koff drift,
Figure BDA0002349228150000032
Tais the zero offset correlation time constant, T, of the accelerometergIs the zero offset correlation time constant of the gyroscope; g (t) is a conversion matrix for converting the inertial navigation device error from a carrier coordinate system to a local coordinate system in the strapdown navigation system,
Figure BDA0002349228150000033
w (t) is process noise of inertial navigation equipment, specifically, w (t) ═ wawgwrawrg]T，waFor accelerometer drift noise, wa＝[waxwaywaz]；wgFor the gyro drift noise, wg＝[wgxwgywgz]；wraFor accelerometer drive noise, wra＝[wraxwraywraz]；wrgFor gyroscope drive noise, wrg＝[wrgxwrgywrgz](ii) a The mathematical expectation is that E { W (t) } 0, E { W (t) WT(τ) } ═ q (t) δ (t- τ), where δ is the unit impulse function and q (t) is the process noise covariance matrix.
Further, the observation equation in step S7 is:
Figure BDA0002349228150000034
wherein
Figure BDA0002349228150000035
Representing the values derived from the state equations,
Figure BDA0002349228150000036
estimating latitude in equation of state for calculation by IGRF model
Figure BDA0002349228150000037
Longitude (G)
Figure BDA0002349228150000038
Height
Figure BDA0002349228150000039
The main earth magnetic field strength at time t;
Figure BDA00023492281500000310
for navigation geomagnetic anomaly map at latitude
Figure BDA00023492281500000311
Longitude (G)
Figure BDA00023492281500000312
A two-dimensional interpolation function at a location;
Figure BDA00023492281500000313
generating a continuation function based on the geomagnetic anomaly map
Figure BDA00023492281500000314
A high-altitude navigation geomagnetic anomaly map; v (t) is a composite white noise composed of magnetometer direction error, time-dependent magnetometer drift, and measurement white noise, and it is mathematically expected that E { V (t) } 0, E { V (t) VT(τ) } ═ r (t) δ (t- τ), δ being the unit impulse function, the observed noise covariance matrix.
Let the sampling period be Δ t, tkAt this time, the state equation in step S3 and the observation equation in step S7 are discretized, and the discretized state quantity is: xk＝X(tk)，
The discretized equation of state expression is:
Xk＝Φk,k-1Xk-1+Γk-1Wk-1(4)
wherein phik,k-1For the state transition matrix, the expression is:
Figure BDA0002349228150000041
Γk-1is process noise Wk-1The expression is:
Figure BDA0002349228150000042
the discretized observation equation expression is as follows:
Figure BDA0002349228150000043
wherein
Figure BDA0002349228150000044
Estimating latitude for calculation of equation of state from IGRF model
Figure BDA0002349228150000045
Longitude (G)
Figure BDA0002349228150000046
Height
Figure BDA0002349228150000047
At time tkThe main field strength of the earth magnetic field;
Figure BDA0002349228150000048
for calculating at latitude from navigation geomagnetic anomaly map
Figure BDA0002349228150000049
Longitude (G)
Figure BDA00023492281500000410
Two-dimensional interpolation function at a location, E { W is satisfied because W (t) and V (t) are white noise processesk}＝0，E{V k0, q (t) and r (t) are covariance intensity arrays of w (t) and v (t), respectively, and when Δ t is not large, q (t) and r (t) are approximately regarded as constant arrays, at which time,
Figure BDA00023492281500000411
wherein Qk≈Q(tk)Δt/；
Figure BDA00023492281500000412
Further, the generation of the geomagnetic estimation data in step S6 uses a natural neighboring point interpolation algorithm, so that higher continuity can be obtained compared with linear interpolation.
Has the advantages that: compared with the prior art, the invention has the following remarkable advantages: compared with the existing linear interpolation geomagnetic navigation method, the method adopts a natural adjacent point interpolation geomagnetic navigation simulation method, and under the condition that the consumed time is basically consistent, the mean value, the variance and the root mean square of errors between the estimated flight path and the real flight path of the natural adjacent point interpolation geomagnetic navigation method are all about 10 percent smaller than those between the estimated flight path and the real flight path of the natural adjacent point interpolation geomagnetic navigation method; the system integrates the existing algorithm and data resources, realizes the full-flow simulation of the geomagnetic auxiliary inertial navigation system based on the geomagnetic abnormal field, has a complete autonomous configuration function, can generate any flight path, sets inertial navigation parameters and magnetometer parameters, and can autonomously extend the magnetic field according to the running height of a carrier.
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FIG. 1 is a schematic diagram of a geomagnetic auxiliary inertial navigation simulation system based on a global geomagnetic abnormal field according to the present invention;
FIG. 2 is a three-dimensional diagram of an EMAG2 for global geomagnetic anomaly field with an altitude of 4000m prepared according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating upward continuation of the embodiment of the present invention to calculate the difference between the geomagnetic anomaly at an altitude of 4000 meters and the original EMAG 2;
FIG. 4 is a diagram illustrating the difference between the geomagnetic anomaly at an altitude of 4000 meters and the original EMAG2 calculated by downward continuation according to the embodiment of the present invention;
FIG. 5 is a three-dimensional display of an embodiment simulation trace;
FIG. 6 is a schematic diagram of a simulated track horizontal projection and local magnetic anomalies;
FIG. 7 is a comparison between an inertial navigation pointing trajectory and a trajectory after geomagnetic correction according to an embodiment of the present invention;
FIG. 8 illustrates an inertial navigation error tracking by two interpolation geomagnetic navigations according to an embodiment of the present invention;
FIG. 9 shows a comparison of two interpolation geomagnetic navigation errors according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, a global geomagnetic auxiliary inertial navigation simulation system based on a global geomagnetic abnormal field includes a track generation module 1, an inertial navigation module 2, a navigation magnetic map generation module 3, a geomagnetic measurement data generation module 4, a geomagnetic estimation data generation module 5, and a filter module 6, where the track generation module 1 is in communication connection with the inertial navigation module 2, the navigation magnetic map generation module 3, and the geomagnetic measurement data generation module 4, the inertial navigation module 2 is in communication connection with the geomagnetic estimation data generation module 5, the navigation magnetic map generation module 3 is in communication connection with the geomagnetic measurement data generation module 4, and the geomagnetic estimation data generation module 5, the geomagnetic measurement data generation module 4 and the geomagnetic estimation data generation module 5 are respectively in communication connection with the filter module 6, and the filter module 6 is in communication connection with the inertial navigation module 2.
A geomagnetic auxiliary inertial navigation simulation method based on a global geomagnetic abnormal field comprises the following specific steps:
s1: the track generation module 1 generates track points according to the motion instructions of the carrier;
s2: the inertial navigation module 2 generates inertial navigation motion parameters and an indication track according to the track point;
s3: transmitting the modified carrier motion parameters to a state equation of a filter module, wherein the initial motion parameters of the carrier come from the initial state of the carrier and the initial measurement value of inertial navigation;
s4: the navigation magnetic map generating module 3 generates a navigation geomagnetic anomaly map by using the data in the basic geomagnetic anomaly map by using a bit field continuation technology according to the running height of the carrier;
s5: the geomagnetic measurement data generation module 4 generates an abnormal field value by interpolating values in the navigation geomagnetic abnormal graph according to the position information of the track point, substitutes the position information and the time information stamp of the track point into the international reference geomagnetic field IGRF model to generate a main magnetic field value, calculates measurement noise, and forms geomagnetic measurement data by the sum of the abnormal field value, the main magnetic field value and the measurement noise;
s6: the geomagnetic estimation data generation module 5 generates abnormal field estimation data according to interpolation of the corrected track point position information in the navigation geomagnetic anomaly map, substitutes the corrected track point position information and a time stamp into the IGRF model to generate main magnetic field estimation data, and the sum of the abnormal field estimation data and the main magnetic field estimation data forms geomagnetic estimation data;
s7: and transmitting the geomagnetic measurement data and the geomagnetic reckoning data to an observation equation of the filter module 6, calculating an estimated value of inertial navigation error by the filter module 6 by using an unscented kalman filter algorithm UKF, and circulating to the step S3 to obtain a corrected value of the motion parameter of the carrier.
Specifically, the inertial navigation motion parameters in step S2 include the latitude, altitude, speed, specific force and frame angular velocity of the carrier.
Specifically, the specific calculation process of the state equation in step S3 is as follows:
1) establishing a discretized state quantity XkIncluding position error, speed error, attitude error, accelerometer measurement error, gyroscope measurement error, totally 15 grades, namely:
Figure BDA0002349228150000061
wherein, δ L, δ λ and δ h are respectively position errors of latitude, longitude and altitude; δ υe、δυn、δυuRespectively representing the speed errors of the east direction, the north direction and the sky direction under a local coordinate system;
Figure BDA0002349228150000062
▽, which is the attitude error angle, i.e. the angle between the mathematical local system and the true local systemx、▽y、▽zThe first-order Markov drift of the accelerometer under a carrier coordinate system; epsilongx、εgy、εgzThe first-order Markov drift of the gyroscope under a carrier coordinate system;
2) establishing a discretization state equation:
Xk＝Φk,k-1Xk-1+Γk-1Wk-1
wherein phik，k-1For the system from tk-1To tkState transition matrix of, in particular
Φk，k-1＝I+F(tk)Δt，
Wherein the content of the first and second substances,
Figure BDA0002349228150000063
Finsthe inertial navigation error dynamic matrix is 9 multiplied by 9; fSA transformation matrix for the transformation of the gyroscope and accelerometer errors from the carrier coordinate system to the local coordinate system, in particular,
Figure BDA0002349228150000071
Figure BDA0002349228150000072
a transformation matrix from the carrier coordinate system to a northeast geographic coordinate system; fMA matrix of associated time constants for the accelerometer and gyroscope first order markov drifts,
Figure BDA0002349228150000073
Tais the zero offset correlation time constant, T, of the accelerometergIs the zero offset correlation time constant of the gyroscope; gamma-shapedk-1Is process noise Wk-1Of (d), in particular Γk-1＝G(tk) Δ t, where G (t) is a transformation matrix for transforming inertial navigation device errors from a carrier coordinate system to a local coordinate system in a strapdown navigation system,
Figure BDA0002349228150000074
Wk＝W(tk) For process noise of inertial navigation equipment, in particular w (t) ═ wawgwrawrg]T，waFor accelerometer drift noise, wa＝[waxwaywaz]；wgFor the gyro drift noise, wg＝[wgxwgywgz]；wraFor accelerometer drive noise, wra＝[wraxwraywraz]；wrgFor gyroscope drive noise, wrg＝[wrgxwrgywrgz](ii) a Satisfies E { Wk}＝0，E{WkWj T}≈Qkδkj，Qk≈Q(tk) And/Δ t, where Q (t) is the covariance matrix of W (t) and δ is the unit impulse function.
Specifically, the observation equation in step S7 is discretized into:
Figure BDA0002349228150000075
wherein
Figure BDA0002349228150000076
For calculation of latitude derived from equation of state by IGRF model
Figure BDA0002349228150000077
Longitude (G)
Figure BDA0002349228150000078
Height
Figure BDA0002349228150000079
Time tkThe main field strength of the earth magnetic field;
Figure BDA00023492281500000710
for calculating at latitude from navigation geomagnetic anomaly map
Figure BDA00023492281500000711
Longitude (G)
Figure BDA00023492281500000712
A two-dimensional interpolation function at a location;
Figure BDA00023492281500000713
generating a continuation function of the basic geomagnetic anomaly map in real time
Figure BDA00023492281500000714
A high-altitude navigation geomagnetic anomaly map; vkIs satisfied for composite white noise consisting of magnetometer heading error, time-dependent magnetometer drift, and measurement white noise
Figure BDA00023492281500000715
Rk≈R(tk) And/Δ t, where R (t) is the covariance matrix of the observed noise and δ is the unit impulse function.
Specifically, in step S6, a natural neighboring point interpolation algorithm is used when calculating the abnormal field estimation data, and first, natural neighboring points of the abnormal field estimation data are found around the interpolation point X and arranged counterclockwise, and then, a shape function is calculated according to an area ratio of the second-order Voronoi unit.
Example 1
Continuation test of geomagnetic anomaly map based on global geomagnetic anomaly field EMAG2
FIG. 2 is a three-dimensional display of original geomagnetic data of EMAG2, prepared at an elevation of 4000m, and a navigation magnetic map generation module 3 respectively extending upward and downward data of EMAG2 by using a bit field extension technique, and FIGS. 3 and 4 are differences between geomagnetic anomaly data at an elevation of 4000m and original geomagnetic anomaly data of EMAG2, which are obtained by extending upward and downward data, respectively, and it can be seen that the differences are + -2 × 10-12And nT.
Example 2
Simulation experiment of geomagnetic-assisted inertial navigation simulation method based on global geomagnetic abnormal field
Simulation experiment test conditions: taking a missile as an example, the missile is accelerated for 20 seconds at the acceleration of 1g, climbs to the elevation angle of 10 degrees and flies at a constant speed for 10 seconds, then the level flight is recovered, the acceleration is continued for 10 seconds, then 2 90-degree turns are made, finally the missile is subjected to dive, the movement lasts 392 seconds, and the flying distance is about 139 kilometers. Inertial navigation and magnetometer parameters are shown in table 1, and the measurement update period is 1 second. Fig. 5-8 are illustrations of simulation procedures, and table 2 is statistics of results of 5 monte carlo simulation experiments.
TABLE 1 inertial navigation and magnetometer parameters for simulation experiments
Figure BDA0002349228150000081
TABLE 2 statistics of simulation test results
Figure BDA0002349228150000082
Figure BDA0002349228150000091
As can be seen from fig. 7 and table 2, the position error starts to diverge after 200 seconds in pure inertial navigation conditions, eventually reaching 9.8 km. After geomagnetic anomaly is adopted for correction, inertial navigation errors can be stably tracked by linear interpolation geomagnetic navigation and natural adjacent point interpolation geomagnetic navigation, the maximum value of the position errors is close to 5km, and the position root mean square error RMSE is close to 2 km. The resolution of the global geomagnetic anomaly data grid of the EMAG2 is 2 minutes (≈ 3.7km), and it can be seen that after the geomagnetic anomaly is adopted for correction, the maximum position error is controlled within 1.5 grids, and the position root mean square error RMSE is controlled within 1/2 grids. In fig. 7, the circle connecting line is the real track of the carrier, the thick solid line is the inertial navigation indicated track, and after 2 90-degree turns, the deviation between the inertial navigation indicated track and the real track is larger and larger; the short thick line and the thin solid line are respectively tracks given by linear interpolation geomagnetic navigation and natural adjacent point geomagnetic navigation, certain deviation exists after the 1 st 90-degree turn, and the position error is reduced again after the 2 nd 90-degree turn.
Fig. 6 is a geomagnetic anomaly of a region where a carrier passes, where a solid line is a projection of a carrier track on a ground level, and a grid curved surface is a rendering graph of a geomagnetic anomaly field intensity amplitude of the region where the carrier track passes.
In fig. 8, the X axis is the carrier running time, unit second, the thick solid line is the error of the inertial navigation indicated track, and the dotted line and the thin solid line are the tracking of the inertial navigation in the latitude direction and the longitude direction by the linear interpolation geomagnetic navigation and the natural adjacent point interpolation geomagnetic navigation, respectively. In fig. 9, the X axis is unit second of carrier operation time, the dotted line is position error of linear interpolation geomagnetic navigation in latitude and longitude directions, the solid line is position error of natural neighboring point interpolation geomagnetic navigation in latitude and longitude directions, it can be seen that they all fluctuate up and down in a 0 horizontal line, and the position error is between 200 seconds and 300 seconds and corresponds to two 90-degree turns, the position error reaches the maximum and then decreases, after 300 seconds, the corresponding carrier enters the 2 nd 90-degree turn, and the position error starts to increase again, but does not diverge.
For the approximation of the geomagnetic abnormal field at any position, two algorithms of natural adjacent point interpolation and linear interpolation are adopted, and the simulation experiment result is shown in table 3, and the experiment result shows that the geomagnetic navigation simulation method of the natural adjacent point interpolation has the maximum value, the mean value, the variance and the root mean square error which are all smaller than the linear interpolation by about 10 percent, and the time consumption of the filtering of the single points of the natural adjacent point interpolation and the linear interpolation is basically equal and is far less than the measurement update sampling period of 1 second, so the natural adjacent point interpolation is adopted as the algorithm for approximating the geomagnetic abnormal field at any position.
Table 3 comparison between natural neighboring point interpolation geomagnetic navigation and linear interpolation geomagnetic navigation (↓ indicates ascending and ↓ indicates descending)
Figure BDA0002349228150000092

Claims (6)

1. The geomagnetic auxiliary inertial navigation simulation system based on the global geomagnetic abnormal field is characterized by comprising a track generation module (1), an inertial navigation module (2), a navigation magnetic map generation module (3), a geomagnetic measurement data generation module (4), a geomagnetic reckoning data generation module (5) and a filter module (6), wherein the track generation module (1) is in communication connection with the inertial navigation module (2), the navigation magnetic map generation module (3) and the geomagnetic measurement data generation module (4), the inertial navigation module (2) is in communication connection with the geomagnetic reckoning data generation module (5), the navigation magnetic map generation module (3) is in communication connection with the geomagnetic measurement data generation module (4) and the geomagnetic reckoning data generation module (5), the geomagnetic measurement data generation module (4) and the geomagnetic reckoning data generation module (5) are in communication connection with the filter module (6) respectively, the filter module (6) is in communication connection with the inertial navigation module (2).
2. The geomagnetic auxiliary inertial navigation simulation method based on the global geomagnetic abnormal field is characterized by comprising the following specific steps of:
s1: the track generation module (1) generates track points according to the motion instructions of the carrier;
s2: the inertial navigation module (2) generates inertial navigation motion parameters and an indication track according to the track point;
s3: transmitting the modified carrier motion parameters to a state equation of a filter module (6);
s4: the navigation magnetic map generation module (3) generates a navigation geomagnetic anomaly map by using the data in the basic geomagnetic anomaly map by using a bit field continuation technology according to the running height of the carrier;
s5: the geomagnetic measurement data generation module (4) generates an abnormal field value by interpolating values in the navigation geomagnetic abnormal graph according to the position information of the track point, substitutes the position information and the time information stamp of the track point into the international reference geomagnetic field IGRF model to generate a main magnetic field value, calculates measurement noise, and forms geomagnetic measurement data by the sum of the abnormal field value, the main magnetic field value and the measurement noise;
s6: the geomagnetic estimation data generation module (5) interpolates the corrected track point position information in a navigation geomagnetic anomaly map to generate abnormal field estimation data, the corrected track point position information and a time stamp are substituted into an IGRF model to generate main magnetic field estimation data, and the sum of the abnormal field estimation data and the main magnetic field estimation data forms geomagnetic estimation data;
s7: and transmitting the geomagnetic measurement data and the geomagnetic reckoning data to an observation equation of a filter module (6), calculating an estimated value of inertial navigation error by the filter module (6), and circulating to the step S3 to obtain a corrected value of the carrier motion parameter.
3. A method for simulating geomagnetic aided inertial navigation based on global geomagnetic abnormal field according to claim 2, wherein the inertial navigation parameters in the step S2 include latitude, altitude, velocity, specific force and frame angular velocity of the vehicle.
4. A method for simulating geomagnetic aided inertial navigation based on global geomagnetic abnormal field according to claim 2, wherein the state equation in the step S3 is calculated as follows:
1) establishing state quantities including position errors, speed errors, attitude errors, accelerometer measurement errors and gyroscope measurement errors, wherein the state quantities have 15 orders, namely:
Figure FDA0002349228140000021
wherein, δ L, δ λ and δ h are respectively position errors of latitude, longitude and altitude; δ υe、δυn、δυuRespectively representing the speed errors of the east direction, the north direction and the sky direction under a local coordinate system;
Figure FDA0002349228140000022
the attitude error angle is the included angle between the mathematical local system and the real local system;
Figure FDA0002349228140000023
the first-order Markov drift of the accelerometer under a carrier coordinate system; epsilongx、εgy、εgzThe first-order Markov drift of the gyroscope under a carrier coordinate system;
2) the state equation is:
Figure FDA0002349228140000024
wherein F (t) is a dynamic matrix of the system at the time t; g (t) is a conversion matrix for converting the inertial navigation equipment error from a carrier coordinate system to a local coordinate system in the strapdown navigation system; w (t) is inertial navigation device process noise, and the mathematical expectation is that E { W (t) } 0, E { W (t) WT(τ) } ═ q (t) δ (t- τ), where δ is the unit impulse function and q (t) is the process noise covariance matrix.
5. A method for simulating geomagnetic auxiliary inertial navigation based on global geomagnetic abnormal field according to claim 2, wherein the observation equation in the step S7 is:
Figure FDA0002349228140000025
wherein
Figure FDA0002349228140000026
Estimating latitude for equation of state computed by IGRF model
Figure FDA0002349228140000027
Longitude (G)
Figure FDA0002349228140000028
Height
Figure FDA0002349228140000029
The main earth magnetic field strength at the time t;
Figure FDA00023492281400000210
for calculating at latitude from navigation geomagnetic anomaly map
Figure FDA00023492281400000211
Longitude (G)
Figure FDA00023492281400000212
A two-dimensional interpolation function at a location;
Figure FDA00023492281400000213
generating a continuation function based on the geomagnetic anomaly map
Figure FDA00023492281400000214
A high-altitude navigation geomagnetic anomaly map; v (t) is a composite white noise composed of magnetometer direction error, time-dependent magnetometer drift, and measurement white noise, and it is mathematically expected that E { V (t) } 0, E { V (t) VT(τ) } ═ r (t) δ (t- τ), where δ is the unit impulse function and r (t) is the observed noise covariance matrix.
6. A method for simulating geomagnetic aided inertial navigation based on the global geomagnetic abnormal field according to claim 2, wherein a natural neighboring point interpolation algorithm is used in the step S6 for generating the geomagnetic abnormal estimation data.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111878056A (en) * 2020-05-11 2020-11-03 中国科学院地质与地球物理研究所 Gyro measurement while drilling system and method
CN113514059A (en) * 2021-05-19 2021-10-19 北京理工大学 Gravity-assisted inertial navigation system simulation platform

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104215259A (en) * 2014-08-22 2014-12-17 哈尔滨工程大学 Inertial navigation error correction method based on geomagnetism modulus gradient and particle filter

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104215259A (en) * 2014-08-22 2014-12-17 哈尔滨工程大学 Inertial navigation error correction method based on geomagnetism modulus gradient and particle filter

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
AIR FORCE INSTITUTE OF TECHNOLOGY: "Airborne Magnetic Anomaly Navigation", 《IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS》 *
柳明等: "基于SLAM的地磁辅助惯性导航系统建模", 《航空精密制造技术》 *
田峰敏等: "基于全球地磁异常场的自主导航仿真系统", 《弹箭与制导学报》 *
蔡永昌等: "基于局部搜索算法的自然邻接点方法", 《力学学报》 *
郑晖等: "地球磁场异常格网(EMAG2)辅助潜艇导航仿真研究", 《地球物理学进展》 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111878056A (en) * 2020-05-11 2020-11-03 中国科学院地质与地球物理研究所 Gyro measurement while drilling system and method
CN111878056B (en) * 2020-05-11 2021-04-13 中国科学院地质与地球物理研究所 Gyro measurement while drilling system and method
CN113514059A (en) * 2021-05-19 2021-10-19 北京理工大学 Gravity-assisted inertial navigation system simulation platform
CN113514059B (en) * 2021-05-19 2024-02-13 北京理工大学 Gravity-assisted inertial navigation system simulation platform

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