CN113029127B - Aircraft autonomous attitude estimation method based on distributed circulating structure - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/04—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means
- G01C21/08—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by terrestrial means involving use of the magnetic field of the earth
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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Abstract
The invention provides an autonomous attitude estimation method of an aircraft based on a distributed circulation structure, which aims to solve the problems of difficult online operation and lower precision of an attitude estimation method based on a micromechanical gyroscope/TAM. Firstly, establishing an autonomous attitude estimation filter, substituting a micromechanical gyroscope and triaxial magnetometer data without correction errors, and obtaining the attitude of an aircraft at the current moment; then, establishing a TAM correction system by utilizing the solved gesture matrix at the current moment; and finally, inputting the error-free numerical value output by the TAM correction system into the attitude estimation system again, and estimating the attitude at the next moment.
Description
Technical Field
The invention belongs to the field of aircraft attitude estimation, and relates to an aircraft autonomous attitude estimation method based on a distributed circulation structure.
Background
Global satellite positioning systems have achieved tremendous success since their application. However, with the development of countermeasures, the outstanding disadvantage of poor concealment and susceptibility to interference from enemy electronic warfare is also revealed undoubtedly in multiple local warfare. Therefore, in order to further adapt to the current war, developing a reliable autonomous navigation mode without data link communication has become a problem to be solved. The micromechanical gyroscope does not need to transmit and receive signals in the working process, has good concealment and short-term precision, can provide all-weather continuous real-time navigation information, and becomes a necessary option of a navigation system. But at the same time has accumulated errors and needs other auxiliary information to be corrected in time. Triaxial magnetometers (Three Axis Magnetometer, TAM) are currently commonly used vector magnetic measurement sensors. The combination of the inertial navigation device and the micromechanical gyroscope has the advantages that the inertial navigation device is combined with the micromechanical gyroscope, so that the inertial navigation device maintains the all-weather and continuous navigation characteristics of the pure inertial navigation device; the passive measurement has good concealment, and exposure and interference by enemy are avoided during communication; the system has high precision, can provide multidimensional high-precision navigation information such as gesture, course, position and the like for the carrier, and has great application potential in the fields of military, security and the like.
However, since the accuracy of both sensors is relatively low, how to obtain a high attitude accuracy is a problem to be considered. The TAM actual working environment is greatly different from the off-line test, and the extreme temperature gradient, the mechanical pressure, the complex electromagnetic environment and the like have great influence on the state of the sensor, thereby playing an important role in the attitude precision. Some practical cases have also proven necessary to correct TAMs online to ensure that certain accuracy of pose determinations are obtained. But for the online correction problem the above approach is to parameterize into an extra added state. The implementation of such a full order filter has several difficulties: (1) The dimension of the state vector is large, which can bring calculation burden to real-time operation; (2) The state comprises a rapid change term and a gradual change term, and the parameters of the filter are difficult to adjust; (3) Because of the better observability of the TAM error correction parameters, metrology updates can adjust it better, which will result in scale factors and deviations being more sensitive to metrology noise, while pose is slower to react. It can be seen how to better correct TAM error parameters online while estimating pose is a key issue that needs to be addressed currently.
Aiming at the defects of the existing micromechanical gyroscope/TAM attitude estimation system, the invention provides a novel method for estimating the autonomous attitude of an aircraft based on a distributed circulating structure. The method divides the gesture estimation and the sensor correction into two parts, reduces the system dimension through the distributed double-circulation structure, and improves the gesture estimation precision.
Disclosure of Invention
The invention aims to solve the problems of micro-mechanical gyroscopes and low TAM precision, easy interference of an electromagnetic environment by TAM and more online estimation state dimensions, and provides a novel method for estimating the autonomous attitude of an aircraft based on a distributed circulation structure. The problems to be solved include:
(1) The dimension of the state vector is large, which can bring calculation burden to real-time operation;
(2) The state comprises a rapid change term and a gradual change term, and the parameters of the filter are difficult to adjust;
(3) Because of the better observability of the TAM error correction parameters, metrology updates can adjust it better, which will result in scale factors and deviations being more sensitive to metrology noise, while pose is slower to react.
The invention relates to an aircraft autonomous attitude estimation method based on a distributed circulating structure, which is characterized by comprising the following technical measures:
step one: establishing an aircraft attitude estimation system state equation and a triaxial magnetometer measurement model by using a discrete quaternion dynamics equation to establish an attitude estimation system observation equation, thereby completely constructing an aircraft attitude estimation system, solving the attitude estimation system to obtain an attitude quaternion, an attitude conversion matrix and a triaxial attitude at the current moment, converting a local geomagnetic field vector theoretical value into a carrier coordinate system by using the current moment attitude matrix, and differencing a local geomagnetic field vector value converted into the carrier coordinate system with a corrected triaxial magnetometer measurement value to obtain a geomagnetic field residual vector;
step two: constructing a triaxial magnetometer correction system observation equation by using residual vectors added with measurement noise, and constructing a triaxial magnetometer correction system state equation by using two error parameters of scale factor errors and zero deviations as system states, thereby constructing a complete triaxial magnetometer correction system, and estimating the state of the system at the current moment, namely error parameters by using a UKF filter;
step three: and correcting the three-axis magnetometer measured value by using the estimated error parameter at the current moment, substituting the corrected measured value into an aircraft attitude estimation system, and re-estimating the three-axis attitude.
Compared with the prior art, the autonomous attitude estimation method of the aircraft based on the distributed circulating structure has the beneficial effects that:
1) The whole system is divided into an attitude estimation system and a sensor correction system, so that the dimension of each filter is reduced, and the calculated amount and the burden of real-time operation are reduced;
2) The whole system is divided into an attitude estimation system and a sensor correction system, so that a rapid change item and a slow change item can be separated, and parameter adjustment is easy;
3) And when the attitude is estimated, TAM error parameters can be corrected, the influence of an airborne electromagnetic environment on TAM measurement is reduced, and the system accuracy is improved.
4) The combined attitude estimation system is constructed by adopting the micromechanical gyroscope and the TAM, so that the autonomous attitude estimation is realized while the cost is obviously reduced, and the concealment performance and the anti-decoy capability of the system are improved.
Drawings
FIG. 1 is a flow chart of steps of a method for estimating autonomous attitude of an aircraft based on a distributed loop structure;
fig. 2 is a block diagram of a distributed circulatory system.
Detailed Description
In order to solve the problems of difficult online operation and lower precision of the attitude estimation method based on the micromechanical gyroscope/TAM, the autonomous attitude estimation method of the aircraft based on the distributed circulating structure is provided. Firstly, establishing an autonomous attitude estimation filter, substituting a micromechanical gyroscope and triaxial magnetometer data without correction errors, and obtaining the attitude of an aircraft at the current moment; then, establishing a TAM correction system by utilizing the solved gesture matrix at the current moment; and finally, inputting the error-free numerical value output by the TAM correction system into the attitude estimation system again, and estimating the attitude at the next moment.
The invention is described in further detail below with reference to fig. 1 of the specification. Referring to fig. 1 of the specification, the process flow of the invention comprises the following steps:
(1) One-step prediction of attitude quaternion at current moment
Defining the gesture quaternion q as a four-dimensional vector:
q≡[q 0 ρ T ] T ，
wherein ρ≡[q1 q 2 q 3 ] T Is a vector part; q 0 Is scalar part, with
The gesture matrix a (·) represented by the quaternion q is as follows:
wherein ,I3×3 Is a unit matrix of 3 x 3,<ρ×>is an oblique symmetric matrix.
The quaternion differential equation is
The angular velocity omega is extracted by using the fiber optic gyroscope, and the output model of the angular velocity omega can be expressed as
ω＝ω-b-η a (2)
wherein ,ωg For the actual gyro output, ω is the true value, b is gyro drift, η a 、η b Mean 0 and variance 0
and />
Is a gaussian white noise of (c).
Equations (1), (2) and (3) may be discretized using the first order Dragon's base tower method.
(2) Construction of observation equation of attitude estimation system
Magnetic field vector B in the carrier coordinate system k And a magnetic field vector H in a geographic coordinate system k The relation of (2) is that
wherein ,
for the predicted value of the gesture quaternion at the current k moment, A (-) is a gesture conversion matrix from a geographic coordinate system to a carrier coordinate system, and B k H is the three-axis magnetometer measurements in the carrier coordinate system k Is the magnetic field vector value, v in the geographic coordinate system k In order to measure the noise of the light,
(3) Aircraft attitude estimation based on rolling horizon estimation
After the attitude estimation system model is established through the gyroscope and the TAM, consideration needs to be given to how the current optimal attitude estimation of the aircraft can be obtained according to the data of the sensor. The invention establishes a rolling time domain estimation model with equality constraint in consideration of the normalized property of the quaternion. The basic idea is that only a fixed amount of data before the current moment is considered, and the influence of the history data on the estimation is approximately described by a method, so that the amount of data participating in optimization each time is unchanged, and the method is realized like a rolling observation 'window'. This "window" contains past limited measurements, and the last output of the "window" is the current state estimate.
The last point of the window (i=l) represents the present moment k, and for convenience, the moment in the window is indicated by L2, …, L. The complete MHE problem with equality constraints can be expressed as
x i+1 ＝f i+1，i (x i ，u i )+w i ，for i＝1，…，L-1 (5)
y i+1 ＝h i+1 (x i+1 )+v i+1 ，for i＝1，…，L-1 (6)
l i (x i )＝0，for i＝1，…，L (7)
wherein ,xi Is the state to be estimated. Equation (5) describes the state recurrence process in the discrete case. U in the recurrence equation i Is a known input whose process noise is w i Process noise variance of Q i . Equation (6) is a measurement equation, y i For the measurement value v i 、R i The measured noise and the measured noise variance, respectively. State in time domain
Sum of variances->
Is a summary of the history information. C in formula (8) nt，k As a cost function, it describes the arrival cost. It is noted that the measurement at i=1 is not included in the cost function. It is assumed that all information derived from the measurements already contains the prior experimental estimate +.>
Is a kind of medium. Equation constraint l i Given by equation (7). The output of the MHE problem is x L : the estimated state vector for the last instant in the time domain "window".
This is a weighted least squares problem in which the weights are the inverse of the variance matrix:
the two-norm notation is adopted:
bringing equations (5), (6), and (7) into the cost function (4) yields the following equation:
s.t.
l i (x i )＝0，for i＝1，…，L
this converts the state estimation problem into a Nonlinear Programming (NPL) problem, which can be solved by numerical optimization, substituted into gyro data, and corrected for the measurement B 'of the triaxial magnetometer' m，k The optimal quaternion estimated value, the attitude matrix and the three-axis attitude of the aircraft at the current moment can be solved. The pose estimation process is updated with a magnetometer measurement period Δt.
(4) Solution of triaxial magnetometer measurement residual
Various error factors that limit the accuracy of the magnetometer may cause attitude estimation errors, and therefore the parameters of the sensor must be estimated online to exclude the effects of the sensor errors. The sensor correction process is to estimate the scale factor s at time k by using the residual of the attitude estimation phase k And zero offset d k . The error parameter is defined as Θ k ：
Θ k ＝[s x，k s y，k s z，k d x，k d y，k d z，k ] T
Order the
B is the optimal estimated value of the quaternion after filtering m，k Is the measurement of the magnetometer at time k. Assuming that the internal angular rate remains constant in the discrete intervalDetermining the magnetic field three-component measurement error vector deltay at that time k Namely the theoretical value of the local geomagnetic field vector under the machine body coordinate system>
Error corrected triaxial magnetometer measurements +.>
Difference between
(5) Estimation of error parameters for a triaxial magnetometer
Will delta y k After a certain number has been accumulated, it can be used to calibrate the sensor. Let n be the number of measurements accumulated in a cycle, then the measurement equation can be written as
z i ＝Δy i +r i ，i＝1，…，n (9)
wherein ,zi Is the error of the ith moment accumulated in one cycle, deltay i Is geomagnetic field residual vector, r i Is a corresponding noise which also has an effect on the attitude estimation error.
In discrete form, the state equation of the sensor correction system is
wherein ,bi Is a process noise term used to represent scale factors and the amount of change in zero offset. Filtering can be accomplished with the use of UKF for the sensor correction system established by equations (9) and (10).
In the above, scale factor s i And zero offset d i The two estimators can be initialized by corrected ground test data, and corrected by sensor correction process in carrier operation stage to obtain optimal estimated value at current time
(6) Correction of triaxial magnetometer measurements
When the optimal estimated value is obtained
Then, the measured value of the triaxial magnetometer can be corrected, and the method comprises the following steps:
obtaining corrected triaxial magnetometer measurements B' k，m . Substituting this value into the attitude estimation system loop, the aircraft attitude can be estimated.
Claims (3)
1. The aircraft autonomous attitude estimation method based on the distributed circulation structure is characterized by comprising the following steps of:
step one: establishing an aircraft attitude estimation system state equation and a triaxial magnetometer measurement model by using a discrete quaternion dynamics equation to establish an attitude estimation system observation equation, thereby completely constructing an aircraft attitude estimation system, solving the attitude estimation system to obtain an attitude quaternion, an attitude conversion matrix and a triaxial attitude at the current moment, converting a local geomagnetic field vector theoretical value into a carrier coordinate system by using the current moment attitude matrix, and differencing a local geomagnetic field vector value converted into the carrier coordinate system with a corrected triaxial magnetometer measurement value to obtain a geomagnetic field residual vector; geomagnetic field residual vector deltay k Is the theoretical value of local geomagnetic field vector in the machine body coordinate system
With error corrected triaxial magnetometer measurements
A difference between; which is a kind ofIn (I)>
H is the optimal estimated value of the quaternion after filtering k For the magnetic field vector value in the geographic coordinate system, A (-) is the attitude transformation matrix from the geographic coordinate system to the carrier coordinate system, B k,m For the measurement of the magnetometer at time k, d k Zero offset, s k Is a scale factor;
step two: constructing a triaxial magnetometer correction system observation equation by using residual vectors added with measurement noise, and constructing a triaxial magnetometer correction system state equation by using two error parameters of scale factor errors and zero deviations as system states, thereby constructing a complete triaxial magnetometer correction system, and estimating the state of the system at the current moment, namely error parameters by using a UKF filter;
step three: correcting the measured value of the triaxial magnetometer by using the estimated error parameter at the current moment, substituting the corrected measured value into an aircraft attitude estimation system, and re-estimating the triaxial attitude;
the method for constructing the observation equation of the triaxial magnetometer correction system in the second step comprises the following steps:
let n be the number of measurements accumulated in a cycle, then the observation equation is written as
z i ＝Δy i +r i ,i＝1,…,n
Where zi is the error at the ith time accumulated in one cycle, Δyi is the geomagnetic field residual vector, and ri is the corresponding noise;
the method for constructing the state equation of the triaxial magnetometer correction system in the second step comprises the following steps:
wherein ,si As a scale factor, d i Zero offset, b i Is a process noise term used to represent the scale factor and the variation of zero offset;
scale factor s i And zero offsetd i The two estimators are initialized by corrected ground test data, and are corrected by a sensor correction process in the carrier operation stage, so as to finally obtain the optimal estimated value at the moment
The measured value of the triaxial magnetometer is corrected by the following method:
obtaining corrected triaxial magnetometer measurements B' k,m Substituting the value into a posture estimation system loop to estimate the posture of the aircraft.
2. The method for estimating autonomous attitude of an aircraft based on a distributed cyclic structure according to claim 1, wherein the method for constructing the observation equation of the attitude estimation system in the step one is as follows:
wherein ,
for the predicted value of the gesture quaternion at the current k moment, A (-) is a gesture conversion matrix from a geographic coordinate system to a carrier coordinate system, and B k H is the three-axis magnetometer measurements in the carrier coordinate system k Is the magnetic field vector value, v in the geographic coordinate system k To measure noise.
3. The method for estimating autonomous attitude of an aircraft based on a distributed loop structure according to claim 1, wherein the method for solving the aircraft attitude estimation system in the step one is as follows:
substituting a discrete aircraft attitude estimation system into a rolling time domain estimation model, and solving the rolling time domain estimation model by adopting a Gaussian-Newton iteration method and combining an MEMS rate gyroscope and corrected three-axis magnetometer measurement values, so as to obtain an attitude quaternion, an attitude conversion matrix and a three-axis attitude at the current moment.
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