CN115265592B - Online compensation method for magnetic temperature cross-linking coupling error of fiber-optic gyroscope - Google Patents
Online compensation method for magnetic temperature cross-linking coupling error of fiber-optic gyroscope Download PDFInfo
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Abstract
The invention discloses an online compensation method for magnetic temperature cross-linking coupling errors of a fiber optic gyroscope, which comprises the following steps: s1, obtaining a real-time inertial navigation resolving result through navigation resolving; s2, respectively arranging a temperature sensor and a magnetic sensor on the X-direction, Y-direction and Z-direction optical fiber gyroscopes in the optical fiber gyroscopes so as to acquire the temperature and the magnetic field intensity of each direction optical fiber gyroscope in real time; s3, judging whether the prepared GPS signal is effective; if the GPS is effective, executing S4, performing integrated navigation on the GPS output and the output of the fiber optic gyroscope inertial navigation, S5, and training a fiber optic gyroscope magnetic temperature cross-linking coupling error model based on an integrated learning algorithm; if the GPS is invalid, S6 is executed, the model constructed in the step S5 is utilized to predict zero bias errors and S7 of magnetic temperature cross-linking coupling of the fiber optic gyroscope, the zero bias predicted value is compensated to the gyroscope output and is substituted into an inertial navigation solution equation, and a compensated navigation result is obtained; the method completes compensation on line, has good error suppression and compensation effects, improves latitude accuracy by 14.4%, and improves longitude accuracy by 10.5%.
Description
Technical Field
The invention relates to the technical field of inertial navigation error suppression of fiber-optic gyroscopes, in particular to an online compensation method of a magnetic temperature cross-linking coupling error of a fiber-optic gyroscope.
Background
The fiber-optic gyroscope inertial navigation/GPS integrated navigation system consists of fiber-optic gyroscope inertial navigation and GPS, and navigation information of the fiber-optic gyroscope inertial navigation and the GPS is integrated navigated by using a Kalman filter so as to improve navigation precision of the system. When the GPS signal is invalid due to complex terrain, obstruction and other conditions, the navigation precision of the fiber-optic gyroscope inertial navigation/GPS integrated navigation system is determined by the navigation precision of the fiber-optic gyroscope inertial navigation, but the magnetic field and the temperature field of the external environment seriously reduce the use precision of the fiber-optic gyroscope, and limit the navigation precision of the fiber-optic gyroscope inertial navigation.
In order to solve the above problems, in the prior art, the influences of the magnetic field and the temperature field on the fiber optic gyroscope are separately compensated, for example, patent CN108775898B issued to the present invention discloses a fiber optic ring for inhibiting the sensitivity of the magnetic field of the fiber optic gyroscope and a preparation method thereof for separately inhibiting the influence of the magnetic field on the fiber optic gyroscope, and patent CN111238462B issued to the present invention provides an LSTM fiber optic gyroscope Wen Bujian mode method based on deep embedded clustering for separately compensating the influence of the temperature field on the fiber optic gyroscope. After the influence of the magnetic field and the temperature field on the fiber optic gyroscope is compensated independently, in actual use, the fiber optic gyroscope still has zero offset error under the combined action of the temperature field and the magnetic field, and finally the inertial navigation precision of the fiber optic gyroscope is reduced. The influence of the magnetic field and the temperature field on the fiber optic gyroscope is called as a fiber optic gyroscope magnetic temperature cross-linking coupling error, in order to inhibit the error to improve the navigation precision of the fiber optic gyroscope inertial navigation, the patent CN110146109B of the issued invention provides a two-dimensional compensation method of the fiber optic gyroscope magnetic temperature cross-linking coupling error, the patent CN113865576A of the issued invention discloses a fiber optic gyroscope magnetic temperature cross-linking coupling error compensation method based on interpolation, and the patent CN113865577A of the issued invention discloses a subsection compensation method of the fiber optic gyroscope magnetic temperature cross-linking coupling error.
However, the above prior art has the following problems: 1) A simple polynomial fitting method is adopted to construct a magnetic temperature cross-linking coupling error model, but an actual magnetic temperature cross-linking coupling error model is extremely complex, and modeling accuracy is low by using the polynomial fitting method; 2) The compensation is carried out in the laboratory environment, but the actual magnetic temperature cross-linking coupling error is greatly influenced by the environment, and the compensation effect is poor by independently utilizing the compensation result of the laboratory environment; 3) Only a single fiber optic gyroscope is compensated, navigation results are not compensated, and particularly GPS information is not used for assistance, so that the error suppression effect is poor.
Disclosure of Invention
The invention aims to provide an on-line compensation method for the magnetic temperature cross-linking coupling error of the fiber-optic gyroscope, which solves the problems of the prior art for the magnetic temperature cross-linking coupling error compensation of the fiber-optic gyroscope.
For this purpose, the technical scheme of the invention is as follows:
an online compensation method for the magnetic temperature cross-linking coupling error of a fiber optic gyroscope comprises the following steps:
s1, adopting a discretization recurrence algorithm suitable for computer calculation to carry out inertial navigation calculation on the output of an optical fiber gyroscope and an accelerometer in the inertial navigation of the optical fiber gyroscope so as to obtain an inertial navigation calculation result at the moment k in real time: alpha k 、β k 、γ k 、L k 、λ k And h k ；
S2, respectively fixing a temperature sensor and a magnetic sensor on an X-direction fiber optic gyro, a Y-direction fiber optic gyro and a Z-direction fiber optic gyro in the fiber optic gyro to acquire the temperature T of the X-direction fiber optic gyro in real time X And magnetic field strength M X Temperature T of Y-direction fiber optic gyroscope Y And magnetic field strength M Y And temperature T of Z-direction fiber optic gyroscope Z And magnetic field strength M Z ；
S3, judging whether signals of the fiber-optic gyroscope with the GPS or the post-configuration GPS are effective or not:
case 1: when the GPS signals are normally received and the number of the received GPS signals is more than or equal to 6, judging that the GPS is effective, executing the steps S4 to S5, and outputting a compensated navigation result;
case 2: when the GPS signals cannot be received or the GPS signals are normally received but the number of the satellites is less than 6, judging that the GPS is invalid, executing the steps S6 to S7, and outputting a compensated navigation result;
s4, performing integrated navigation on the GPS output and the output of the fiber optic gyroscope inertial navigation; wherein,
s401, constructing a state equation of a Kalman filter of the combined navigation according to an error equation calculated by inertial navigation:wherein X is 15 For a fifteen-dimensional state quantity of the integrated navigation kalman filter,wherein (1)>East error angle for fiber optic gyroscope inertial navigation,>north error angle for inertial navigation of fiber optic gyroscope,>is the angle of the error of the inertial navigation of the fiber-optic gyroscope, delta V E Is the east velocity error, δV, of the inertial navigation of the fiber-optic gyroscope N North speed error, δV, of inertial navigation of fiber optic gyroscope U Is the radial velocity error of the fiber-optic gyroscope inertial navigation, delta L is the latitude error of the fiber-optic gyroscope inertial navigation, delta lambda is the longitude error of the fiber-optic gyroscope inertial navigation, delta h is the altitude error of the fiber-optic gyroscope inertial navigation, epsilon x Zero offset error epsilon of X-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope y Zero offset error epsilon of Y-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope z Zero offset error of Z-direction gyro for inertial navigation of fiber-optic gyro,>zero offset error of X-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of Y-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of the Z-direction accelerometer which is the inertial navigation of the fiber-optic gyroscope;
F 15 is a state transition matrix, and the expression is as follows:
wherein L is latitude, lambda is longitude, and h is altitude; v (V) E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; r is R M And R is N The local earth meridian radius and the mortise unitary circle radius are respectively; omega ie Is the rotation angular rate of the earth;and->The east-direction specific force, the north-direction specific force and the sky-direction specific force are respectively measured by an optical fiber gyroscope inertial navigation accelerometer;the attitude matrix is a land strapdown inertial navigation;
G 15 in order to measure the noise input matrix,u is measurement noise, < >>Wherein u is g Measurement noise for fiber optic gyroscope, u g ＝[u gx u gy u gz ] T ，u gx Measurement noise of X-direction fiber optic gyroscope, u gy Measurement noise of Y-direction fiber optic gyroscope, u gz Measuring noise of the Z-direction fiber optic gyroscope; u (u) a U is the measurement noise of the accelerometer a ＝[u ax u ay u az ] T ，u ax Measurement noise for an X-direction accelerometer, u ay Measurement noise for Y-direction accelerometer, u az Measuring noise for the Z-direction accelerometer;
s402, constructing a measurement equation of a Kalman filter of the integrated navigation: z=hx 15 +υ，
Wherein Z is an observation vector, Z= [ V ] E -V GE ,V N -V GN ,V U -V GU ,L-L G ,λ-λ G ,h-h G ] T Wherein V is E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; v (V) GE 、V GN 、V GU The GPS signal is the east speed, the north speed and the sky speed in the GPS signal; l, lambda and h are latitude, longitude and altitude of the optical fiber inertial navigation output respectively; l (L) G 、λ G And h G Latitude, longitude and altitude in the GPS signal, respectively; h is the observation matrix of the sample,I 3 is a unit matrix with three rows and three columns, +.>0 3×3 Zero matrix of three rows and three columns, 0 3×6 A zero matrix with three rows and six columns; v is observation noise;
s403, solving the state equation constructed in the step S401 and the observation equation constructed in the step S402 by using a Kalman filtering algorithm to obtain a state quantity X in a real-time fifteen-dimensional integrated navigation Kalman filter 15 ；
S404, the inertial navigation solution obtained in step S1, namely alpha k 、β k 、γ k 、L k 、λ k And h k Corresponding state quantities of nine navigation result errors in the real-time fifteen-dimensional combined navigation Kalman filter are subtracted respectively, namely +.>δV E 、δV N 、δV U δl, δλ, δh to obtain a navigation result of the combined navigation, i.e. α, by navigation error compensation k '、β k '、γ k '、V k '、L k '、λ k ' and h k '；
S5, constructing a fiber optic gyroscope magnetic temperature cross-linking coupling error model based on an integrated learning algorithm, taking the temperature and the magnetic field intensity of the three fiber optic gyroscopes acquired in the step S2 as input data, taking the gyro zero bias estimated by the combined navigation obtained in the step S4 as output data, respectively obtaining a prediction model of an X-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof, a prediction model of a Y-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof, and a prediction model of a Z-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof through training;
s6, substituting the temperature and the magnetic field intensity of the three optical fiber gyroscopes acquired in the step S2 into a prediction model of zero bias errors of the X-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the three optical fiber gyroscopes, a prediction model of zero bias errors of the Y-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the Y-direction optical fiber gyroscopes, and a prediction model of zero bias errors of the Z-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the Z-direction optical fiber gyroscopes, so as to obtain zero bias errors epsilon 'of the X-direction optical fiber gyroscopes, which are caused by magnetic temperature cross-linking coupling errors of the optical fiber gyroscopes, respectively' x Zero offset error epsilon 'of Y-direction fiber optic gyroscope' y And zero offset error epsilon 'of Z-direction fiber optic gyroscope' z ；
S7, utilizing the zero offset predicted value epsilon '= [ epsilon ] obtained in the step S6' x ε′ y ε′ z ] T The steps ofIn the solution equation of S1Compensating for->And then->Substituting the navigation result into an inertial navigation solution equation to obtain a compensated navigation result, wherein the method comprises the following steps: alpha k '、β k '、γ k '、V k '、L k '、λ k ' and h k '。
Further, in step S1, the solution formula of the inertial navigation solution is:
L k ＝L k-1 +T s V Nk-1 /(R M +h k-1 )，
λ k ＝λ k-1 +T s V Ek-1 secL k-1 /(R N +h k-1 )，
h k ＝h k-1 +T s V Uk-1 ，
in the method, in the process of the invention, g n ＝[0 0 -g] T ，/>
wherein T is s The real-time sampling period of the original data is set; k is the discretized moment; the physical quantity of each symbol in the lower right-hand corner band k is represented as the state value of the physical quantity at time k, and the symbol in the lower right-hand corner band k-1 is represented as the physical state value at time k-1;v, L, lambda, h are inertial navigation solutions, +.>The attitude matrix is the inertial navigation of the fiber-optic gyroscope; v is the velocity vector of the fiber-optic gyroscope inertial navigation under the navigation coordinate system, and V= [ V ] E V N V U ] T ，V E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; l, lambda and h are latitude, longitude and altitude of the fiber-optic gyroscope inertial navigation on the earth surface respectively; />And f m For the original data +.>For the angular rate raw data measured by a gyroscope component in the inertial navigation of the fiber-optic gyroscope, f m Adding specific force raw data measured by a speedometer component into fiber optic gyroscope inertial navigation; omega ie And g is the earth rotation angular velocity and the gravitational acceleration, respectively; r is R M And R is N The local earth's meridian radius and the mortise unitary radius are respectively;
furthermore, according toThree attitude angles in the navigation result are obtained: pitch angle α=acrsin (C 23 ) Roll angle->Course angle->
Further, in step S2, the temperature sensor is preferably a digital temperature sensor of the model DS18B 20; the magnetic sensor preferably employs an editable hall effect linear sensor model AH 810.
Further, in step S5, in the building of the fiber-optic gyroscope magnetic temperature cross-linking coupling error model based on the integrated learning algorithm, the individual learner adopts a decision tree algorithm learner, and the learner combines with the algorithm Bagging algorithm.
Compared with the prior art, the online compensation method for the magnetic temperature cross-linking coupling error of the fiber optic gyroscope has the beneficial effects that:
1) The magnetic temperature cross-linking coupling error model is constructed by adopting the integrated learning algorithm, so that the modeling accuracy is high; meanwhile, the model is trained by adopting the temperature and magnetic field intensity acquired in real time under the condition that GPS signals are effective and the gyro zero offset estimated in real time by combining the navigation Kalman filter when the GPS signals are effective as data, so that the error suppression effect is improved, and the model is directly utilized to predict the gyro zero offset to complete compensation under the condition that the GPS signals are ineffective, so that the influence of the environment on the magneto-thermal cross-linking coupling error is fully considered, and the compensation effect is good; the method not only can synchronously compensate three fiber-optic gyroscopes, but also can compensate navigation results, and the laboratory calibration process is not needed in the compensation process, but also the online compensation is realized in the navigation process, so that the process is simple and convenient;
2) In a dynamic test, compared with the uncompensated condition, the result of performing magneto-thermal cross-linking coupling error compensation on the inertial navigation of a certain fiber optic gyroscope by adopting the method reduces the maximum latitude error from 0.97Km to 0.83Km, improves the latitude precision by 14.4%, reduces the maximum longitude error from 0.76Km to 0.68Km, improves the longitude precision by 10.5%, and proves the correctness and accuracy of the online compensation method for the magneto-thermal cross-linking coupling error of the fiber optic gyroscope, and has good practicability.
Drawings
FIG. 1 is a schematic flow chart of an online compensation method for magnetic temperature cross-linking coupling errors of a fiber optic gyroscope according to the present invention;
FIG. 2 is a schematic diagram of a fiber optic gyroscope inertial navigation system utilizing the method of the present invention to compensate for pre-and post-compensation latitude errors in dynamic experiments in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of the inertial navigation of a fiber optic gyroscope using the method of the present invention to compensate for pre-and post-compensation longitude errors in a dynamic test, in accordance with an embodiment of the present invention.
Detailed Description
The invention will now be further described with reference to the accompanying drawings and specific examples, which are in no way limiting.
As shown in FIG. 1, the method for on-line compensation of the magnetic temperature cross-linking coupling error of the fiber optic gyroscope comprises the following specific steps:
s1, performing inertial navigation solution by using fiber-optic gyroscope inertial navigation;
adopting a discretization recurrence algorithm suitable for computer calculation to carry out inertial navigation calculation on the output of the fiber-optic gyroscope and the accelerometer in the fiber-optic gyroscope inertial navigation, wherein the specific calculation formula is as follows:
L k ＝L k-1 +T s V Nk-1 /(R M +h k-1 )，
λ k ＝λ k-1 +T s V Ek-1 secL k-1 /(R N +h k-1 )，
h k ＝h k-1 +T s V Uk-1 ，
in the method, in the process of the invention, g n ＝[0 0 -g] T ，/>
wherein T is s The real-time sampling period of the original data is set; k is the discretized moment; the physical quantity of each symbol in the lower right-hand corner band k is represented as the state value of the physical quantity at time k, and the symbol in the lower right-hand corner band k-1 is represented as the physical state value at time k-1;v, L, lambda, h are inertial navigation solutions, +.>The attitude matrix is the inertial navigation of the fiber-optic gyroscope; v is the velocity vector of the fiber-optic gyroscope inertial navigation under the navigation coordinate system, and V= [ V ] E V N V U ] T ，V E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; l, lambda and h are latitude, longitude and altitude of the fiber-optic gyroscope inertial navigation on the earth surface respectively; />And f m For the original data +.>For the angular rate raw data measured by a gyroscope component in the inertial navigation of the fiber-optic gyroscope, f m Adding specific force raw data measured by a speedometer component into fiber optic gyroscope inertial navigation; omega ie And g is the earth rotation angular velocity and the gravitational acceleration, respectively; r is R M And R is N The local earth's meridian radius and the mortise unitary radius are respectively;
the initial value of the inertial navigation calculation result when k=0 is obtained by the initial alignment process of the inertial navigation of the fiber-optic gyroscope; when k is more than or equal to 1, the real-time original data output at k moment is subjected to inertial navigation by the fiber-optic gyroscopeAnd->Inertial navigation calculation is carried out to obtain k moment inertial navigation calculation result +.>V k 、L k 、λ k And h k ；
Further according toAnd can be further from->Three attitude angles in the navigation result are obtained: α=acrsin (C 23 )，/>
Wherein C is 11 Is thatFirst column element of first row, C 12 Is->The first row and second column elements of C 13 Is->The third column element of the first row, C 21 Is->The first column element of the second row of C 22 Is->The second row and the second column elements of C 23 Is->And the third column element of the second row, C 31 Is->The third row and first column elements of C 32 Is->The third row and second column elements of C 33 Is->A third row and a third column element of (a); alpha is a pitch angle, beta is a roll angle, and gamma is a course angle; the symbol acrsin (·) represents an arcsine calculation, and the symbol arctan (·) represents an arctangent calculation; thus, it is possible to make the k time +.>Obtaining alpha at k time k 、β k And gamma k ；
S2, respectively fixing a temperature sensor and a magnetic sensor on an X-direction fiber optic gyro, a Y-direction fiber optic gyro and a Z-direction fiber optic gyro in the fiber optic gyro to acquire the temperature T of the X-direction fiber optic gyro in real time X And magnetic field strength M X Temperature T of Y-direction fiber optic gyroscope Y And magnetic field strength M Y And temperature T of Z-direction fiber optic gyroscope Z And magnetic field strength M Z The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the temperature sensor is preferably a digital temperature sensor with the model DS18B 20; the magnetic sensor is preferably an editable hall effect linear sensor model AH 810;
s3, judging whether signals of the fiber-optic gyroscope with the GPS or the post-configuration GPS are effective or not:
case 1: when the GPS signals are normally received and the number of the received GPS signals is more than or equal to 6, judging that the GPS is effective; in this case, step S4 to step S5 are executed, and the compensated navigation result is outputted;
case 2: when the GPS signals cannot be received or the GPS signals are normally received but the number of the satellites is less than 6, judging that the GPS fails; in this case, step S6 to step S7 are executed, and the compensated navigation result is output;
s4, performing integrated navigation on GPS output and output of fiber optic gyroscope inertial navigation, wherein the method comprises the following specific steps:
s401, constructing a state equation of a Kalman filter of the integrated navigation according to an error equation calculated by inertial navigation, wherein the expression is as follows:
wherein X is 15 Fifteen-dimensional state quantity for the combined navigation Kalman filter is expressed as follows:
wherein,east error angle for fiber optic gyroscope inertial navigation,>north error angle for inertial navigation of fiber optic gyroscope,>is the angle of the error of the inertial navigation of the fiber-optic gyroscope, delta V E Is the east velocity error, δV, of the inertial navigation of the fiber-optic gyroscope N North speed error, δV, of inertial navigation of fiber optic gyroscope U Is the space velocity error of the fiber optic gyroscope inertial navigation, delta L is the latitude error of the fiber optic gyroscope inertial navigation, delta lambda is the fiber optic gyroscopeThe longitude error and δh of the spiral inertial navigation are the altitude error and epsilon of the fiber-optic gyroscope inertial navigation x Zero offset error epsilon of X-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope y Zero offset error epsilon of Y-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope z Zero offset error of Z-direction gyro for inertial navigation of fiber-optic gyro,>zero offset error of X-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of Y-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of the Z-direction accelerometer which is the inertial navigation of the fiber-optic gyroscope;
F 15 is a state transition matrix, and the expression is as follows:
wherein F is 11 、F 12 、F 13 、F 21 、F 22 、F 13 、F 32 、F 33 As a non-zero matrix element of the matrix,
wherein L is latitude, lambda is longitude, and h is altitude; v (V) E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; r is R M And R is N The local earth meridian radius and the mortise unitary circle radius are respectively; omega ie Is the rotation angular rate of the earth;and->The east-direction specific force, the north-direction specific force and the sky-direction specific force are respectively measured by an optical fiber gyroscope inertial navigation accelerometer;the attitude matrix is a land strapdown inertial navigation;
G 15 to measure the noise input matrix, the expression is:
u is measurement noise, and its expression is:wherein u is g Measurement noise for fiber optic gyroscope, u g ＝[u gx u gy u gz ] T ，u gx Measurement noise of X-direction fiber optic gyroscope, u gy Measurement noise of Y-direction fiber optic gyroscope, u gz Measuring noise of the Z-direction fiber optic gyroscope; u (u) a U is the measurement noise of the accelerometer a ＝[u ax u ay u az ] T ，u ax Measurement noise for an X-direction accelerometer, u ay Measurement noise for Y-direction accelerometer, u az Measuring noise for the Z-direction accelerometer;
s402, constructing a measurement equation of a Kalman filter of the integrated navigation, wherein the expression is as follows:
Z＝HX 15 +υ，
wherein Z is an observation vector, Z= [ V ] E -V GE ,V N -V GN ,V U -V GU ,L-L G ,λ-λ G ,h-h G ] T Wherein V is E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; v (V) GE 、V GN 、V GU The GPS signal is the east speed, the north speed and the sky speed in the GPS signal; l, lambda and h are latitude, longitude and altitude of the optical fiber inertial navigation output respectively; l (L) G 、λ G And h G Latitude, longitude and altitude in the GPS signal, respectively; h is an observation matrix, and the expression is:I 3 is a unit matrix with three rows and three columns, +.>0 3×3 Zero matrix of three rows and three columns, 0 3×6 A zero matrix with three rows and six columns; v is observation noise;
s403, solving the state equation constructed in the step S401 and the observation equation constructed in the step S402 in real time by using a Kalman filtering algorithm to obtain a state quantity X in a real-time fifteen-dimensional integrated navigation Kalman filter 15 ；
S404, the inertial navigation solution obtained in step S1, namely alpha k 、β k 、γ k 、L k 、λ k And h k And respectively subtracting corresponding state quantities of nine navigation result errors in the real-time fifteen-dimensional combined navigation Kalman filter from the nine navigation results: />δV E 、δV N 、δV U Performing navigation error compensation on δL, δλ and δh to obtain a navigation result of the integrated navigation: alpha k '、β k '、γ k '、V k '、L k '、λ k ' and h k 'A'; in particular, the method comprises the steps of,
L k '＝L k -δL，
λ k '＝λ k -δλ，
h k '＝h k -δh；
the navigation result of the integrated navigation in the step S404 is the navigation result after compensation under the condition that the GPS is valid;
s5, constructing a fiber-optic gyroscope magnetic temperature cross-linking coupling error model, and training the model by taking the temperature and the magnetic field intensity of the three fiber-optic gyroscopes acquired in the step S2 as input data and taking the zero offset of the gyroscope obtained in the step S4 as output data;
specifically, the specific implementation manner of step S5 is as follows:
s501, constructing a fiber-optic gyroscope magnetic temperature cross-linking coupling error model based on an integrated learning algorithm, wherein an individual learner adopts a decision tree algorithm learner, and the learner combines with an algorithm Bagging algorithm;
s502, training the model:
1) For an X-direction fiber optic gyroscope: temperature T of X-direction fiber optic gyroscope acquired in step S2 X And magnetic field strength M X For inputting data, zero offset error estimated value epsilon of X-direction fiber optic gyroscope in state quantity in fifteen-dimensional combined navigation Kalman filter obtained in step S403 x The method comprises the steps of obtaining zero offset error of an X-direction fiber optic gyroscope and a prediction model of temperature and magnetic field intensity of the X-direction fiber optic gyroscope by training input and output data through an integrated learning algorithm for outputting data;
2) For Y-direction fiber optic gyroscope: temperature T of Y-direction fiber optic gyroscope acquired in step S2 Y And magnetic field strength M Y For inputting data, zero offset error estimated value epsilon of Y-direction fiber optic gyroscope in state quantity in fifteen-dimensional combined navigation Kalman filter obtained in step S403 y The method comprises the steps of obtaining a prediction model of zero offset error of a Y-direction fiber optic gyroscope and temperature and magnetic field intensity of the Y-direction fiber optic gyroscope by training input and output data through an integrated learning algorithm for outputting data;
3) For a Z-direction fiber optic gyroscope: temperature T of Z-direction fiber optic gyroscope acquired in step S2 Z And magnetic field strength M Z For inputting data, zero offset error estimated value epsilon of Z-direction fiber optic gyroscope in state quantity in fifteen-dimensional combined navigation Kalman filter obtained in step S403 z For outputting data, training the input and output data by using an integrated learning algorithm to obtain a prediction model of the zero offset error of the Z-direction fiber-optic gyroscope and the temperature and magnetic field intensity of the Z-direction fiber-optic gyroscope;
through the step S5, the fiber-optic gyroscope magnetic temperature cross-linking coupling error model can be continuously trained under the condition that the GPS signal is effective, so that the trained fiber-optic gyroscope magnetic temperature cross-linking coupling error model can be directly utilized under the condition that the GPS signal is ineffective, and zero offset caused by the fiber-optic gyroscope magnetic temperature cross-linking coupling error can be accurately predicted;
s6, substituting the temperature and the magnetic field intensity of the three optical fiber gyroscopes acquired in the step S2 into a magnetic temperature cross-linking coupling error model of the optical fiber gyroscopes so as to obtain a zero offset predicted value caused by the magnetic temperature cross-linking coupling error of the optical fiber gyroscopes; in particular, the method comprises the steps of,
for an X-direction fiber optic gyroscope: to be used forS2, acquiring temperature T of X-direction fiber optic gyroscope X And magnetic field strength M X For inputting data, substituting the zero offset error of the X-direction fiber optic gyroscope obtained in the step S5 and a prediction model of the temperature and the magnetic field strength of the zero offset error of the X-direction fiber optic gyroscope, so as to obtain the zero offset error epsilon 'of the X-direction fiber optic gyroscope, which is caused by the predicted magneto-thermal coupling when the GPS is invalid' x ；
For Y-direction fiber optic gyroscope: temperature T of Y-direction fiber optic gyroscope acquired in step S2 Y And magnetic field strength M Y And (3) substituting the zero offset error of the Y-direction fiber optic gyroscope obtained in the step (S5) and a prediction model of the temperature and the magnetic field strength of the Y-direction fiber optic gyroscope for inputting data to obtain the zero offset error epsilon 'of the Y-direction fiber optic gyroscope caused by the predicted magneto-thermal coupling when the GPS is invalid' y ；
For a Z-direction fiber optic gyroscope: temperature T of Z-direction fiber optic gyroscope acquired in step S2 Z And magnetic field strength M Z For inputting data, substituting the Z-direction fiber optic gyroscope zero bias error obtained in the step S5 and a prediction model of the temperature and the magnetic field strength of the Z-direction fiber optic gyroscope zero bias error to obtain the Z-direction fiber optic gyroscope zero bias error epsilon 'caused by the predicted magneto-thermal coupling when the GPS is invalid' z ；
S7, compensating the navigation result obtained by the solution in the step S1 by using a zero offset predicted value caused by the magnetic temperature cross-linking coupling error of the fiber-optic gyroscope obtained in the step S6 to obtain a compensated navigation result;
specifically, the zero offset compensation vector of the gyroscope is recorded as epsilon '= [ epsilon ]' x ε′ y ε′ z ] T Wherein ε' x Zero offset error epsilon 'of X-direction fiber optic gyroscope predicted in step S6' y Zero offset error epsilon 'of Y-direction fiber optic gyroscope predicted in step S6' z The Z-direction fiber optic gyroscope zero offset error predicted in the step S6 is obtained;
in the inertial navigation solution equation in step S1Compensating for->The calculation formula is as follows:
/>
in the method, in the process of the invention,for compensating the angular rate vector measured by the fiber optic gyroscope before,/>Measuring an angular rate vector for the compensated fiber optic gyroscope; in the compensation process, other physical quantities in the inertial navigation solution equation in the step S1 are unchanged;
and then willSubstituting the GPS magnetic temperature cross-linking coupling error compensation parameter into an inertial navigation solution equation to obtain a navigation result subjected to the magnetic temperature cross-linking coupling error compensation of the fiber-optic gyroscope under the condition that the GPS is invalid, wherein the navigation result comprises the following steps: alpha k '、β k '、γ k '、V k '、L k '、λ k ' and h k '。
In order to verify the correctness and the accuracy of the online compensation method of the magnetic temperature cross-linking coupling error of the fiber optic gyroscope, a set of land fiber optic gyroscope is selected for carrying out vehicle-mounted test. Specifically, a selected fiber optic gyroscope inertial navigation and a set of GPS are installed on a test vehicle; the optical fiber gyro inertial navigation specifically comprises three optical fiber gyroscopes with zero offset stability of 0.003 degrees/h and three accelerometers with zero offset stability of 10 mug; meanwhile, a temperature sensor and a magnetic sensor are respectively fixed on an X-direction fiber optic gyroscope, a Y-direction fiber optic gyroscope and a Z-direction fiber optic gyroscope in the fiber optic gyroscope, and the temperature sensor is a digital temperature sensor with the model DS18B 20; the magnetic sensor is specifically an editable hall effect linear sensor model AH 810.
The vehicle-mounted test method is designed as follows: starting a dynamic test after the optical fiber gyroscope inertial navigation alignment is completed, wherein the total time of the dynamic test is 12.5 hours, compensating the magnetic temperature cross-linking coupling error by using the method to obtain a compensated navigation result, and obtaining latitude error and longitude error of the optical fiber gyroscope inertial navigation after the magnetic temperature cross-linking coupling error compensation by using GPS information as a reference; test data were kept during the test. After the test is finished, as a comparison reference, firstly, calculating a navigation result by using inertial navigation without adopting the method of the application and obtaining an uncompensated latitude error and longitude error of the inertial navigation of the fiber optic gyroscope by using GPS information as a reference; then, after the data stored in the test process are subjected to magneto-thermal cross-linking coupling error compensation by using the method, the latitude error and the longitude error of the compensated fiber optic gyroscope inertial navigation are calculated.
FIG. 2 is a schematic diagram of the fiber optic gyroscope inertial navigation method in the embodiment for compensating the latitude errors before and after the compensation in the dynamic test by using the method of the application; FIG. 3 is a schematic diagram of the inertial navigation of the fiber optic gyroscope of this embodiment using the method of the present application to compensate for pre-and post-compensation longitude errors in dynamic experiments; as is obvious from comparing fig. 2 and fig. 3, by using the method of the present application to compensate the magneto-thermal cross-linking coupling error of a certain fiber optic gyroscope inertial navigation, the maximum latitude error is reduced from 0.97Km to 0.83Km, the latitude precision is improved by 14.4%, the maximum longitude error is reduced from 0.76Km to 0.68Km, and the longitude precision is improved by 10.5%; therefore, the online compensation method for realizing the magnetic temperature cross-linking coupling error of the fiber-optic gyroscope by adopting the method has certain correctness and accuracy, and the online compensation mode is simple, easy to operate and good in practicability.
The invention, in part, is not disclosed in detail and is well known in the art. While the foregoing describes illustrative embodiments of the present invention to facilitate an understanding of the present invention by those skilled in the art, it should be understood that the present invention is not limited to the scope of the embodiments, but is to be construed as protected by all the inventions by the appended claims insofar as such variations are within the spirit and scope of the present invention as defined and defined by the appended claims.
Claims (4)
1. An online compensation method for a magnetic temperature cross-linking coupling error of an optical fiber gyroscope is characterized by comprising the following steps:
s1, adopting a discretization recurrence algorithm suitable for computer calculation to carry out inertial navigation calculation on the output of an optical fiber gyroscope and an accelerometer in the inertial navigation of the optical fiber gyroscope so as to obtain an inertial navigation calculation result at the moment k in real time: alpha k 、β k 、γ k 、L k 、λ k And h k ；
S2, respectively fixing a temperature sensor and a magnetic sensor on an X-direction fiber optic gyro, a Y-direction fiber optic gyro and a Z-direction fiber optic gyro in the fiber optic gyro to acquire the temperature T of the X-direction fiber optic gyro in real time X And magnetic field strength M X Temperature T of Y-direction fiber optic gyroscope Y And magnetic field strength M Y And temperature T of Z-direction fiber optic gyroscope Z And magnetic field strength M Z ；
S3, judging whether signals of the fiber-optic gyroscope with the GPS or the post-configuration GPS are effective or not:
case 1: when the GPS signals are normally received and the number of the received GPS signals is more than or equal to 6, judging that the GPS is effective, executing the steps S4 to S5, and outputting a compensated navigation result;
case 2: when the GPS signals cannot be received or the GPS signals are normally received but the number of the satellites is less than 6, judging that the GPS is invalid, executing the steps S6 to S7, and outputting a compensated navigation result;
s4, performing integrated navigation on the GPS output and the output of the fiber optic gyroscope inertial navigation; wherein,
s401, constructing a state equation of a Kalman filter of the combined navigation according to an error equation calculated by inertial navigation:wherein X is 15 For a fifteen-dimensional state quantity of the integrated navigation kalman filter,wherein (1)>East error angle for fiber optic gyroscope inertial navigation,>north error angle for inertial navigation of fiber optic gyroscope,>is the angle of the error of the inertial navigation of the fiber-optic gyroscope, delta V E Is the east velocity error, δV, of the inertial navigation of the fiber-optic gyroscope N North speed error, δV, of inertial navigation of fiber optic gyroscope U Is the radial velocity error of the fiber-optic gyroscope inertial navigation, delta L is the latitude error of the fiber-optic gyroscope inertial navigation, delta lambda is the longitude error of the fiber-optic gyroscope inertial navigation, delta h is the altitude error of the fiber-optic gyroscope inertial navigation, epsilon x Zero offset error epsilon of X-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope y Zero offset error epsilon of Y-direction fiber optic gyroscope for inertial navigation of fiber optic gyroscope z Zero offset error of Z-direction gyro for inertial navigation of fiber-optic gyro,>zero offset error of X-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of Y-direction accelerometer for inertial navigation of Fiber Optic Gyroscope (FOG)>Zero offset error of the Z-direction accelerometer which is the inertial navigation of the fiber-optic gyroscope;
F 15 is a state transition matrix, and the expression is as follows:
wherein L is latitude, lambda is longitude, and h is altitude; v (V) E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; r is R M And R is N The local earth meridian radius and the mortise unitary circle radius are respectively; omega ie Is the rotation angular rate of the earth;and->The east-direction specific force, the north-direction specific force and the sky-direction specific force are respectively measured by an optical fiber gyroscope inertial navigation accelerometer; />The attitude matrix is a land strapdown inertial navigation;
G 15 in order to measure the noise input matrix,u is measurement noise, < >>Wherein u is g Measurement noise for fiber optic gyroscope, u g ＝[u gx u gy u gz ] T ，u gx Measurement noise of X-direction fiber optic gyroscope, u gy Measurement noise of Y-direction fiber optic gyroscope, u gz Measuring noise of the Z-direction fiber optic gyroscope; u (u) a U is the measurement noise of the accelerometer a ＝[u ax u ay u az ] T ，u ax Measurement noise for an X-direction accelerometer, u ay Measurement noise for Y-direction accelerometer, u az Measuring noise for the Z-direction accelerometer;
s402, constructing a measurement equation of a Kalman filter of the integrated navigation: z=hx 15 +υ，
Wherein Z is an observation vector, Z= [ V ] E -V GE ,V N -V GN ,V U -V GU ,L-L G ,λ-λ G ,h-h G ] T Wherein V is E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; v (V) GE 、V GN 、V GU The GPS signal is the east speed, the north speed and the sky speed in the GPS signal; l, lambda and h are latitude, longitude and altitude of the optical fiber inertial navigation output respectively; l (L) G 、λ G And h G Latitude, longitude and altitude in the GPS signal, respectively; h is the observation matrix of the sample,I 3 is a unit matrix with three rows and three columns, +.>0 3×3 Zero matrix of three rows and three columns, 0 3×6 A zero matrix with three rows and six columns; v is observation noise;
s403, solving the state equation constructed in the step S401 and the observation equation constructed in the step S402 by using a Kalman filtering algorithm to obtain a state quantity X in a real-time fifteen-dimensional integrated navigation Kalman filter 15 ；
S404, the inertial navigation solution obtained in step S1, namely alpha k 、β k 、γ k 、L k 、λ k And h k Corresponding state quantities of nine navigation result errors in the real-time fifteen-dimensional combined navigation Kalman filter are respectively subtracted, namelyδV E 、δV N 、δV U δl, δλ, δh to obtain a navigation result of the combined navigation, i.e. α, by navigation error compensation k '、β k '、γ k '、V k '、L k '、λ k ' and h k '；
S5, constructing a fiber optic gyroscope magnetic temperature cross-linking coupling error model based on an integrated learning algorithm, taking the temperature and the magnetic field intensity of the three fiber optic gyroscopes acquired in the step S2 as input data, taking the gyro zero bias estimated by the combined navigation obtained in the step S4 as output data, respectively obtaining a prediction model of an X-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof, a prediction model of a Y-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof, and a prediction model of a Z-direction fiber optic gyroscope zero bias error and the temperature and the magnetic field intensity thereof through training;
s6, substituting the temperature and the magnetic field intensity of the three optical fiber gyroscopes acquired in the step S2 into a prediction model of zero bias errors of the X-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the three optical fiber gyroscopes, a prediction model of zero bias errors of the Y-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the Y-direction optical fiber gyroscopes, and a prediction model of zero bias errors of the Z-direction optical fiber gyroscopes and the temperature and the magnetic field intensity of the Z-direction optical fiber gyroscopes, so as to obtain zero bias errors epsilon 'of the X-direction optical fiber gyroscopes, which are caused by magnetic temperature cross-linking coupling errors of the optical fiber gyroscopes, respectively' x Zero offset error epsilon 'of Y-direction fiber optic gyroscope' y And zero offset error epsilon 'of Z-direction fiber optic gyroscope' z ；
S7, utilizing the zero offset predicted value epsilon '= [ epsilon ] obtained in the step S6' x ε′ y ε′ z ] T In the solving equation of the step S1Compensating for->And then->Substituting the navigation result into an inertial navigation solution equation to obtain a compensated navigation result, wherein the method comprises the following steps: alpha k '、β k '、γ k '、V k '、L k '、λ k ' and h k '。
2. The online compensation method of the magnetic temperature cross-linking coupling error of the fiber-optic gyroscope according to claim 1, wherein in step S1, a solution formula of inertial navigation solution is:
L k ＝L k-1 +T s V Nk-1 /(R M +h k-1 )，
λ k ＝λ k-1 +T s V Ek-1 secL k-1 /(R N +h k-1 )，
h k ＝h k-1 +T s V Uk-1 ，
in the method, in the process of the invention, g n ＝[0 0 -g] T ，/>
wherein T is s The real-time sampling period of the original data is set; k is the discretized moment; the physical quantity of each symbol in the lower right-hand corner band k is represented as the state value of the physical quantity at time k, and the symbol in the lower right-hand corner band k-1 is represented as the physical state value at time k-1;v, L, lambda, h are inertial navigation solutions, +.>The attitude matrix is the inertial navigation of the fiber-optic gyroscope; v is the velocity vector of the fiber-optic gyroscope inertial navigation under the navigation coordinate system, and V= [ V ] E V N V U ] T ，V E 、V N And V U The east speed, the north speed and the sky speed of the fiber-optic gyroscope inertial navigation are respectively; l, lambda and h are latitude, longitude and altitude of the fiber-optic gyroscope inertial navigation on the earth surface respectively; />And f m For the original data +.>For the angular rate raw data measured by a gyroscope component in the inertial navigation of the fiber-optic gyroscope, f m Adding specific force raw data measured by a speedometer component into fiber optic gyroscope inertial navigation; omega ie And g is the earth rotation angular velocity and the gravitational acceleration, respectively; r is R M And R is N The local earth's meridian radius and the mortise unitary radius are respectively;
furthermore, according toThree attitude angles in the navigation result are obtained: pitch angle α=acrsin (C 23 ) Roll angle->Course angle->
3. The online compensation method of the magnetic temperature cross-linking coupling error of the fiber optic gyroscope according to claim 1, wherein in the step S2, the temperature sensor is preferably a digital temperature sensor with the model DS18B 20; the magnetic sensor preferably employs an editable hall effect linear sensor model AH 810.
4. The online compensation method of the fiber optic gyroscope magnetic temperature cross-linking coupling error according to claim 1, wherein in step S5, in constructing a fiber optic gyroscope magnetic temperature cross-linking coupling error model based on an integrated learning algorithm, an individual learner adopts a decision tree algorithm learner, and the learner combines with an algorithm Bagging algorithm.
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