CN104748761A - Optimal attitude matching-based moving base transfer alignment time delay compensation method - Google Patents

Abstract

The invention discloses an optimal attitude matching-based moving base transfer alignment time delay compensation method. The method comprises carrying out coarse alignment on an inertial navigation subsystem by navigation information of an inertial navigation main system, respectively carrying out navigation calculation by the inertial navigation main system and the inertial navigation subsystem, transmitting rate and attitude information to the inertial navigation subsystem by the inertial navigation main system, respectively acquiring strapdown matrixes of the inertial navigation main system and the inertial navigation subsystem according to the inertial navigation calculation result, simultaneously, constructing an installation angle recourse matrix of the inertial navigation subsystem, constructing observed quantity in the inertial navigation subsystem to obtain speed difference and measurement misalignment angle of the inertial navigation main system and the inertial navigation subsystem, building a strapdown inertial navigation system state equation, a system observation equation and system observed quantity, carrying out Kalman filtering iterative computation to obtain transfer alignment time delay estimated values of the inertial navigation main system and the inertial navigation subsystem, and carrying out compensation to obtain an inertial navigation subsystem attitude misalignment angle after time delay compensation. The method realizes accurate time delay estimation and compensation and has a wide use range.

Description

Based on the moving base Transfer Alignment delay compensation method of optimum attitude coupling

Technical field

The invention belongs to technical field of inertial, particularly a kind of moving base Transfer Alignment delay compensation method based on optimum attitude coupling.

Background technology

Inertial navigation system, before entering navigational state, has to pass through initial alignment.Inertial navigation system Transfer Alignment be sub-inertial navigation system Data Dynamic mate the process of main inertial navigation system data, namely the inertial navigation system speed of main inertial navigation system and attitude information aims at sub-inertial navigation system.In Transfer Alignment process, due to resolving and transmission delay of main inertial navigation, sub-inertial reference calculation information and the reference information carrying out mating can not Complete Synchronizations, and time delay is comparatively large in some cases, thus can affect speed of convergence and the precision of Kalman filter in Transfer Alignment.

Document 1: propose main inertial guidance data such as directly utilizing main inertial navigation attitude four element, carrier aircraft angular velocity and time delay in " Computer Simulation " the 25th volume the 2nd interim " compensation method of Time-delay in Transfer Alignment " and carry out four element calculating, draw main inertial navigation attitude four element after delay, and then obtain the algorithm of the measurement misalignment after compensating.But in this algorithm, time delay relies on hardware device to measure, and does not consider the situation of large established angle.

Summary of the invention

The object of the present invention is to provide the moving base Transfer Alignment delay compensation method based on optimum attitude coupling that a kind of speed is fast, precision is high.

The technical solution realizing the object of the invention is: a kind of moving base Transfer Alignment delay compensation method based on optimum attitude coupling, comprises the following steps:

Step 1, utilizes the navigation information antithetical phrase inertial navigation system of main inertial navigation system to carry out coarse alignment;

Step 2, main inertial navigation system and sub-inertial navigation system carry out navigation calculation respectively, and the speed obtained and attitude information are transferred to sub-inertial navigation system by main inertial navigation system;

Step 3, the strap-down matrix of main and sub inertial navigation system is obtained respectively according to navigation calculation result, the established angle compensation matrix of constructor inertial navigation system, constructs observed quantity in sub-inertial navigation system simultaneously, namely obtains the velocity contrast between main and sub inertial navigation system and measures misalignment;

Step 4, carry out standard Kalman filtering iteration to resolve: set up strapdown inertial navitation system (SINS) state equation, systematic observation equation and systematic perspective and measure, and carry out Kalman filtering Iterative, obtain the time delay estimated value of main and sub inertial navigation system Transfer Alignment and compensate, obtaining the attitude misalignment of the sub-inertial navigation system after to time delay equalization.

Compared with prior art, its remarkable advantage is in the present invention: time delay adds among filtering as state variable by (1), can estimate time delay accurately and efficiently and compensate, significantly improve Transfer Alignment precision; (2) solve time delay problem, avoid and utilize hardware to postpone the trouble brought settling time; (3) optimum attitude algorithm has compared with other conventional transmission alignment algorithms that form is simple, easy to understand, greatly can reduce the advantage of calculated amount, normally can work under sub-inertial navigation established angle is the environment of wide-angle.

Accompanying drawing explanation

Fig. 1 is the workflow diagram of the moving base Transfer Alignment delay compensation method that the present invention is based on optimum attitude coupling.

Fig. 2 be in embodiment 1 Transfer Alignment l-G simulation test to carrier flight path figure after time delay equalization.

Fig. 3 be in embodiment 1 Transfer Alignment l-G simulation test to time delay equalization forward and backward attitude misalignment curve comparison figure.

Fig. 4 is that Transfer Alignment l-G simulation test of the present invention is to time delay estimadon curve map.

Embodiment

Below in conjunction with drawings and the specific embodiments, the present invention is described in further detail.

Composition graphs 1, the present invention is based on the moving base Transfer Alignment delay compensation method of optimum attitude coupling, comprises the following steps:

Step 1, utilizes the navigation information antithetical phrase inertial navigation system of main inertial navigation system to carry out coarse alignment, and be transferred to sub-inertial navigation system by the speed of main inertial navigation system, attitude, positional information, sub-inertial navigation system utilizes the information that main inertial navigation is transmitted to complete initial work.

Step 2, main inertial navigation system and sub-inertial navigation system carry out navigation calculation respectively, and the speed obtained and attitude information are transferred to sub-inertial navigation system by main inertial navigation system;

Step 3, the strap-down matrix of main and sub inertial navigation system is obtained respectively according to navigation calculation result, the established angle compensation matrix of constructor inertial navigation system, constructs observed quantity in sub-inertial navigation system simultaneously, namely obtains the velocity contrast between main and sub inertial navigation system and measures misalignment;

Step 4, carry out standard Kalman filtering iteration to resolve: set up strapdown inertial navitation system (SINS) state equation, systematic observation equation and systematic perspective and measure, and carry out Kalman filtering Iterative, obtain the time delay estimated value of main and sub inertial navigation system Transfer Alignment and compensate, obtaining the attitude misalignment of the sub-inertial navigation system after to time delay equalization; The described standard Kalman filtering iteration that carries out resolves, specific as follows:

1st step, sets up ins error model according to the mechanization of strapdown inertial navitation system (SINS), obtains the error equation of system, comprises attitude error equations, velocity error equation and inertial device error equation, specific as follows:

(1.1) attitude error equations and velocity error equation are:

$\left\{\begin{array}{c}{\stackrel{\·}{\mathrm{\φ}}}_E={\mathrm{\φ}}_N{w}_{\mathrm{ie}}\sin L+{\mathrm{\φ}}_N{V}_E\tan L/(R_N+h)-{\mathrm{\φ}}_U{w}_{\mathrm{ie}}\cos L\\ -{\mathrm{\φ}}_U{V}_E/(R_N+h)-\mathrm{\δ}{V}_N/(R_N+h)-{\mathrm{\ϵ}}_E\\ {\stackrel{\·}{\mathrm{\φ}}}_N=-{\mathrm{\φ}}_E{w}_{\mathrm{ie}}\sin L-{\mathrm{\φ}}_E{V}_E\tan L/(R_N+h)\\ -{\mathrm{\φ}}_U{V}_N/(R_M+h)+{\mathrm{\δV}}_E/(R_N+h)-{\mathrm{\ϵ}}_N\\ {\stackrel{\·}{\mathrm{\φ}}}_U={\mathrm{\φ}}_E{w}_{\mathrm{ie}}\cos L+{\mathrm{\φ}}_E{V}_E/(R_N+h)+{\mathrm{\φ}}_N{V}_N/(R_M+h)\\ +{\mathrm{\δV}}_E\tan L/(R_N+h)-{\mathrm{\ϵ}}_U\\ \mathrm{\δ}{\stackrel{\·}{V}}_E=-{\mathrm{\φ}}_N{f}_U+{\mathrm{\φ}}_U{f}_N+{\mathrm{\δV}}_E{V}_N\tan L/(R_M+h)\\ -{\mathrm{\δV}}_E{V}_U/(R_M+h)+{2\mathrm{\δV}}_N{w}_{\mathrm{ie}}\sin L-{\mathrm{\δV}}_E{V}_E\tan L/(R_N+h)\\ -{2\mathrm{\δV}}_U{w}_{\mathrm{ie}}\cos L-{\mathrm{\δV}}_U{V}_E/(R_N+h)+{\▿}_E\\ \mathrm{\δ}{\stackrel{\·}{V}}_N={\mathrm{\φ}}_E{f}_U-{\mathrm{\φ}}_U{f}_E-{2\mathrm{\δV}}_E{w}_{\mathrm{ie}}\sin L-{\mathrm{\δV}}_E{V}_E\tan L/(R_N+h)\\ -{\mathrm{\δV}}_N{V}_U/(R_M+h)-{\mathrm{\δV}}_U{V}_N/(R_M+h)+{\▿}_N\\ \mathrm{\δ}{\stackrel{\·}{V}}_U=-{\mathrm{\φ}}_E{f}_N+{\mathrm{\φ}}_N{f}_E+2{\mathrm{\δV}}_E{w}_{\mathrm{ie}}\cos L+{\mathrm{\δV}}_E{V}_E/(R_N+h)\\ +2\mathrm{\δ}{V}_N{V}_N/(R_M+h)+{\▿}_U\end{array}\right.$

In formula, φ _e, φ _n, φ _ube respectively the misaligned angle of the platform in east, north, direction, sky, δ V _e, δ V _n, δ V _ube respectively the velocity error in carrier east, north, direction, sky, V _e, V _n, V _ube respectively the speed in east, north, direction, sky, L, h represent latitude and height respectively, R _mfor the radius-of-curvature of each point on ellipsoid meridian circle, R _nfor the radius-of-curvature of each point on prime vertical, w _iefor earth rotation angular speed, f _e, f _n, f _uinertial navigation system accelerometer measures to specific force be ratio force component on Xia Dong, north, direction, three, sky by the navigation obtained after coordinate conversion, ε _e, ε _n, ε _ube respectively the component that the equivalence of gyro in geographic coordinate system drifts in east, north, direction, sky, ▽ _e, ▽ _n, ▽ _ube respectively the component that the equivalence of accelerometer in geographic coordinate system is biased in east, north, direction, sky;

Speed V _iand specific force f _ithere is provided by main inertial navigation system, wherein i=E, N, U; The equivalence drift ε of gyro in geographic coordinate system _i▽ is biased with the equivalence of accelerometer _i, short owing to aiming at the time, these equivalents are random constant value, namely have:

${\stackrel{\·}{\mathrm{\ϵ}}}_i=0(i=E,N,U)$

${\stackrel{\·}{\mathrm{\λ}}}_i=0(i=E,N,U)$

(1.2) alignment error angle equation is:

${\stackrel{\·}{\mathrm{\λ}}}_i=0(i=E,N,U)$

Using the time delay in Transfer Alignment as random constant value process, namely the model of main inertial navigation system time delay Δ t is:

${\stackrel{\·}{\▿}}_i=0$

Wherein, λ _e, λ _n, λ _uto tie up to the component on x, y, z axle at carrier for the fix error angle of the relatively main inertial navigation system of sub-inertial navigation system.

2nd step, according to the state equation of ins error model and systematic error establishing equation strapdown inertial navitation system (SINS); The state equation of described strapdown inertial navitation system (SINS) is shown below:

$\stackrel{\·}{X}=\mathrm{FX}+\mathrm{GW}$

In formula, X is system state vector, represent the derivative of system state vector, F is systematic state transfer matrix, and G is that system noise drives matrix, and W is system noise vector, specific as follows:

(2.1) X is system state vector:

X＝[φ _iδV _iε _i▽ _iλ _iΔt] _16×1，i＝E,N,U

(2.2) F is systematic state transfer matrix:

Matrix-block F in systematic state transfer matrix ₁with F ₂as follows:

$F_1={\left[\begin{array}{ccc}0& {\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L& -({\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})\\ -({\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L)& 0& -\frac{V_N}{R_M+h}\\ {\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h}& \frac{V_N}{R_M+h}& 0\\ 0& -f_u& f_N\\ f_U& 0& -f_E\\ -f_N& f_E& 0\end{array}\right]}_{6\×3}$

$F_2={\left[\begin{array}{ccc}0& -\frac{1}{R_M+h}& 0\\ \frac{V_N}{R_M+h}& \frac{1}{R_N+h}& 0\\ \frac{\tan L}{R_N+h}& 0& 0\\ \frac{V_N}{R_M+h}\tan L-\frac{V_U}{R_M+h}& {2\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L& -({2\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})\\ -2({\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L)& -\frac{V_U}{R_M+h}& -\frac{V_N}{R_M+h}\\ 2({\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})& \frac{2V_N}{R_M+h}& 0\end{array}\right]}_{6\×3}$

(2.3) G is that system noise drives matrix:

$G={\left[\begin{array}{cc}-C_b^n& 0_{3\×3}\\ 0_{3\×3}& C_b^n\\ 0_{10\×3}& 0_{10\×3}\end{array}\right]}_{16\×6}$

(2.4) W is system noise vector matrix:

W＝[W _GxW _GyW _GzW _▽xW _▽yW _▽z] ^T _6×1

And suppose that it is zero mean Gaussian white noise, covariance matrix is E (WW ^t)=Q, Q is systematic procedure noise variance matrix;

In formula, for attitude matrix, W _gx, W _gy, W _gzbe respectively the component of Modelling of Random Drift of Gyroscopes on x, y, z axle, W _{▽ x}, W _{▽ y}, W _{▽ z}be respectively the component of accelerometer bias on x, y, z axle.

3rd step, chooses the velocity contrast between main and sub inertial navigation system and measures misalignment as observed quantity, the relation derived the misaligned angle of the platform, attitude misalignment and measure between misalignment, and then obtaining optimum attitude matching algorithm; Described optimum attitude matching algorithm, is specially:

(3.1) choose the velocity contrast between main and sub inertial navigation system and measure misalignment φ _mas observed quantity, obtaining system measurements equation is:

Z＝HX+V

In formula, Z=[φ _mxφ _myφ _mzδ V _eδ V _nδ V _u] be observed quantity, φ _mx, φ _my, φ _mzfor measuring the component of misalignment on x, y, z axle; V be measurement noise and for average be the white Gaussian noise of zero, its covariance is E [VV ^t]=R, R is measuring noise square difference battle array;

(3.2) misalignment φ is measured _mobtained by following derivation:

${\tilde{C}}_s^m{C}_n^{s^{\text{'}}}{C}_m^n=I-{\mathrm{\φ}}_m\×$

In formula, for the transition matrix between main and sub inertial navigation system body coordinate system, for the transposition of sub-inertial navigation system attitude matrix, be main inertial navigation system attitude matrix, be the offset of sub-inertial navigation system established angle attitude matrix, also existing after this matrix compensation can not the fix error angle λ of direct compensation, and has:

${\tilde{C}}_s^m=(I-\mathrm{\λ}\×)C_s^m$

Therefore can obtain:

$\begin{array}{c}{\tilde{C}}_s^m{C}_n^{s^{\text{'}}}{C}_m^n={\tilde{C}}_s^m{C}_{n^{\text{'}}}^s{C}_m^n={\tilde{C}}_s^m{C}_m^s{C}_n^m{C}_{n^{\text{'}}}^n{C}_m^n\\ ={\tilde{C}}_s^m{C}_m^s(I+C_n^m\mathrm{\φ}\×C_m^n)\\ =(I-\mathrm{\λ}\×)(I+C_n^m\mathrm{\φ}\×C_m^n)\\ =(I-\mathrm{\λ}\×)(I+\left(C_n^m\mathrm{\φ}\right)\×)\\ \≈I+\left(C_n^m\mathrm{\φ}\right)\×-\mathrm{\λ}\×\\ =I-{\mathrm{\φ}}_m\×\end{array}$

Namely obtain optimum attitude matching algorithm;

In formula for matrix transposition, for matrix transposition, for sub-inertial navigation mathematical platform coordinate is tied to the transition matrix of navigational coordinate system, φ is sub-Inertial navigation platform misalignment;

(3.3), after considering time delay, misalignment φ is measured _mbe expressed as:

${\mathrm{\φ}}_m=\mathrm{\λ}-C_n^m\mathrm{\φ}+{\mathrm{\ω}}_m\mathrm{\Δt}$

Velocity error is:

δv＝v _s(t+Δt)-v _m(t)-f _m(t)Δt

In formula, v _s(t+ Δ t) for sub-inertial navigation is in the speed of t+ Δ t, v _mt () is the speed of main inertial navigation in t, f _mt () is the specific force of main inertial navigation in t;

The measurement matrix of system can be obtained thus:

$H={\left[\begin{array}{cccccc}-C_n^b& 0_{3\×3}& 0_{3\×3}& 0_{3\×3}& I_{3\×3}& B_{3\×1}\\ 0_{3\×3}& I_{3\×3}& 0_{3\×3}& 0_{3\×3}& 0_{3\×3}& C_{3\×1}\end{array}\right]}_{6\×16}$

Wherein:

$B_{3\×1}=\left[\begin{array}{c}{f}_{\mathrm{ME}}\\ f_{\mathrm{MN}}\\ f_{\mathrm{MU}}\end{array}\right],C_{3\×1}=\left[\begin{array}{c}{\mathrm{\ω}}_{\mathrm{mx}}\\ {\mathrm{\ω}}_{\mathrm{my}}\\ {\mathrm{\ω}}_{\mathrm{mz}}\end{array}\right]$

F in formula _mE, f _mN, f _mUbe respectively the ratio force component of ratio force information on east, north, direction, three, sky that the moment is aimed in main inertial navigation, ω _mx, ω _my, ω _mzthe angular velocity on body axis system x, y, z axle is engraved in when being main inertial navigation aligning.

4th step, Kalman filtering Iterative is carried out in observed quantity according to the system state equation set up, systematic observation equation and system, obtains the time delay estimated value of main and sub inertial navigation system Transfer Alignment and the attitude misalignment to the sub-inertial navigation system after time delay equalization.The state equation of system and measurement equation discretize are expressed as:

X _k＝Φ _k,k-1X _k-1+Γ _k-1W _k-1

Z _k＝H _kX _k+V _k

Wherein, X _krepresent by estimated state, Φ _{k, k-1}for t _k-1the Matrix of shifting of a step in moment, Γ _k-1for k-1 moment system noise drives battle array, W _kfor system incentive noise sequence, Z _kfor measurement matrix, H _kfor measuring battle array, V _kfor measurement noise sequence.Specific as follows according to the Kalman Algorithm of the Kalman filter fundamental equation being applicable to discrete system:

State one-step prediction equation:

X _k/k-1＝φ _k,k-1X _k-1

Wherein, X _k/K-1for k moment system state one-step prediction value, X _k-1for k-1 moment system state estimation value, φ _{k, k-1}for the systematic state transfer matrix in k-1 moment to k moment;

One-step prediction square error equation:

$P_{k/l-1}={\mathrm{\φ}}_{k,k-1}{P}_{k-1}{\mathrm{\φ}}_{k,k-1}^T+{\mathrm{\Γ}}_{k-1}{Q}_{k-1}{\mathrm{\Γ}}_{k-1}^T$

Wherein, P _k/k-1for the system state covariance matrix in k-1 moment to k moment, P _k-1for the system state covariance matrix in k-1 moment, Q _k-1for k-1 moment system noise matrix;

Optimal filtering gain equation:

$K_k=P_{k|k-1}{H}_k^T{[H_k{P}_{k|k-1}{H}_k^T+P_k]}^{-1}$

Wherein, K _kfor k moment system-gain matrix, H _kfor k moment system measurements matrix, R _kfor k moment system measurements noise matrix;

State estimation equation:

X _k＝X _k/k-1+K _k(Z _k-H _kX _k/k-1)

Estimate square error equation:

$P_k=(I-K_k{H}_k)P_{l/k-1}{(I-K_k{H}_k)}^T+K_k{R}_k{K}_{k-1}^T$

Wherein, Q _ksystematic procedure noise variance matrix, P _kfor mean squared error matrix.

The Transfer Alignment time delay estimadon and the compensation that add optimum attitude coupling based on speed can be completed by above-mentioned steps.

Embodiment 1

In order to be described the inventive method, fully show reliability and the accuracy of the method, l-G simulation test is as follows:

1) starting condition and optimum configurations is emulated

(11) carrier east, north, sky speed are respectively-50m/s ,-50m/s, 0m/s; Carrier initial position: latitude is 32.03 °, longitude is 118.46 °, is highly 400m; Carrier initial attitude is: the angle of pitch is 0 °, and roll angle is 0 °, and crab angle is 135 °.

(12) sub-inertial navigation accelerometer constant value is biased is set to 5mg; Sub-inertial navigation gyro constant drift is set to 10(deg/h).

(13) Kalman filtering initial parameter X ₀, R ₀, Q ₀, P ₀arrange as follows:

X ₀＝0

P ₀＝diag{(1°) ²,(1°) ²,(1°) ²,(0.5m/s) ²,(0.5m/s) ²,(0.5m/s) ²,

(10°/h) ²,(10°/h) ²,(10°/h) ²,(5mg) ²,(5mg) ²,(5mg) ²,(1.1°) ²,(1.1°) ²,(1.1°) ²}

Q ₀＝diag{(10°/h) ²,(10°/h) ²,(10°/h) ²,(5mg) ²,(5mg) ²,(5mg) ²}

R ₀＝diag{(0.0003°) ²,(0.0003°) ²,(0.0003°) ²,(0.1m/s) ²,(0.1m/s) ²,(0.1m/s) ²}

(14) arranging the time delay that main inertial navigation information is transferred to sub-inertial navigation is 0.1S.The concrete flight path of carrier is shown in Fig. 2.

2) Simulation results and analysis

Fig. 3 gives the attitude misalignment evaluated error curve of carrier inertial navigation after Kalman filtering is aimed at, have in figure and time delay is compensated and curve when not compensating, wherein red solid line is the curve after compensating in the elapsed time, and blue dotted line is do not carry out processing the curve after aiming to time delay.As seen from Figure 3 when not considering time delay, attitude misalignment evaluated error is comparatively large, and the attitude misalignment error of three axles is respectively 15.2mrad ,-0.59mrad ,-5.5mrad.And attitude misalignment evaluated error can be observed restrain fast after 10s after use this method, the attitude misalignment error of three axles is respectively-0.1mrad, 0.01mrad ,-0.22mrad.Simultaneously this method estimates that time delay be 0.985s exactly as can be seen from Figure 4.In sum, this method can estimate time delay effectively, exactly, and the impact that brings to Transfer Alignment of compensating time delay effectively, meet high precision and the rapidity requirement of Transfer Alignment.

Claims (6)

1., based on a moving base Transfer Alignment delay compensation method for optimum attitude coupling, it is characterized in that, comprise the following steps:

Step 1, utilizes the navigation information antithetical phrase inertial navigation system of main inertial navigation system to carry out coarse alignment;

Step 2, main inertial navigation system and sub-inertial navigation system carry out navigation calculation respectively, and the speed obtained and attitude information are transferred to sub-inertial navigation system by main inertial navigation system;

Step 3, the strap-down matrix of main and sub inertial navigation system is obtained respectively according to navigation calculation result, the established angle compensation matrix of constructor inertial navigation system, constructs observed quantity in sub-inertial navigation system simultaneously, namely obtains the velocity contrast between main and sub inertial navigation system and measures misalignment;

Step 4, carry out standard Kalman filtering iteration to resolve: set up strapdown inertial navitation system (SINS) state equation, systematic observation equation and systematic perspective and measure, and carry out Kalman filtering Iterative, obtain the time delay estimated value of main and sub inertial navigation system Transfer Alignment and compensate, obtaining the attitude misalignment of the sub-inertial navigation system after to time delay equalization.

2. the moving base Transfer Alignment delay compensation method based on optimum attitude coupling according to claim 1, it is characterized in that, the navigation information antithetical phrase inertial navigation system of main inertial navigation system is utilized to carry out coarse alignment described in step 1, be transferred to sub-inertial navigation system by the speed of main inertial navigation system, attitude, positional information, sub-inertial navigation system utilizes the information that main inertial navigation is transmitted to complete initial work.

3. the moving base Transfer Alignment delay compensation method based on optimum attitude coupling according to claim 1, is characterized in that, carry out standard Kalman filtering iteration and resolve described in step 4, specific as follows:

1st step, sets up ins error model according to the mechanization of strapdown inertial navitation system (SINS), obtains the error equation of system, comprises attitude error equations, velocity error equation and inertial device error equation;

2nd step, according to the state equation of ins error model and systematic error establishing equation strapdown inertial navitation system (SINS);

3rd step, chooses the velocity contrast between main and sub inertial navigation system and measures misalignment as observed quantity, the relation derived the misaligned angle of the platform, attitude misalignment and measure between misalignment, and then obtaining optimum attitude matching algorithm;

4th step, Kalman filtering Iterative is carried out in observed quantity according to the system state equation set up, systematic observation equation and system, obtains the time delay estimated value of main and sub inertial navigation system Transfer Alignment and the attitude misalignment to the sub-inertial navigation system after time delay equalization.

4. the moving base Transfer Alignment delay compensation method based on optimum attitude coupling according to claim 3, it is characterized in that, described in the 1st step, the error equation of system comprises attitude error equations, velocity error equation and inertial device error equation, specific as follows:

(1.1) attitude error equations and velocity error equation are:

$\left\{\begin{array}{c}{\stackrel{\·}{\mathrm{\φ}}}_E={\mathrm{\φ}}_N{w}_{\mathrm{ie}}\sin L+{\mathrm{\φ}}_N{V}_E\tan L/(R_N+h)-{\mathrm{\φ}}_U{w}_{\mathrm{ie}}\cos L\\ -{\mathrm{\φ}}_U{V}_E/(R_N+h)-\mathrm{\δ}{V}_N/(R_N+h)-{\mathrm{\ϵ}}_E\\ {\stackrel{\·}{\mathrm{\φ}}}_N=-{\mathrm{\φ}}_E{w}_{\mathrm{ie}}\sin L-{\mathrm{\φ}}_E{V}_E\tan L/(R_N+h)\\ -{\mathrm{\φ}}_U{V}_N/(R_M+h)+{\mathrm{\δV}}_E/(R_N+h)-{\mathrm{\ϵ}}_N\\ {\stackrel{\·}{\mathrm{\φ}}}_U={\mathrm{\φ}}_E{w}_{\mathrm{ie}}\cos L+{\mathrm{\φ}}_E{V}_E/(R_N+h)+{\mathrm{\φ}}_N{V}_N/(R_M+h)\\ +{\mathrm{\δV}}_E\tan L/(R_N+h)-{\mathrm{\ϵ}}_U\\ \mathrm{\δ}{\stackrel{\·}{V}}_E=-{\mathrm{\φ}}_N{f}_U+{\mathrm{\φ}}_U{f}_N+{\mathrm{\δV}}_E{V}_N\tan L/(R_M+h)\\ -{\mathrm{\δV}}_E{V}_U/(R_M+h)+{2\mathrm{\δV}}_N{w}_{\mathrm{ie}}\sin L-{\mathrm{\δV}}_E{V}_E\tan L/(R_N+h)\\ -{2\mathrm{\δV}}_U{w}_{\mathrm{ie}}\cos L-{\mathrm{\δV}}_U{V}_E/(R_N+h)+{\▿}_E\\ \mathrm{\δ}{\stackrel{\·}{V}}_N={\mathrm{\φ}}_E{f}_U-{\mathrm{\φ}}_U{f}_E-{2\mathrm{\δV}}_E{w}_{\mathrm{ie}}\sin L-{\mathrm{\δV}}_E{V}_E\tan L/(R_N+h)\\ -{\mathrm{\δV}}_N{V}_U/(R_M+h)-{\mathrm{\δV}}_U{V}_N/(R_M+h)+{\▿}_N\\ \mathrm{\δ}{\stackrel{\·}{V}}_U=-{\mathrm{\φ}}_E{f}_N+{\mathrm{\φ}}_N{f}_E+2{\mathrm{\δV}}_E{w}_{\mathrm{ie}}\cos L+{\mathrm{\δV}}_E{V}_E/(R_N+h)\\ +2\mathrm{\δ}{V}_N{V}_N/(R_M+h)+{\▿}_U\end{array}\right.$

In formula, φ _e, φ _n, φ _ube respectively the misaligned angle of the platform in east, north, direction, sky, δ V _e, δ V _n, δ V _ube respectively the velocity error in carrier east, north, direction, sky, V _e, V _n, V _ube respectively the speed in east, north, direction, sky, L, h represent latitude and height respectively, R _mfor the radius-of-curvature of each point on ellipsoid meridian circle, R _nfor the radius-of-curvature of each point on prime vertical, w _iefor earth rotation angular speed, f _e, f _n, f _uinertial navigation system accelerometer measures to specific force be ratio force component on Xia Dong, north, direction, three, sky by the navigation obtained after coordinate conversion, ε _e, ε _n, ε _ube respectively the component that the equivalence of gyro in geographic coordinate system drifts in east, north, direction, sky, ▽ _e, ▽ _n, ▽ _ube respectively the component that the equivalence of accelerometer in geographic coordinate system is biased in east, north, direction, sky;

Speed V _iand specific force f _ithere is provided by main inertial navigation system, wherein i=E, N, U; The equivalence drift ε of gyro in geographic coordinate system _i▽ is biased with the equivalence of accelerometer _i, short owing to aiming at the time, these equivalents are random constant value, namely have:

${\stackrel{\·}{\mathrm{\ϵ}}}_i=0(i=E,N,U)$

${\stackrel{\·}{\▿}}_i=0(i=E,N,U)$

(1.2) alignment error angle equation is:

${\stackrel{\·}{\mathrm{\λ}}}_i=0(i=E,N,U)$

Using the time delay in Transfer Alignment as random constant value process, namely the model of main inertial navigation system time delay Δ t is:

$\mathrm{\Δ}\stackrel{\·}{t}=0$

Wherein, λ _e, λ _n, λ _uto tie up to the component on x, y, z axle at carrier for the fix error angle of the relatively main inertial navigation system of sub-inertial navigation system.

5. the moving base Transfer Alignment delay compensation method based on optimum attitude coupling according to claim 3, it is characterized in that, described in the 2nd step, the state equation of strapdown inertial navitation system (SINS) is shown below:

$\stackrel{\·}{X}=\mathrm{FX}+\mathrm{GW}$

In formula, X is system state vector, represent the derivative of system state vector, F is systematic state transfer matrix, and G is that system noise drives matrix, and W is system noise vector, specific as follows:

(2.1) X is system state vector:

X＝[φ _iδV _iε _i▽ _iλ _iΔt] _16×1，i＝E,N,U

(2.2) F is systematic state transfer matrix:

Matrix-block F in systematic state transfer matrix ₁with F ₂as follows:

$F_1={\left[\begin{array}{ccc}0& {\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L& -({\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})\\ -({\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L)& 0& -\frac{V_N}{R_M+h}\\ {\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h}& \frac{V_N}{R_M+h}& 0\\ 0& -f_u& f_N\\ f_U& 0& -f_E\\ -f_N& f_E& 0\end{array}\right]}_{6\×3}$

$F_2={\left[\begin{array}{ccc}0& -\frac{1}{R_M+h}& 0\\ \frac{V_N}{R_M+h}& \frac{1}{R_N+h}& 0\\ \frac{\tan L}{R_N+h}& 0& 0\\ \frac{V_N}{R_M+h}\tan L-\frac{V_U}{R_M+h}& {2\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L& -({2\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})\\ -2({\mathrm{\ω}}_{\mathrm{ie}}\sin L+\frac{V_E}{R_N+h}\tan L)& -\frac{V_U}{R_M+h}& -\frac{V_N}{R_M+h}\\ 2({\mathrm{\ω}}_{\mathrm{ie}}\cos L+\frac{V_E}{R_N+h})& \frac{2V_N}{R_M+h}& 0\end{array}\right]}_{6\×3}$

(2.3) G is that system noise drives matrix:

$G={\left[\begin{array}{cc}-C_b^n& 0_{3\×3}\\ 0_{3\×3}& C_b^n\\ 0_{10\×3}& 0_{10\×3}\end{array}\right]}_{16\×6}$

(2.4) W is system noise vector matrix:

W＝[W _GxW _GyW _GzW _▽xW _▽yW _▽z] ^T _6×1

And suppose that it is zero mean Gaussian white noise, covariance matrix is E (WW ^t)=Q, Q is systematic procedure noise variance matrix;

In formula, for attitude matrix, W _gx, W _gy, W _gzbe respectively the component of Modelling of Random Drift of Gyroscopes on x, y, z axle, W _{▽ x}, W _{▽ y}, W _{▽ z}be respectively the component of accelerometer bias on x, y, z axle.

6. the moving base Transfer Alignment delay compensation method based on optimum attitude coupling according to claim 3, it is characterized in that, optimum attitude matching algorithm described in the 3rd step, is specially:

(3.1) choose the velocity contrast between main and sub inertial navigation system and measure misalignment φ _mas observed quantity, obtaining system measurements equation is:

Z＝HX+V

In formula, Z=[φ _mxφ _myφ _mzδ V _eδ V _nδ V _u] be observed quantity, φ _mx, φ _my, φ _mzfor measuring the component of misalignment on x, y, z axle; V be measurement noise and for average be the white Gaussian noise of zero, its covariance is E [VV ^t]=R, R is measuring noise square difference battle array;

(3.2) misalignment φ is measured _mobtained by following derivation:

${\tilde{C}}_s^m{C}_n^{s^{\text{'}}}{C}_m^n=I-{\mathrm{\φ}}_m\×$

In formula, for the transition matrix between main and sub inertial navigation system body coordinate system, for the transposition of sub-inertial navigation system attitude matrix, be main inertial navigation system attitude matrix, be the offset of sub-inertial navigation system established angle attitude matrix, also existing after this matrix compensation can not the fix error angle λ of direct compensation, and has:

${\tilde{C}}_s^m=(I-\mathrm{\λ}\×)C_s^m$

Therefore can obtain:

$\begin{array}{c}{\tilde{C}}_s^m{C}_n^{s^{\text{'}}}{C}_m^n={\tilde{C}}_s^m{C}_{n^{\text{'}}}^s{C}_m^n={\tilde{C}}_s^m{C}_m^s{C}_n^m{C}_{n^{\text{'}}}^n{C}_m^n\\ ={\tilde{C}}_s^m{C}_m^s(I+C_n^m\mathrm{\φ}\×C_m^n)\\ =(I-\mathrm{\λ}\×)(I+C_n^m\mathrm{\φ}\×C_m^n)\\ =(I-\mathrm{\λ}\×)(I+\left(C_n^m\mathrm{\φ}\right)\×)\\ \≈I+\left(C_n^m\mathrm{\φ}\right)\×-\mathrm{\λ}\×\\ =I-{\mathrm{\φ}}_m\×\end{array}$

Namely obtain optimum attitude matching algorithm;

In formula for matrix transposition, for matrix transposition, for sub-inertial navigation mathematical platform coordinate is tied to the transition matrix of navigational coordinate system, φ is sub-Inertial navigation platform misalignment;

(3.3), after considering time delay, misalignment φ is measured _mbe expressed as:

${\mathrm{\φ}}_m=\mathrm{\λ}-C_n^m\mathrm{\φ}+{\mathrm{\ω}}_m\mathrm{\Δt}$

Velocity error is:

δv＝v _s(t+Δt)-v _m(t)-f _m(t)Δt

In formula, v _s(t+ Δ t) for sub-inertial navigation is in the speed of t+ Δ t, v _mt () is the speed of main inertial navigation in t, f _mt () is the specific force of main inertial navigation in t;

The measurement matrix of system can be obtained thus:

$H={\left[\begin{array}{cccccc}-C_n^b& 0_{3\×3}& 0_{3\×3}& 0_{3\×3}& I_{3\×3}& B_{3\×1}\\ 0_{3\×3}& I_{3\×3}& 0_{3\×3}& 0_{3\×3}& 0_{3\×3}& C_{3\×1}\end{array}\right]}_{6\×16}$

Wherein:

$B_{3\×1}=\left[\begin{array}{c}{f}_{\mathrm{ME}}\\ f_{\mathrm{MN}}\\ f_{\mathrm{MU}}\end{array}\right],C_{3\×1}=\left[\begin{array}{c}{\mathrm{\ω}}_{\mathrm{mx}}\\ {\mathrm{\ω}}_{\mathrm{my}}\\ {\mathrm{\ω}}_{\mathrm{mz}}\end{array}\right]$

F in formula _mE, f _mN, f _mUbe respectively the ratio force component of ratio force information on east, north, direction, three, sky that the moment is aimed in main inertial navigation, ω _mx, ω _my, ω _mzthe angular velocity on body axis system x, y, z axle is engraved in when being main inertial navigation aligning.