CN103913181B - A kind of airborne distributed POS Transfer Alignments based on parameter identification - Google Patents

Abstract

A kind of airborne distributed POS Transfer Alignments based on parameter identification.Airborne distributed POS is made up of the main POS of high accuracy and many sub- IMU.The problem of unknown and time-varying for body elastic deformation, body elastic deformation angle is considered as into second order markoff process, and the elastic deformation angle and elastic deformation angular speed are extended for into state variable, the difference of speed and attitude of main POS and sub- IMU is chosen to measure, the Mathematical Modeling of sub- IMU Transfer Alignments is set up；Secondly, Kalman filtering is carried out, using the elastic deformation angle and elastic deformation angular speed calculation that estimate and the parameter for updating second order markoff process；Finally using the second order markoff process parameter after renewal as subsequent time filtering initial value, so as to estimate more accurate sub- IMU attitude errors, velocity error and site error, using the strapdown calculation result of the sub- IMU of the error correction, more accurate sub- IMU positions, speed and attitude are calculated.

Description

A kind of airborne distributed POS Transfer Alignments based on parameter identification

Technical field

The present invention relates to a kind of airborne distributed POS Transfer Alignments based on parameter identification, can be used for various needs The strapdown inertial navigation system of position, speed and attitude is determined by transfer alignment technique, is particularly suitable for body and be there is bullet Property deformation situation.

Background technology

Multitask remote sensing load is one of current airborne earth observation developing direction, such as integrated high-resolution mapping camera, Imaging spectrometer, big visual field infrared scanner, synthetic aperture radar (Synthetic Aperture Radar, SAR) are in same The multitask load of carrier aircraft, airborne distributive array antenna SAR and flexible multi-baseline interference SAR etc..For equipment task remote sensing The high performance turbine remote sensing system of load, needs to realize high-acruracy survey to the kinematic parameter of each load distributed points.

Position and attitude measuring system (Position and Orientation System, POS) is at present airborne to see over the ground The Main Means that remote sensing load obtains the kinematic parameters such as position, speed, attitude are surveyed, which is mainly constituted including IMU, global positioning system System, navigational computer and the poster processing soft.It is comprehensively airborne for the high-performance for being equipped with multiple or various observation load to see over the ground Examining system, as multiple or various observation load are arranged on the diverse location of aircraft, aircraft elastic deformation causes the sky between load Between relativeness change.Now, traditional single POS obviously cannot meet the high-precision motion of different settlement multi-loads The demand of parameter measurement.Therefore, it is necessary to it is height to set up the distributed space-time datum system (airborne distributed POS system) of high accuracy In the airborne earth observation systems of performance synthesis, all load provide high-precision time, spatial information, its typical application load For distributive array antenna SAR.Distributed SAR antenna is distributed in wing both sides, needs to the position at each antenna, speed, appearance State and main and sub system baseline carry out high-acruracy survey.

Airborne distributed POS system is typically by the main POS of high accuracy and many sub- Inertial Measurement Unit (Inertial Measurment Unit, IMU) composition.Main POS is typically mounted in carrier aircraft cabin；The general distributing installation of sub- IMU is in body Diverse location (includes wing), carries out Transfer Alignment to which by kinematic parameters such as the high precision position of main POS, speed, attitudes To realize the accurate measurement of movable information at place.As airframe has elastic deformation, except certainty between master subsystem Lever arm error and fix error angle beyond, also there is time dependent random lever arm error and elastic deformation angle.Wherein with The random lever arm error of time change and elastic deformation angle, do not simply fail to accurate measurement, and can be in main and sub system Transfer Alignment It is middle to introduce complicated random error, so that sub- IMU movement parameter measurements precise decreasing.Accordingly, it would be desirable in Transfer Alignment process In the elastic deformation of aircraft is estimated and is compensated.

Elastic deformation in practical flight has two kinds, and a kind of is due to the deflection deformation produced by fighter maneuver, another kind It is vibration source or fitful wind etc. make that carrier aircraft is produced inside carrier aircraft vibration deformation, both deformations typically can be regarded as mistake at random Journey.The existing method compensated to elastic deformation angle mainly has three kinds：First method is to simulate body bullet using software Property motion model, for example the patent of Publication No. 201210113395 using ANSYS aid in modeling method simulation wing elasticity Deform, but the model set up by the method changes with the change of aircraft material, and plug-in load is not accounted for aircraft bullet Property deformation impact.Second method is to adopt to increase Kalman filter process noise matrix to reduce body deformation and vibration Impact.The method be according to true model analysis of covariance result come determine injection white noise intensity, i.e., by increase Process noise carrys out the deflection deformation of compensating Modeling.The method can also increase wave filter in addition to it can compensate flex motion Robustness, but to reduce (Kain J.E., Cloutier J.R..Rapid of the precision of Transfer Alignment as cost transfer alignment for tactical weapon applications[C].AIAA Guidance, Navigation and Control Conference.1989:1290-1300.).The third method is empirical modeling method, And more conventional method, will body elastic deformation angle be idealized as the markoff process of second order or three ranks, and by its Augmentation for Kalman filtering state variable, by Kalman Filter Estimation go out the elastic deformation angle and compensate (Li Duanchang, Zhong Maiying, Guo Dingfei. the error detection and compensation [C] in distributed POS Transfer Alignments. the 25th Chinese Control and decision making meeting Collection of thesis .2013:4194-4199.).But the method exist problem be above-mentioned parameter selection more empirically determine, in reality The accuracy of the parameter is difficult to ensure that in engineer applied.Additionally, the markoff process parameter at body elastic deformation angle is in aircraft Can change with extraneous factor in flight course, even if can rule of thumb provide corresponding process ginseng in the filtering incipient stage Number, cannot guarantee that the accuracy of System State Model and noise statisticses in filtering, and filtering accuracy will decline very To appearance diverging.

The content of the invention

The present invention technology solve problem be：Overcome the deficiencies in the prior art, propose a kind of based on the airborne of parameter identification Distributed POS Transfer Alignments, the method can improve the Transfer Alignment essence that carrier aircraft body has distributed POS during elastic deformation Degree.

The present invention technical solution be：A kind of airborne distributed POS Transfer Alignments based on parameter identification.Its Comprise the following steps that：

(1) body elastic deformation angle is considered as into second order markoff process, is set up comprising sub- IMU ins errors model and angle The Transfer Alignment error model of error model；

(2) body elastic deformation angle and elastic deformation angular speed are extended for into state variable, and by high accuracy main POS and son The difference of the speed and attitude of IMU sets up the Mathematical Modeling of sub- IMU Transfer Alignments as measurement；

(3) t is gone out using Kalman Filter Estimation_kThe elastic deformation angle at momentWith elastic deformation angular speedK=0,1, 2 ..., N-1, using what is estimatedWithIn line computation and update description elastic deformation angle second order markoff process ginseng Number；

(4) using the second order markoff process parameter after renewal as subsequent time t_k+1Filtering initial value, using karr Graceful filtering estimates more accurate t_k+1The sub- IMU attitude errors at moment, velocity error and site error, using above-mentioned error The strapdown calculation result of sub- IMU is corrected, t is obtained_k+1The position of Shi Kezi IMU, speed and attitude.

In above-mentioned steps (1), Transfer Alignment error model includes that the angle between sub- IMU ins errors model and master subsystem is missed Differential mode type.Specifically Transfer Alignment error modeling step is：

1) set up sub- IMU ins errors model

The definition of coherent reference coordinate system includes：Note i is geocentric inertial coordinate system；E is terrestrial coordinate system；Main POS and son IMU navigational coordinate systems are northeast day geographic coordinate system, respectively with n and n₁Represent；Carrier coordinate system origin be carrier center of gravity, x Along carrier transverse axis to the right, before carrier Y, along carrier vertical pivot upwards, the coordinate system is fixed on carrier z-axis y-axis axle, claims For upper carrier coordinate system before the right side, the carrier coordinate system of main POS and sub- IMU is represented respectively with a and b；According to above-mentioned definition, sub- IMU Ins error model is：

A) the attitude error differential equation：

B) the velocity error differential equation：

C) the site error differential equation：

D) the inertia type instrument error differential equation：

WhereinFor sub- IMU attitudes misalignment, φ_E、φ_NAnd φ_URespectively east orientation, north orientation, day To misalignment, subscript E, N and U represent respectively east orientation, north orientation and day to；It is the angle speed of relative inertness system for sub- IMU navigation Degree；ForError angular speed；The attitude battle array of its navigation system is tied to for sub- IMU carriersEstimate；WithRespectively sub- IMU speed and velocity error, wherein V_E、V_N And V_URespectively east orientation, north orientation and sky orientation speed, δ V_E、δV_NWith δ V_URespectively east orientation, north orientation and sky orientation speed error；It is the specific force of sub- IMU, wherein f_E、f_NAnd f_URespectively east orientation, north orientation and day are to specific force；WithThe angular speed and its error of respectively sub- IMU navigation system terrestrial coordinate system relatively；WithRespectively sub- IMU navigation The angular speed and its error of the relative terrestrial coordinate system of system；L, λ, H and δ L, δ λ, δ H is respectively sub- IMU latitudes, longitude, height and latitude Degree error, longitude error, height error；For the first derivative of latitude,For The first derivative of longitude；R_MAnd R_NRespectively along meridian circle and the principal radius of curvature of prime vertical；ε^b=[ε_x ε_y ε_z]^TWithRespectively sub- IMU gyroscope constant value drifts count constant value biasing, wherein ε with adding_x、ε_yAnd ε_zIt is respectively sub IMU carriers system x-axis, y-axis and z-axis gyroscope constant value drift, whereinWithRespectively sub- IMU carriers system x-axis, y-axis and z Axle adds meter constant value biasing.

2) set up the angle error model between master subsystem

A) fixedly mount the differential equation of error angle ρ：

Wherein ρ=[ρ_x ρ_y ρ_z]^TError angle, ρ are fixedly mounted for sub- IMU_x、ρ_yAnd ρ_zRespectively sub- IMU carriers system x-axis, y Axle and z-axis fix error angle.

B) differential equation at elastic deformation angle：

Wherein θ_jFor the elastic deformation angle on sub- IMU carriers system jth axle, j=x, y, z, θ=[θ_x θ_y θ_z]^TFor elasticity change Shape angle；β_j=2.146/ τ_j, τ_jFor second order markoff process correlation time；η_jFor zero-mean white noise, its varianceMeet：

σ_j ²For elastic deformation angle θ_jVariance, β j andTo describe the ginseng of the second order markoff process of elastic deformation angle θ Number.

The sub- IMU Transfer Alignments Mathematical Modeling that above-mentioned steps (2) are set up is：

Z=HX+V

Wherein systematic state variable X is：

X=[X₁ X₂]^T

System transfer matrix F can be determined by the Transfer Alignment error model of sub- IMU；System noiseWhereinWithRespectively sub- IMU carriers system x-axis, y-axis, z-axis gyro and sub- IMU carriers system x-axis, y-axis, z-axis acceleration The random error of meter, not including random constant error；White Gaussian noise of system noise W for zero-mean, its variance matrix Q is by gyro Constant value drift, plus meter constant value biasing and second order markoff process parameter Q_ηjDetermine；The expression formula of system noise acoustic matrix G is：

WhereinThe pose transformation matrix of navigation system is tied to for sub- IMU carriers.

System measurements variable Z=[δ ψ δ θ δ γ δ V '_E δV′_N δV′_U]^T, wherein δ ψ, δ θ, δ γ and δ V '_E、δV′_N、δ V′_UThe course angle of respectively sub- IMU and main POS, the angle of pitch, the difference of roll angle and east orientation, north orientation, the difference of sky orientation speed；Measure NoiseWherein v_δψ、v_δθ、v_δγPOS course angles based on respectively, the angle of pitch, The measurement noise of roll angle,POS east orientations, north orientation, the measurement noise of sky orientation speed based on respectively；V is The white Gaussian noise of zero-mean, its variance matrix R by main POS position and velocity accuracy determine；Measurement matrix H is：

Make main POS attitude matrixsNoteFor matrix T_aIn l rows, m row element, l=1,2,3, m= 1,2,3；Then in above formulaWithExpression formula be：

T at the sub- IMU mount points of utilization adopted by above-mentioned steps (3)_kThe elastic deformation angular estimation value at momentWith elastic deformation Attitude rate estimator valueOn-line identification describes elastic deformation The second order markoff process parameter beta at angle_jWithConcretely comprise the following steps：

1) determine valid data θ_jWith

NoteWithValid data number be Loop, initial t₀Moment Loop=1；

Work as t_kMoment elastic deformation Attitude rate estimator valueMeetWhen, Loop=Loop+1,Conversely, Loop=1,Wherein []_kMiddle subscript k represents t_kMoment, D () represent variance, γ₁=2 And γ₂=0.1 is respectively upper bound threshold parameter and lower bound threshold parameter；

2) calculate t_kMoment parameterWith

Initial t₀Moment, β_jWithInitial value isWith

A) utilize vector θ_jWithCalculate varianceAnd covariance

B) giving iterative initial value isWith Newton Algorithm it is as follows with β_jFor the nonlinear equation of independent variable, Second order markoff process parameter is obtainedWith

WhereinNote

3) parameterThe Effective judgement of estimated result

Work as t_kMoment parameter beta_jEstimateIt is unsatisfactory forWhen, order

Using the second order markoff process parameter after renewal as subsequent time t in above-mentioned steps (4)_k+1Filtering it is initial Value, goes out sub- IMU attitude errors, velocity error and site error using Kalman Filter Estimation, finally corrects sub- IMU strapdowns and resolves As a result the step of is：

1) attitude error, velocity error and the site error of sub- IMU are estimated

By t_kThe second order markoff process parameter that moment calculatesWithAs subsequent time t_k+1Filtering Initial value, goes out t using Kalman Filter Estimation_k+1The sub- IMU the misaligned angle of the platform φ at moment_E、φ_N、φ_U, velocity error δ V_E、δV_N、 δV_UWith site error δ L, δ λ, δ H；

2) using the strapdown calculation result of the sub- IMU of above-mentioned error correction, obtain t_k+1The sub- IMU positions at moment, speed and appearance State

A) speed amendment

WhereinWithThe revised east orientation of respectively sub- IMU, north orientation and sky orientation speed；WithRespectively sub- IMU strapdowns resolve east orientation, north orientation and the sky orientation speed for obtaining；δV_E、δV_NWith δ V_URespectively For t_k+1The sub- IMU strapdowns that moment Kalman Filter Estimation goes out resolve east orientation, north orientation and sky orientation speed error；

B) position correction

L^new=L^old-δL

λ^new=λ^old-δλ

H^new=H^old-δH

Wherein L^old、λ^oldAnd H^oldRespectively sub- IMU strapdowns resolve latitude, the longitude and altitude for obtaining；L^new、λ^newAnd H^new The revised latitude of respectively sub- IMU, longitude and altitude；δ L, δ λ and δ H are respectively t_k+1The son that moment Kalman Filter Estimation goes out IMU strapdowns resolve latitude, longitude and altitude error；

C) attitude rectification

Calculate t_k+1Shi Kezi IMU geographic coordinate systems n₁With computed geographical coordinates n '₁Between transition matrix

Calculate t_k+1Shi Kezi IMU carrier coordinate systems b and true geographic coordinate system n₁Between transition matrix

WhereinFor t_k+1Shi Kezi IMU strapdowns resolve the attitude matrix for obtaining；

By the attitude battle array of the sub- IMU after being updatedCalculate t_k+1Course angle ψ of Shi Kezi IMU_s, pitching angle theta_sAnd roll Angle γ_s, willIt is designated as

Wherein T_lmFor matrixIn l rows, m row element, l=1,2,3, m=1,2,3；Then sub- IMU course angles ψ_s、 Pitching angle theta_sWith roll angle γ_sMain value, i.e. ψ_{S master}、θ_{S master}And γ_{S master}Respectively：

θ_{S master}=arcsin (T₃₂)

Due to course angle ψ_s, pitching angle theta_sWith roll angle γ_sSpan be respectively defined as [0,2 π],[- π ,+π]；So, ψ_s、θ_sAnd γ_sTrue value can be determined by following formula：

θ_s=θ_{S master}

It is modified by the speed of antithetical phrase IMU, position and attitude, more accurate sub- IMU mount points can be obtained Speed, position and attitude information, complete Transfer Alignment.

Present invention advantage compared with prior art is：

For the markoff process unknown parameters and the problem of time-varying of body elastic deformation described in practical application, utilize In Transfer Alignment the speed and attitude information of the main POS of high accuracy can the advantage that is modified of antithetical phrase IMU state variables, profit The elastic deformation angle that gone out with Kalman Filter Estimation and elastic deformation angular speed calculating markoff process parameter, so as to realize The on-line identification of the parameter.Overcome preset parameter method that is traditional, empirically determining and cannot truly describe body elasticity Deformation cause Transfer Alignment precision low deficiency, and not by carrier aircraft material constraint and whether plug-in load is affected, raising The accuracy of System State Model and noise statisticses, so as to improve the precision of Transfer Alignment.

Description of the drawings

Fig. 1 is the flow chart of the present invention；

Fig. 2 is the flow chart of the second order markoff process parameter identification method of the present invention；

Specific embodiment

As shown in figure 1, the concrete grammar of the present invention implements as follows：

1st, set up the Transfer Alignment error model comprising angle error model between sub- IMU ins errors model and master subsystem

Specifically Transfer Alignment error modeling step is：

(1) set up sub- IMU ins errors model

The definition of coherent reference coordinate system includes：Note i is geocentric inertial coordinate system；E is terrestrial coordinate system；Main POS and son IMU navigational coordinate systems are northeast day geographic coordinate system, respectively with n and n₁Represent；Carrier coordinate system origin be carrier center of gravity, x Along carrier transverse axis to the right, before carrier Y, along carrier vertical pivot upwards, the coordinate system is fixed on carrier z-axis y-axis axle, claims For upper carrier coordinate system before the right side, the carrier coordinate system of main POS and sub- IMU is represented respectively with a and b；According to above-mentioned definition, sub- IMU Ins error model is：

A) attitude error equation：

B) velocity error equation：

C) site error equation：

D) inertia type instrument error equation：

WhereinFor sub- IMU attitudes misalignment, φ_E、φ_NAnd φ_URespectively east orientation, north orientation, day To misalignment, subscript E, N and U represent respectively east orientation, north orientation and day to；It is the angle speed of relative inertness system for sub- IMU navigation Degree；ForError angular speed；The attitude battle array of its navigation system is tied to for sub- IMU carriersEstimate；WithRespectively sub- IMU speed and velocity error, wherein V_E、V_N And V_URespectively east orientation, north orientation and sky orientation speed, δ V_E、δV_NWith δ V_URespectively east orientation, north orientation and sky orientation speed error；It is the specific force of sub- IMU, wherein f_E、f_NAnd f_URespectively east orientation, north orientation and day are to specific force；WithThe angular speed and its error of respectively sub- IMU navigation system terrestrial coordinate system relatively；WithRespectively sub- IMU navigation The angular speed and its error of the relative terrestrial coordinate system of system；L, λ, H and δ L, δ λ, δ H is respectively sub- IMU latitudes, longitude, height and latitude Degree error, longitude error, height error；For the first derivative of latitude,For The first derivative of longitude；R_MAnd R_NRespectively along meridian circle and the principal radius of curvature of prime vertical；ε^b=[ε_x ε_y ε_z]^TWithRespectively sub- IMU gyroscope constant value drifts count constant value biasing, wherein ε with adding_x、ε_yAnd ε_zIt is respectively sub IMU carriers system x-axis, y-axis and z-axis gyroscope constant value drift, whereinWithRespectively sub- IMU carriers system x-axis, y-axis and z Axle adds meter constant value biasing.

(2) set up the angle error model between master subsystem

Angle error model between master subsystem fixedly mounts error angle ρ=[ρ by sub- IMU_x ρ_y ρ_z]^TBecome with body elasticity Shape angle θ=[θ_x θ_y θ_z]^TTogether decide on, wherein ρ_x、ρ_yAnd ρ_zRespectively sub- IMU carriers system x-axis, y-axis and z-axis alignment error Angle, θ_x、θ_yAnd θ_zRespectively sub- IMU carriers system x-axis, y-axis and z-axis elastic deformation angle.

A) fixedly mount the differential equation of error angle ρ：

B) differential equation at elastic deformation angle：

Wherein j=x, y, z, β_j=2.146/ τ_j, τ_jFor second order markoff process correlation time；η_jFor zero-mean white noise Sound, its varianceMeet：

σ_j ²For elastic deformation angle θ_jVariance.β j andTo describe the second order of elastic deformation angle θ

The parameter of markoff process.

2nd, set up the Mathematical Modeling of sub- IMU Transfer Alignments

According to airborne distributed POS Transfer Alignments error model in 1 by body elastic deformation angle and elastic deformation angular speed State variable is extended for, and using the difference of the speed and attitude of high accuracy main POS and sub- IMU as measurement, sets up sub- IMU transmission right Accurate Mathematical Modeling is：

Wherein systematic state variable X is：

X=[X₁ X₂]^T

System transfer matrix F can be determined by the Transfer Alignment error model of sub- IMU；System noiseWhereinWithRespectively sub- IMU carriers system x-axis, y-axis, z-axis gyro and sub- IMU carriers system x-axis, y-axis, z-axis accelerate The random error of degree meter, not including random constant error；White Gaussian noise of system noise W for zero-mean, its variance matrix Q is by top Spiral shell constant value drift, plus meter constant value biasing and second order markoff process parameterDetermine；The expression formula of system noise acoustic matrix G is：

WhereinThe pose transformation matrix of navigation system is tied to for sub- IMU carriers.

System measurements variable Z=[δ ψ δ θ δ γ δ V '_E δV′_N δV′_U]^T, wherein δ ψ, δ θ, δ γ and δ V '_E、δV′_N、δ V′_UThe course angle of respectively sub- IMU and main POS, the angle of pitch, the difference of roll angle and east orientation, north orientation, the difference of sky orientation speed；Measure NoiseWherein v_δψ、v_δθ、v_δγPOS course angles based on respectively, the angle of pitch, The measurement noise of roll angle,POS east orientations, north orientation, the measurement noise of sky orientation speed based on respectively；V is The white Gaussian noise of zero-mean, its variance matrix R by main POS position and velocity accuracy determine；Measurement matrix H is：

Make main POS attitude matrixsNoteFor matrix T_aIn l rows, m row element, l=1,2,3, m= 1,2,3；Then in above formulaWithExpression formula be：

3rd, on-line identification describes the second order markoff process parameter at elastic deformation angle

T at sub- IMU mount points is gone out using Kalman Filter Estimation_kThe elastic deformation angle at moment (k=0,1,2 ..., N-1) With elastic deformation Attitude rate estimator valueWithUsing what is estimatedWithOn-line identification description elasticity becomes The second order markoff process parameter beta at shape angle_jWithConcretely comprise the following steps：

(1) t at sub- IMU mount points is gone out using Kalman Filter Estimation_kThe elastic deformation angle at momentWith elastic deformation angle Velocity estimation valueInitial t₀Moment gives Kalman filtering algorithm layout is as follows：

State one-step prediction equation

WhereinΦ_k,k-1Respectively t_kMoment system mode one-step prediction value, t_k-1Moment system mode is estimated Value, t_k-1Moment is to t_kThe systematic state transfer matrix at moment；

State Estimation accounting equation

WhereinK_k、Z_k、H_kRespectively t_kMoment system mode valuation, system gain matrix, measurement vector sum measure square Battle array；

Filtering gain equation

Wherein P_k/k-1、R_kRespectively t_kWhen the one-step prediction of etching system covariance matrix, t_kMoment system measurements noise matrix；

One-step prediction mean square error equation

Wherein, P_k-1、Q_k-1、Γ_k-1Respectively t_k-1When etching system covariance matrix, t_k-1Moment system noise matrix, t_k-1When Etching system noise drives matrix；

Estimate mean square error equation

Wherein, P_kFor t_kMoment system mode covariance matrix, I are unit battle array.

(2) second order markoff process parameter identification

Go out t at sub- IMU mount points using Kalman Filter Estimation_kThe elastic deformation angle at moment and elastic deformation angular speed are estimated EvaluationWithWith on-line identification and the second order markoff process parameter beta for describing elastic deformation angle can be updated_j WithSpecific parameter distinguishes that calculation procedure is：

A) determine valid data θ_jWith

In filtering, second order markoff process parameter may occur large change at certain moment, now recycle Estimate before Parameters variationWithCalculating nonlinear equation coefficient can cause procedure parameter estimate to there is larger error, because This must add determination in parameter identification methodWithValid data θ_jWithPart.For according to elastic deformation angle speed Degree can effectively reflect System State Model parameter beta_jSentencing for Parameters variation in the characteristics of change design parameter discrimination method Disconnected part, so that it is determined that valid data θ_jWithThe setting principle of Rule of judgment can be sketched to give estimateOne is put Letter is interval, i.e., when the estimate related to parameter belongs to confidential interval, that is, think that the moment relevant parameter does not change, Otherwise then critical parameter changes.Specifically Rule of judgment is：

Wherein []_kMiddle subscript k represents moment t_k, D () expression variances, γ₁=2 and γ₂=0.1 be respectively the upper bound and Threshold parameter lower bound threshold parameter.

NoteWithValid data number be Loop, initial t₀Moment Loop=1.Determine valid data θ_jWithIt is concrete Step is：

Work as t_kMoment elastic deformation Attitude rate estimator valueMeetWhen, Loop=Loop+1,Conversely, Loop=1,

B) calculate t_kMoment parameterWith

Due to elastic deformation angle θ_jSecond order markoff process shown in meeting formula (6), takes variance to (6) the right and left, Convolution (7) can be obtained：

Wherein

With Newton Algorithm with β_jNonlinear equation (20) for independent variable is obtained second order markoff process parameterWithIn practical situations both, aircraft elastic deformation correlation time τ_j>0 and be more than or equal to 1.Therefore, t_kMoment newton Iterative initial value is given before method iterationInitial t₀Moment, β_jWithInitial value isWithCalculate t_kMoment ParameterWithConcretely comprise the following steps：

I) utilize vector θ_jWithCalculate varianceAnd covariance

Ii) giving iterative initial value isWith Newton Algorithm it is as follows with β_jFor the nonlinear equation of independent variable (20), you can obtain second order markoff process parameterWithNote

C) parameterThe Effective judgement of estimated result

As the solution that nonlinear equation Newton method is tried to achieve is the approximate solution near initial value, it is therefore desirable to judge iterative approximation The validity of solution.Due in practical situations both, aircraft elastic deformation correlation time τ_j>0 and be more than or equal to 1, therefore for The judgement of iterative solution validity can provide following Rule of judgment：

WhereinFor t_kThe moment parameter beta that moment is calculated by equation (20)_jEstimate.

Can sketch m odel validity judgment part：Work as t_kMoment parameter beta_jEstimateIt is unsatisfactory forWhen, orderThe particular flow sheet of second order Markov Parameters discrimination method is as shown in Figure 2.

4th, correct sub- IMU strapdowns resolve obtain speed, position, attitude information

Using the second order markoff process parameter after renewal as subsequent time t_k+1Filtering initial value, so as to estimate More accurate sub- IMU attitude errors, velocity error and site error, are resolved using the strapdown of the sub- IMU of the evaluated error amendment As a result, more accurate sub- IMU positions, speed and attitude are calculated.Specifically amendment step is：

(1) attitude error, velocity error and the site error of sub- IMU are estimated

By t_kThe second order markoff process parameter that moment calculatesWithAs subsequent time (t_k+1) filter Ripple initial value, goes out t using Kalman Filter Estimation_k+1The sub- IMU the misaligned angle of the platform (φ at moment_E、φ_N、φ_U), velocity error (δ V_E、δV_N、δV_U) and site error (δ L, δ λ, δ H).

A) speed amendment

WhereinWithThe revised east orientation of respectively sub- IMU, north orientation and sky orientation speed；WithRespectively sub- IMU strapdowns resolve east orientation, north orientation and the sky orientation speed for obtaining；δV_E、δV_NWith δ V_URespectively For t_k+1The sub- IMU strapdowns that moment Kalman Filter Estimation goes out resolve east orientation, north orientation and sky orientation speed error.

B) position correction

Wherein L^old、λ^oldAnd H^oldRespectively sub- IMU strapdowns resolve latitude, the longitude and altitude for obtaining；L^new、λ^newAnd H^new The revised latitude of respectively sub- IMU, longitude and altitude；δ L, δ λ and δ H are respectively t_k+1The son that moment Kalman Filter Estimation goes out IMU strapdowns resolve latitude, longitude and altitude error.

C) attitude rectification

Calculate t_k+1Shi Kezi IMU geographic coordinate systems n₁With computed geographical coordinates n '₁Between transition matrix

Calculate t_k+1Shi Kezi IMU carrier coordinate systems b and true geographic coordinate system n₁Between transition matrix

WhereinFor t_k+1Shi Kezi IMU strapdowns resolve the attitude matrix for obtaining.

By the attitude battle array of the sub- IMU after being updatedCalculate course angle ψ of sub- IMU mount points_s, pitching angle theta_sAnd roll angle γ_s.WillIt is designated as

And because

Wherein T_lmFor matrixIn l rows, m row element, l=1,2,3, m=1,2,3；Then sub- IMU course angles ψ_s、 Pitching angle theta_sWith roll angle γ_sMain value, i.e. ψ_{S master}、θ_{S master}And γ_{S master}Respectively：

Due to course angle ψ_s, pitching angle theta_sWith roll angle γ_sSpan be respectively defined as [0,2 π], [- π ,+π].So, ψ_s、θ_sAnd γ_sTrue value can be determined by following formula：

θ_s=θ_{S master} (30)

It is modified by the speed of antithetical phrase IMU, position and attitude, more accurate sub- IMU mount points can be obtained Speed, position and attitude information, complete Transfer Alignment.

The content not being described in detail in description of the invention belongs to prior art known to professional and technical personnel in the field.

Claims (5)

1. a kind of airborne distributed POS Transfer Alignments based on parameter identification, concretely comprise the following steps：

Body elastic deformation angle is considered as second order markoff process by 1.1, is set up comprising sub- IMU ins errors model and angle error The Transfer Alignment error model of model；

Body elastic deformation angle and elastic deformation angular speed are extended for state variable by 1.2, and by high accuracy main POS and sub- IMU Speed and attitude difference as measurement, set up the Mathematical Modeling of sub- IMU Transfer Alignments；

1.3 go out t using Kalman Filter Estimation_kThe elastic deformation angle at momentWith elastic deformation angular speedK=0,1, 2 ..., N-1, using what is estimatedWithIn line computation and update description elastic deformation angle second order markoff process ginseng Number；

1.4 using the second order markoff process parameter after renewal as subsequent time t_k+1Filtering initial value, using Kalman filter Ripple estimates more accurate t_k+1The sub- IMU attitude errors at moment, velocity error and site error, using above-mentioned error correction The strapdown calculation result of sub- IMU, obtains t_k+1The position of Shi Kezi IMU, speed and attitude.

2. airborne distributed POS Transfer Alignments based on parameter identification according to claim 1, it is characterised in that： In described step 1.1, Transfer Alignment error model includes the angle error model between sub- IMU ins errors model and master subsystem, Specifically Transfer Alignment error modeling step is：

2.1 set up sub- IMU ins errors model

The definition of coherent reference coordinate system includes：Note i is geocentric inertial coordinate system；E is terrestrial coordinate system；Main POS and sub- IMU lead Boat coordinate system is northeast day geographic coordinate system, respectively with n and n₁Represent；Carrier coordinate system origin is carrier center of gravity, and x-axis is along load To the right, before carrier Y, along carrier vertical pivot upwards, the coordinate system is fixed on carrier z-axis y-axis body transverse axis, referred to as before the right side Upper carrier coordinate system, represents the carrier coordinate system of main POS and sub- IMU respectively with a and b；According to above-mentioned definition, sub- IMU inertial navigations are missed Differential mode type is：

A) the attitude error differential equation：

${\stackrel{\·}{\mathrm{\φ}}}^{n_1}=-{\mathrm{\ω}}_{{\mathrm{in}}_1}^{n_1}\×{\mathrm{\φ}}^{n_1}+{\mathrm{\δ\ω}}_{{\mathrm{in}}_1}^{n_1}+{\hat{C}}_b^{n_1}{\mathrm{\ϵ}}^b$

B) the velocity error differential equation：

$\mathrm{\δ}{\stackrel{\·}{V}}^{n_1}=f^{n_1}\×{\mathrm{\φ}}^{n_1}-(2{\mathrm{\δ\ω}}_{ie}^{n_1}+{\mathrm{\δ\ω}}_{{\mathrm{en}}_1}^{n_1})\×V^{n_1}-(2{\mathrm{\ω}}_{ie}^{n_1}+{\mathrm{\ω}}_{{\mathrm{en}}_1}^{n_1})\×{\mathrm{\δV}}^{n_1}+{\hat{C}}_b^{n_1}{\▿}^b$

C) the site error differential equation：

$\left[\begin{array}{c}\mathrm{\δ}\stackrel{\·}{L}\\ \mathrm{\δ}\stackrel{\·}{\mathrm{\λ}}\\ \mathrm{\δ}\stackrel{\·}{H}\end{array}\right]=\left[\begin{array}{ccc}0& 0& -\stackrel{\·}{L}/(R_M+H)\\ \stackrel{\·}{\mathrm{\λ}}\tan L& 0& -\stackrel{\·}{\mathrm{\λ}}/(R_N+H)\\ 0& 0& 0\end{array}\right]\left[\begin{array}{c}\mathrm{\δ}L\\ \mathrm{\δ}\mathrm{\λ}\\ \mathrm{\δ}H\end{array}\right]+\left[\begin{array}{ccc}0& 1/(R_M+H)& 0\\ \sec L/(R_N+H)& 0& 0\\ 0& 0& 1\end{array}\right]\left[\begin{array}{c}\mathrm{\δ}{V}_E\\ {\mathrm{\δV}}_N\\ {\mathrm{\δV}}_U\end{array}\right]$

D) the inertia type instrument error differential equation：

$\left\{\begin{array}{c}{\stackrel{\·}{\mathrm{\ϵ}}}^b=0\\ {\stackrel{\·}{\▿}}^b=0\end{array}\right.$

WhereinFor sub- IMU attitudes misalignment, φ_E、φ_NAnd φ_URespectively east orientation, north orientation, day are to mistake Quasi- angle, subscript E, N and U represent respectively east orientation, north orientation and day to；It is the angular speed of relative inertness system for sub- IMU navigation；ForError angular speed；The attitude battle array of its navigation system is tied to for sub- IMU carriersEstimate；WithRespectively sub- IMU speed and velocity error, wherein V_E、V_N And V_URespectively east orientation, north orientation and sky orientation speed, δ V_E、δV_NWith δ V_URespectively east orientation, north orientation and sky orientation speed error；It is the specific force of sub- IMU, wherein f_E、f_NAnd f_URespectively east orientation, north orientation and day are to specific force；WithThe angular speed and its error of respectively sub- IMU navigation system terrestrial coordinate system relatively；WithRespectively sub- IMU navigation The angular speed and its error of the relative terrestrial coordinate system of system；L, λ, H and δ L, δ λ, δ H is respectively sub- IMU latitudes, longitude, height and latitude Degree error, longitude error, height error；For the first derivative of latitude,For The first derivative of longitude；R_MAnd R_NRespectively along meridian circle and the principal radius of curvature of prime vertical；ε^b=[ε_x ε_y ε_z]^TWithRespectively sub- IMU gyroscope constant value drifts count constant value biasing, wherein ε with adding_x、ε_yAnd ε_zIt is respectively sub IMU carriers system x-axis, y-axis and z-axis gyroscope constant value drift, whereinWithRespectively sub- IMU carriers system x-axis, y-axis and z Axle adds meter constant value biasing；

2.2 set up the angle error model between master subsystem

A) fixedly mount the differential equation of error angle ρ：

$\stackrel{\·}{\mathrm{\ρ}}=0$

Wherein ρ=[ρ_x ρ_y ρ_z]^TError angle, ρ are fixedly mounted for sub- IMU_x、ρ_yAnd ρ_zRespectively sub- IMU carriers system x-axis, y-axis and z Axle misalignment angle；

B) differential equation at elastic deformation angle：

${\stackrel{\·\·}{\mathrm{\θ}}}_j+2{\mathrm{\β}}_j{\stackrel{\·}{\mathrm{\θ}}}_j+{{\mathrm{\β}}_j}^2{\mathrm{\θ}}_j={\mathrm{\η}}_j$

Wherein θ_jFor the elastic deformation angle on sub- IMU carriers system jth axle, j=x, y, z, θ=[θ_x θ_y θ_z]^TFor elastic deformation angle； β_j=2.146/ τ_j, τ_jFor second order markoff process correlation time；η_jFor zero-mean white noise, its varianceMeet：

$Q_{{\mathrm{\η}}_j}=4{{\mathrm{\β}}_j}^3{{\mathrm{\σ}}_j}^2$

σ_j ²For elastic deformation angle θ_jVariance, β_jWithTo describe the parameter of the second order markoff process of elastic deformation angle θ.

3. airborne distributed POS Transfer Alignments based on parameter identification according to claim 2, it is characterised in that： The sub- IMU Transfer Alignments Mathematical Modeling set up in described step 1.2 is：

$\stackrel{\·}{X}=FX+GW$

Z=HX+V

Wherein systematic state variable X is：

X=[X₁ X₂]^T

$X_1={\left[\begin{array}{ccccccccccccccc}{\mathrm{\φ}}_E& {\mathrm{\φ}}_N& {\mathrm{\φ}}_U& {\mathrm{\δV}}_E& {\mathrm{\δV}}_N& {\mathrm{\δV}}_U& \mathrm{\δ}L& \mathrm{\δ}\mathrm{\λ}& \mathrm{\δ}H& {\mathrm{\ϵ}}_x& {\mathrm{\ϵ}}_y& {\mathrm{\ϵ}}_z& {\▿}_x& {\▿}_y& {\▿}_z\end{array}\right]}^T$

$X_2={\left[\begin{array}{ccccccccc}{\mathrm{\ρ}}_x& {\mathrm{\ρ}}_y& {\mathrm{\ρ}}_z& {\mathrm{\θ}}_x& {\mathrm{\θ}}_y& {\mathrm{\θ}}_z& {\stackrel{\·}{\mathrm{\θ}}}_x& {\stackrel{\·}{\mathrm{\θ}}}_y& {\stackrel{\·}{\mathrm{\θ}}}_z\end{array}\right]}^T$

System transfer matrix F can be determined by the Transfer Alignment error model of sub- IMU；System noiseWherein WithRespectively sub- IMU carriers system x-axis, y-axis, z-axis gyro and sub- IMU carriers system x-axis, y-axis, z-axis accelerate The random error of degree meter, not including random constant error；White Gaussian noise of system noise W for zero-mean, its variance matrix Q is by top Spiral shell constant value drift, plus meter constant value biasing and second order markoff process parameterDetermine；The expression formula of system noise acoustic matrix G is：

$G={\left[\begin{array}{ccc}{C}_b^{n_1}& 0_{3\×3}& 0_{3\×3}\\ 0_{3\×3}& C_b^{n_1}& 0_{3\×3}\\ 0_{15\×3}& 0_{15\×3}& 0_{13\×3}\\ 0_{3\×3}& 0_{3\×3}& I_{3\×3}\end{array}\right]}_{24\×9}$

WhereinThe pose transformation matrix of navigation system is tied to for sub- IMU carriers；

System measurements variable Z=[δ_ψ δθ δ_γ δV′_E δV′_N δV′_U]^T, wherein δ ψ, δ θ, δ_γWith δ V '_E、δV′_N、δV′_URespectively The course angle of sub- IMU and main POS, the angle of pitch, the difference of roll angle and east orientation, north orientation, the difference of sky orientation speed；Measurement noiseWherein v_δψ、v_δθ、v_δγPOS course angles, the angle of pitch, roll based on respectively The measurement noise at angle,POS east orientations, north orientation, the measurement noise of sky orientation speed based on respectively；V is zero equal The white Gaussian noise of value, its variance matrix R by main POS position and velocity accuracy determine；Measurement matrix H is：

$H={\left[\begin{array}{cccccc}{H}_{3\×3}^1& 0_{3\×3}& 0_{3\×9}& H_{3\×3}^2& H_{3\×3}^3& 0_{3\×3}\\ 0_{3\×3}& I_{3\×3}& 0_{3\×9}& 0_{3\×3}& 0_{3\×3}& 0_{3\×3}\end{array}\right]}_{6\×24}$

Make main POS attitude matrixsNoteFor matrix T_aIn l rows, m row element, l=1,2,3, m=1,2, 3；Then in above formulaWithExpression formula be：

$H_{3\×3}^1=\left[\begin{array}{ccc}\frac{{T_a}^{\left(12\right)}{T_a}^{\left(32\right)}}{{\left({T_a}^{\left(12\right)}\right)}^2+{\left({T_a}^{\left(22\right)}\right)}^2}& \frac{{T_a}^{\left(22\right)}{T_a}^{\left(32\right)}}{{\left({T_a}^{\left(12\right)}\right)}^2+{\left({T_a}^{\left(22\right)}\right)}^2}& -1\\ -\frac{{T_a}^{\left(22\right)}}{\sqrt{1-{\left({T_a}^{\left(32\right)}\right)}^2}}& \frac{{T_a}^{\left(12\right)}}{\sqrt{1-{\left({T_a}^{\left(32\right)}\right)}^2}}& 0\\ \frac{{T_a}^{\left(21\right)}{T_a}^{\left(33\right)}-{T_a}^{\left(31\right)}{T_a}^{\left(23\right)}}{{\left({T_a}^{\left(33\right)}\right)}^2+{\left({T_a}^{\left(31\right)}\right)}^2}& \frac{{T_a}^{\left(31\right)}{T_a}^{\left(13\right)}-{T_a}^{\left(11\right)}{T_a}^{\left(33\right)}}{{\left({T_a}^{\left(33\right)}\right)}^2+{\left({T_a}^{\left(31\right)}\right)}^2}& 0\end{array}\right]$

$H_{3\×3}^2=H_{3\×3}^3=\left[\begin{array}{ccc}\frac{{T_a}^{\left(12\right)}{T_a}^{\left(23\right)}-{T_a}^{\left(13\right)}{T_a}^{\left(22\right)}}{{\left({T_a}^{\left(12\right)}\right)}^2+{\left({T_a}^{\left(22\right)}\right)}^2}& 0& \frac{{T_a}^{\left(11\right)}{T_a}^{\left(22\right)}-{T_a}^{\left(12\right)}{T_a}^{\left(21\right)}}{{\left({T_a}^{\left(12\right)}\right)}^2+{\left({T_a}^{\left(22\right)}\right)}^2}\\ \frac{{T_a}^{\left(33\right)}}{\sqrt{1-{\left({T_a}^{\left(32\right)}\right)}^2}}& 0& -\frac{{T_a}^{\left(31\right)}}{\sqrt{1-{\left({T_a}^{\left(32\right)}\right)}^2}}\\ -\frac{{T_a}^{\left(31\right)}{T_a}^{\left(32\right)}}{{\left({T_a}^{\left(33\right)}\right)}^2+{\left({T_a}^{\left(31\right)}\right)}^2}& 1& -\frac{{T_a}^{\left(32\right)}{T_a}^{\left(33\right)}}{{\left({T_a}^{\left(33\right)}\right)}^2+{\left({T_a}^{\left(31\right)}\right)}^2}\end{array}\right].$

4. airborne distributed POS Transfer Alignments based on parameter identification according to claim 2, it is characterised in that： Using t at sub- IMU mount points in described step 1.3_kThe elastic deformation angular estimation value at momentAnd bullet Property deformation Attitude rate estimator valueOn-line identification describes the second order markoff process at elastic deformation angle Parameter beta_jWithConcretely comprise the following steps：

4.1 determine valid data θ_jWith

NoteWithValid data number be Loop, initial t₀Moment Loop=1；

Work as t_kMoment elastic deformation Attitude rate estimator valueMeetWhen, Loop =Loop+1,Conversely,

Loop=1,Wherein []_kMiddle subscript k represents t_kMoment, D () represent variance, γ₁ =2 and γ₂=0.1 is respectively upper bound threshold parameter and lower bound threshold parameter；

4.2 calculate t_kMoment parameterWith

Initial t₀Moment, β_jWithInitial value isWith

A) utilize vector θ_jWithCalculate varianceAnd covariance

B) giving iterative initial value isWith Newton Algorithm it is as follows with β_jFor the nonlinear equation of independent variable, you can Obtain second order markoff process parameterWith

$D\left({\stackrel{\·\·}{\mathrm{\θ}}}_j\right)+4{{\mathrm{\β}}_j}^{2}D\left({\stackrel{\·}{\mathrm{\θ}}}_j\right)+{{\mathrm{\β}}_j}^{4}D\left({\mathrm{\θ}}_j\right)+4{\mathrm{\β}}_{j}Cov({\stackrel{\·}{\mathrm{\θ}}}_j,{\stackrel{\·\·}{\mathrm{\θ}}}_j)+2{{\mathrm{\β}}_j}^{2}Cov({\mathrm{\θ}}_j,{\stackrel{\·\·}{\mathrm{\θ}}}_j)+4{{\mathrm{\β}}_j}^{3}Cov({\mathrm{\θ}}_j,{\stackrel{\·}{\mathrm{\θ}}}_j)=Q_{{\mathrm{\η}}_j}$

WhereinNote

4.3 parameterThe Effective judgement of estimated result

Work as t_kMoment parameter beta_jEstimateIt is unsatisfactory forWhen, order

5. airborne distributed POS Transfer Alignments based on parameter identification according to claim 2, it is characterised in that： Using the second order markoff process parameter after renewal as subsequent time t in described step 1.4_k+1Filtering initial value, adopt Kalman Filter Estimation goes out sub- IMU attitude errors, velocity error and site error, finally corrects sub- IMU strapdowns calculation result Step is：

5.1 attitude error, velocity error and the site errors for estimating sub- IMU

By t_kThe second order markoff process parameter that moment calculatesWithAs subsequent time t_k+1Filtering it is initial Value, goes out t using Kalman Filter Estimation_k+1The sub- IMU the misaligned angle of the platform φ at moment_E、φ_N、φ_U, velocity error δ V_E、δV_N、δV_U With site error δ L, δ λ, δ H；

The 5.2 strapdown calculation results for utilizing the sub- IMU of above-mentioned error correction, obtain t_k+1The sub- IMU positions at moment, speed and attitude

A) speed amendment

$V_E^{new}=V_E^{old}-{\mathrm{\δV}}_E$

$V_N^{new}=V_N^{old}-{\mathrm{\δV}}_N$

$V_U^{new}=V_U^{old}-{\mathrm{\δV}}_U$

WhereinWithThe revised east orientation of respectively sub- IMU, north orientation and sky orientation speed；WithRespectively sub- IMU strapdowns resolve east orientation, north orientation and the sky orientation speed for obtaining；δV_E、δV_NWith δ V_URespectively t_k+1Moment karr The graceful sub- IMU strapdowns for estimating that filter resolve east orientation, north orientation and sky orientation speed error；

B) position correction

L^new=L^old-δL

λ^new=λ^old-δλ

H^new=H^old-δH

Wherein L^old、λ^oldAnd H^oldRespectively sub- IMU strapdowns resolve latitude, the longitude and altitude for obtaining；L^new、λ^newAnd H^newRespectively For the revised latitudes of sub- IMU, longitude and altitude；δ L, δ λ and δ H are respectively t_k+1The sub- IMU that moment Kalman Filter Estimation goes out Strapdown resolves latitude, longitude and altitude error；

C) attitude rectification

Calculate t_k+1Shi Kezi IMU geographic coordinate systems n₁With computed geographical coordinates n₁' transition matrix

$C_{n_1^{\′}}^{n_1}=\left[\begin{array}{ccc}1& -{\mathrm{\φ}}_U& {\mathrm{\φ}}_N\\ {\mathrm{\φ}}_U& 1& -{\mathrm{\φ}}_E\\ -{\mathrm{\φ}}_N& {\mathrm{\φ}}_E& 1\end{array}\right]$

Calculate t_k+1Shi Kezi IMU carrier coordinate systems b and true geographic coordinate system n₁Between transition matrix

$C_b^{n_1}=C_{n_1^{\′}}^{n_1}{C}_b^{n_1^{\′}}$

WhereinFor t_k+1Shi Kezi IMU strapdowns resolve the attitude matrix for obtaining；

By the attitude battle array of the sub- IMU after being updatedCalculate t_k+1Course angle ψ of Shi Kezi IMU_s, pitching angle theta_sAnd roll angle γ_s, willIt is designated as

$C_b^{n_1}={\left[\begin{array}{ccc}{T}_{11}& T_{12}& T_{13}\\ T_{21}& T_{22}& T_{23}\\ T_{31}& T_{32}& T_{33}\end{array}\right]}_{3\×3}$

Wherein T_lmFor matrixIn l rows, m row element, l=1,2,3, m=1,2,3；Then sub- IMU course angles ψ_s, pitching Angle θ_sWith roll angle γ_sMain value, i.e. ψ_{S master}、θ_{S master}And γ_{S master}Respectively：

θ_{S master}=arcsin (T₃₂)

Due to course angle ψ_s, pitching angle theta_sWith roll angle γ_sSpan be respectively defined as [0,2 π],[- π ,+π]；So, ψ_s、θ_sAnd γ_sTrue value can be determined by following formula：

θ_s=θ_{S master}

Be modified by the speed of antithetical phrase IMU, position and attitude, can obtain more accurately the speed of sub- IMU mount points, Position and attitude information, complete Transfer Alignment.