CN1908584A - Method for determining initial status of strapdown inertial navigation system - Google Patents

Abstract

The initial attitude determination method for SINS comprises: rotating the SINS from initial position to any one position round arbitrary 3D axis; according to SINS output on first position and the relation of earth rotational angular velocity and acceleration of gravity, determining the initial attitude primarily; then, using Kalman filter to estimate the gyro constant drift and other values for more accurate initial attitude. This invention improves observability and precision.

Description

A kind of initial status of strapdown inertial navigation system is determined method

Technical field

The present invention relates to definite method of a kind of strapdown inertial navigation system (SINS) initial attitude, can be used for various in the initial attitude of high-precision strapdown inertial navigation system determine, be particularly suitable for not having indexing mechanism when airborne SINS installs, or the indexing mechanism precision is not high, the corner condition of limited.

Background technology

The ultimate principle of strapdown inertial navigation system (SINS) is the mechanics law according to the relative inertness space of newton's proposition, utilize the line motion and the angular motion parameter in gyroscope, accelerometer measures carrier relative inertness space, under given motion starting condition, carry out integral operation by computing machine, position, speed and attitude information are provided continuously, in real time.SINS relies on its own inertial sensitive element fully, do not rely on any external information and measure navigational parameter, therefore, it has good concealment, be not subjected to the weather condition restriction, advantage such as no signal is lost, and is interference-free, be a kind of complete autonomous type, round-the-clock navigational system, be widely used in fields such as Aeronautics and Astronautics, navigation.According to the ultimate principle of SINS, SINS must obtain initial information before navigator fix resolves, comprise initial position, speed and attitude.Initial position and the velocity information of SINS obtain easily than initial attitude, and the precision after initial attitude is determined is exactly the initial precision of SINS when entering the navigation duty.Carry out fast accurate initial attitude when therefore, SINS starts working and determine it is a crucial step.

Existing strapdown inertial navitation system (SINS) initial attitude is determined to be divided into coarse alignment and two stages of fine alignment.Coarse alignment stage is exactly under quiet pedestal condition, with the direct introducing computing machine of the gyroscope of (fixedly two positions or two positions arbitrarily) on single position or two positions and accelerometer output, calculates the initial attitude of carrier.When using the method, usually ignore the error and the external interference factor of gyroscope and accelerometer, yet these factors can cause error, so the initial attitude computational accuracy is not high.Especially, when the gyroscope on adopting fixing two positions and the output of accelerometer are calculated, require SINS around Z axle Rotate 180 degree or 90 degree, this just need be installed in SINS on the indexing mechanism, utilize indexing mechanism to realize the rotation of 180 degree or 90 degree, extremely inconvenient when engineering is used, and also the precision of indexing mechanism is not high, rotational angle also can't accurately be measured, and has reduced the precision that initial attitude is determined.Because the restriction of SINS installation site in the concrete engineering, also exist rotational angle can't satisfy the situation that 180 degree or 90 degree require, at this moment, existing fixed two positions initial attitude determines that method can't use.In addition, when gyroscope on utilizing any two positions and accelerometer output, need to calculate arcsin function, the error of gyroscope and accelerometer itself and measuring error etc. cause the result of calculation instability easily, the imaginary number phenomenon occurs, therefore often need carry out repeatedly the collection and the calculating of gyroscope and accelerometer output on the two positions arbitrarily, result of calculation is selected, after averaging, as the initial attitude of carrier.So, the time that initial attitude is determined will be multiplied, and the precision that initial attitude calculates also can't be guaranteed.

The fine alignment stage is to carry out on the basis of coarse alignment, utilizes the state-space method of modern control theory, and the data of gyroscope and accelerometer output are handled.When the data of single position are handled, the considerable degree of orientation misalignment is poor, speed of convergence is slower, required time is longer, and gyroscope and accelerometer error are unobservable, therefore, can't estimate preferably, do not reach the purpose that improves the initial attitude precision, can not when initial attitude calculates, realize demarcation gyroscope and accelerometer.When the data of fixing two positions are handled, as above to narrate, existing fixed two positions initial attitude determines that there is the restriction of the anglec of rotation in method, and higher to the indexing mechanism accuracy requirement, often can not use in the concrete engineering.

Summary of the invention

Technology of the present invention is dealt with problems and is: overcome the deficiencies in the prior art, provide a kind of accurately, initial status of strapdown inertial navigation system is determined method easily.

Technical solution of the present invention is: a kind of initial status of strapdown inertial navigation system is determined method,

Concrete steps are as follows:

(1) the SINS preheating is prepared, and concrete setup time is according to different systems and difference;

(2) SINS ready after, keep SINS in initial position (being called primary importance) transfixion, gather gyroscope output and accelerometer and export;

(3) utilize accelerometer output and the relation of acceleration of gravity and the relation of gyroscope output and earth rotation angular speed, calculate the course angle  of primary importance ₁, pitching angle theta ₁With roll angle γ ₁

(4) need not indexing mechanism, SINS is rotated to any one position (being called the second place) from primary importance around the space three-dimensional arbitrary axis, keep SINS, gather gyroscope output and accelerometer output in second place transfixion by any means;

(5) adopt Kalman Filter Technology, with  ₁, θ ₁And γ ₁As initial parameter, the data of gyroscope and accelerometer output on two positions are handled.Because the change of SINS position, changed the system matrix in the SINS error model, thereby the observability of SINS system improves, filter effect is improved, and the error angle that calculates when better estimating the second place between geographic coordinate system n ' and the true geographic coordinate system n (abbreviates misalignment φ as _x, φ _yAnd φ _z) and gyroscope constant value drift, accelerometer often be worth biasing;

(6) utilize the φ that estimates _x, φ _yAnd φ _zCalculate the transition matrix C between true geographic coordinate system n and the calculating geographic coordinate system n ' _{N '} ⁿAccording to the angle increment or the angular velocity information of gyroscope output, adopt the hypercomplex number method, calculate the transition matrix C between carrier coordinate system b and the calculating geographic coordinate system n ' _b ^{N '}By C _{N '} ⁿAnd C _b ^{N '}, calculate the transition matrix C between carrier coordinate system b and the true geographic coordinate system n _b ⁿ, again by C _b ⁿCalculate the course angle  of the second place ₂, pitching angle theta ₂With roll angle γ ₂, with its initial attitude as SINS.

Principle of the present invention is: when SINS kept transfixion in some positions, accelerometer output and acceleration of gravity and gyroscope output had following relation with the earth rotation angular speed:

$\left[\begin{array}{c}{f}_{x1}\\ f_{y1}\\ f_{z1}\end{array}\right]=C_n^b\left[\begin{array}{c}0\\ 0\\ g\end{array}\right]...\left(1\right)$

$\left[\begin{array}{c}{\mathrm{\ω}}_{x1}\\ {\mathrm{\ω}}_{y1}\\ {\mathrm{\ω}}_{z1}\end{array}\right]=C_n^b\left[\begin{array}{c}0\\ {\mathrm{\ω}}_{\mathrm{ie}}\cos L\\ {\mathrm{\ω}}_{\mathrm{ie}}\sin L\end{array}\right]...\left(2\right)$

Wherein, f _X1, f _Y1And f _Z1And ω _X1, ω _Y1And ω _Z1The respectively specific force and the angular speed of X-axis, Y-axis and the output of Z axle of SINS on the position for this reason; G is an acceleration of gravity; ω _IeBe the earth rotation angular speed, its in east, north, old name for the Arabian countries in the Middle East make progress be projected as Ω=[0 ω _IeCosL ω _IeSinL]; L is a local latitude; C _n ^bFor navigation coordinate is tied to the transition matrix of carrier coordinate system, $C_n^b={\left(C_b^n\right)}^T=\left[\begin{array}{ccc}{C}_{11}& C_{13}& C_{13}\\ C_{21}& C_{12}& C_{23}\\ C_{31}& C_{32}& C_{33}\end{array}\right].$

C _n ^bCan be expressed as this position course angle  ₁, pitching angle theta ₁With roll angle γ ₁Expression formula, utilize (1) formula and (2) formula can calculate the  of this position ₁, β ₁And γ ₁Computing formula is as follows:

By (1), (2) Shi Kede:

$C_{13}=\frac{f_{x1}}{g}$

$C_{23}=\frac{f_{y1}}{g}$

$C_{33}=\frac{f_{z1}}{g}$

$C_{12}=\frac{{\mathrm{\ω}}_{x1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{x1}\tan L}{g}$

$C_{22}=\frac{{\mathrm{\ω}}_{y1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{y1}\tan L}{g}...\left(3\right)$

$C_{32}=\frac{{\mathrm{\ω}}_{z1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{z1}\tan L}{g}$

C ₁₁＝C ₂₂C ₃₃-C ₂₃C ₃₂

C ₂₁＝-C ₁₂C ₃₃+C ₁₃C ₃₂

C ₃₁＝C ₁₂C ₂₃-C ₁₃C ₂₂

Course angle  ₁, pitching angle theta ₁With roll angle γ ₁The main value computing formula be:

If course angle  ₁, pitching angle theta ₁With roll angle γ ₁Span be defined as [0,2 π], [π ,+π],  so ₁, θ ₁And γ ₁True value can determine as follows.

θ ₁=θ _{1 is main}(5)

By the definite  of (5) formula ₁, θ ₁And γ ₁Be SINS at this locational course angle, the angle of pitch and roll angle.

Owing to do not consider the measuring error of accelerometer biasing, gyroscopic drift and accelerometer and gyroscope output information in (1) formula and (2) formula, the course angle  that tries to achieve ₁, pitching angle theta ₁With roll angle γ ₁Can not the accurate description carrier coordinate system and local geographic coordinate system between true angular relationship.Therefore, should further utilize modern estimation theory that the initial attitude misalignment is estimated from stochastic error and random disturbance on this basis.

Utilize Kalman Filter Technology, with  ₁, θ ₁And γ ₁As initial parameter, can estimate the error angle that calculates between geographic coordinate system n ' and the true geographic coordinate system n, proofread and correct C _b ^{N '}After, can obtain initial attitude more accurately.But, when Kalman filtering is handled the accelerometer of single position and gyroscope output, the incomplete may observe of system, wherein, two accelerometers and a gyrostatic error are unobservable, so estimation effect is poor, do not reach the purpose that improves the initial attitude precision.The present invention is by rotating to any one position from primary importance around the space three-dimensional arbitrary axis with SINS, promptly change the position of SINS, change the system matrix in the SINS error model, thereby improve the observability of SINS system, improve the Kalman filtering effect, estimate the error of misalignment and gyroscope, accelerometer better.The misalignment that utilization estimates is to transition matrix C _b ^{N '}Proofread and correct, obtain course angle, the angle of pitch and roll angle more accurately.

The present invention's advantage compared with prior art is:

(1) the present invention broken that conventional fixed two positions initial attitude calculates need be by indexing mechanism with the constraints of SINS around Z axle Rotate 180 degree or 90 degree, but need not to pass through indexing mechanism, SINS is rotated to the optional position around arbitrary axis, is a kind of any two-position initial attitude computing method of space three-dimensional.Avoided because of the indexing mechanism precision is not high, the reduction of the fixedly two positions initial attitude computational accuracy that causes has promptly improved the precision that initial attitude calculates.In addition, SINS being rotated to the optional position around arbitrary axis also greatly facilitates in actual application in engineering.

(2) the present invention utilizes the data of gyroscope and accelerometer output on two positions, improve the observability of SINS system, improve the filter effect of Kalman filter, estimate misalignment and gyroscope constant value drift better, accelerometer often is worth biasing, after the misalignment that utilization estimates is proofreaied and correct attitude matrix, obtain course angle, the angle of pitch and roll angle more accurately.

(3) the present invention can finish to survey when initial attitude calculates and float and the calibration task, has not only improved the precision that system's initial attitude calculates, and calibration precision also is improved, and recompenses at the SINS navigational state, can improve navigation and positioning accuracy effectively.

Description of drawings

Fig. 1 determines the process flow diagram of method for initial attitude of the present invention;

Fig. 2 is the synoptic diagram of course angle , pitching angle theta and roll angle γ, Ox among the figure _ny _nz _nBe navigation coordinate system, i.e. the geographical coordinate system in sky, northeast, Ox _by _bz _bBe carrier coordinate system.Wherein, Fig. 2 a represents that from navigation coordinate be Ox _ny _nz _nBe rotated counterclockwise  and carrier coordinate system Ox around the zn axle _by _bz _bOverlap,  is course angle; Fig. 2 b represents that from navigation coordinate be Ox _ny _nz _nAround x _nAxle is rotated counterclockwise θ and carrier coordinate system Ox _by _bz _bOverlap, θ is the angle of pitch; Fig. 2 c represents that from navigation coordinate be Ox _ny _nz _nAround y _nAxle is rotated counterclockwise γ and carrier coordinate system Ox _by _bz _bOverlap, γ is roll angle.

Embodiment

As shown in Figure 1, specific implementation method of the present invention is as follows:

1, the preparation of strapdown inertial navigation system

After the SINS start, enter standby condition.

2, primary importance data acquisition

SINS is ready, keeps SINS in initial position (being called primary importance) transfixion, gathers gyroscope output in 5 minutes and accelerometer output, if but the lower proper extension of the precision of SINS is adopted several times.

3, primary importance Attitude Calculation

Navigation coordinate system is taken as the geographical coordinate system in sky, northeast, the course angle  of primary importance place ₁, pitching angle theta ₁With roll angle γ ₁Definition shown in Fig. 2 a, Fig. 2 b and Fig. 2 c.

Accelerometer output and acceleration of gravity and gyroscope output have following relation with the earth rotation angular speed:

$\left[\begin{array}{c}{f}_{x1}\\ f_{y1}\\ f_{z1}\end{array}\right]=C_n^b\left[\begin{array}{c}0\\ 0\\ g\end{array}\right]...\left(6\right)$

$\left[\begin{array}{c}{\mathrm{\ω}}_{x1}\\ {\mathrm{\ω}}_{y1}\\ {\mathrm{\ω}}_{z1}\end{array}\right]=C_n^b\left[\begin{array}{c}0\\ {\mathrm{\ω}}_{\mathrm{ie}}\cos L\\ {\mathrm{\ω}}_{\mathrm{ie}}\sin L\end{array}\right]...\left(7\right)$

In the formula, f _X1, f _Y1And f _Z1And ω _X1, ω _Y1And ω _Z1Be respectively the specific force and the angular speed of X-axis, Y-axis and the output of Z axle of SINS on first position; G is an acceleration of gravity; ω _IeBe the earth rotation angular speed, its in east, north, old name for the Arabian countries in the Middle East make progress be projected as Ω=[0 ω _IeCosL ω _IeSinL], L represents local latitude; C _n ^bFor navigation is tied to the transition matrix that carrier is, can be written as:

$C_n^b={\left(C_b^n\right)}^T=\left[\begin{array}{ccc}{C}_{11}& C_{13}& C_{13}\\ C_{21}& C_{12}& C_{23}\\ C_{31}& C_{32}& C_{33}\end{array}\right].$

By (6), (7) Shi Kede:

$C_{13}=\frac{f_{x1}}{g}$

$C_{23}=\frac{f_{y1}}{g}$

$C_{33}=\frac{f_{z1}}{g}$

$C_{12}=\frac{{\mathrm{\ω}}_{x1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{x1}\tan L}{g}$

$C_{22}=\frac{{\mathrm{\ω}}_{y1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{y1}\tan L}{g}...\left(8\right)$

$C_{32}=\frac{{\mathrm{\ω}}_{z1}}{{\mathrm{\ω}}_{\mathrm{ie}}\cos L}-\frac{f_{z1}\tan L}{g}$

C ₁₁＝C ₂₂C ₃₃-C ₂₃C ₃₂

C ₂₁＝-C ₁₂C ₃₃+C ₁₃C ₃₂

C ₃₁＝C ₁₂C ₂₃-C ₁₃C ₂₂

Course angle  ₁, pitching angle theta ₁With roll angle γ ₁The main value computing formula be:

θ _{1 is main}=arcsin (C ₂₃) (9)

If course angle  ₁, pitching angle theta ₁With roll angle γ ₁Span be defined as [0,2 π], [π ,+π],  so ₁, θ ₁And γ ₁True value can determine as follows.

θ ₁=θ _{1 is main}(10)

By the definite  of (10) formula ₁, θ ₁And γ ₁Be course angle, the angle of pitch and the roll angle of SINS on primary importance.

4, second place data acquisition

By any means SINS is rotated to any one position (being called the second place) from initial position around the space three-dimensional arbitrary axis, keep SINS, gather gyroscope output in 5 minutes and accelerometer output in second place transfixion.

5, the data of two positions are carried out Filtering Processing

With  ₁, θ ₁And γ ₁As initial parameter, utilize Kalman Filter Technology, the data of gyroscope and accelerometer output on two positions are handled, accurately estimate misalignment φ _x, φ _yAnd φ _z(under the geographical coordinate system in sky, northeast is φ _E, φ _NAnd φ _U) and gyroscope constant value drift, accelerometer often be worth biasing.

(1) the SINS initial attitude is determined the foundation of error model

Navigation coordinate system is taken as the geographical coordinate system in sky, northeast, and position and vertical speed error are omitted, and accelerometer and gyrostatic error are considered as setovering at random and add white-noise process, and this moment, the error model of SINS was:

$\left[\begin{array}{c}\mathrm{\δ}{\stackrel{\·}{V}}_E\\ \mathrm{\δ}{\stackrel{\·}{V}}_N\\ {\stackrel{\·}{\mathrm{\φ}}}_E\\ {\stackrel{\·}{\mathrm{\φ}}}_N\\ {\stackrel{\·}{\mathrm{\φ}}}_U\\ {\stackrel{\·}{\▿}}_x\\ {\stackrel{\·}{\▿}}_y\\ {\stackrel{\·}{\mathrm{\ϵ}}}_x\\ {\stackrel{\·}{\mathrm{\ϵ}}}_y\\ {\stackrel{\·}{\mathrm{\ϵ}}}_z\end{array}\right]=\left[\begin{array}{cccccccccc}0& 2{\mathrm{\Ω}}_U& 0& -g& 0& T_{11}& T_{12}& 0& 0& 0\\ -2{\mathrm{\Ω}}_U& 0& g& 0& 0& T_{21}& T_{22}& 0& 0& 0\\ 0& 0& 0& {\mathrm{\Ω}}_U& -{\mathrm{\Ω}}_N& 0& 0& T_{11}& T_{12}& T_{13}\\ 0& 0& -{\mathrm{\Ω}}_U& 0& 0& 0& 0& T_{21}& T_{22}& T_{23}\\ 0& 0& -{\mathrm{\Ω}}_N& 0& 0& 0& 0& T_{31}& T_{32}& T_{33}\\ 0& 0& 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right]\left[\begin{array}{c}\mathrm{\δ}{V}_E\\ \mathrm{\δ}{V}_N\\ {\mathrm{\φ}}_E\\ {\mathrm{\φ}}_N\\ {\mathrm{\φ}}_U\\ {\▿}_x\\ {\▿}_y\\ {\mathrm{\ϵ}}_x\\ {\mathrm{\ϵ}}_y\\ {\mathrm{\ϵ}}_z\end{array}\right]...\left(11\right)$

In the formula, subscript E, N, U represent east, north, sky respectively.Earth rotation angular speed ω _IeIn east, north, old name for the Arabian countries in the Middle East make progress be projected as Ω=[0 ω _IeCosL ω _IeSinL]=[0 Ω _NΩ _U], L represents local latitude; Subscript x, y, z are carrier coordinate system; T _Ij(i=1,2,3; J=1,2,3) be attitude matrix C _b ⁿIn element,

$C_b^n{=\left\{T_{\mathrm{ij}}\right\}}_{i=\mathrm{1,2,3};j=\mathrm{1,2,3}}.$

(2) the SINS initial attitude is determined the foundation of Kalman filter model

For strapdown inertial navitation system (SINS), consider the random deviation of Gyroscope Random Drift Error and accelerometer, equation (11) is modified to following form:

$\left[\frac{{\stackrel{\·}{X}}_a\left(t\right)}{{\stackrel{\·}{X}}_b\left(t\right)}\right]=\left[\begin{array}{cc}F& T_i\\ 0_{5\×5}& 0_{5\×5}\end{array}\right]\left[\frac{X_a\left(t\right)}{X_b\left(t\right)}\right]+\left[\frac{W^{\′}\left(t\right)}{0_{5\×1}}\right]=A_{i}X\left(t\right)+W\left(t\right)...\left(12\right)$

In the formula, W (t) is N (O, white Gaussian noise Q); State variable X _a=[δ V _Eδ V _Nφ _Eφ _Nφ _U] ^T, X _b=[ _x _yε _xε _yε _z] ^TThe random noise state vector $W^{\′}\left(t\right)={\left[\begin{array}{ccccc}{w}_{\mathrm{\δ}{V}_E}& w_{\mathrm{\δ}{V}_N}& w_{\mathrm{\φE}}& w_{\mathrm{\φN}}& w_{\mathrm{\φU}}\end{array}\right]}^T,$ Wherein, δ V _E, δ V _NBe respectively east orientation and north orientation velocity error, φ _E, φ _NBe horizontal misalignment; φ _UBe the orientation misalignment;  _x,  _yBe accelerometer value biasing often at random, ε _x, ε _y, ε _zIt is the gyroscope Random Constant Drift; 0 _{5 * 5}With 0 _{5 * 1}Be the null matrix of specifying dimension; F and T _iTheing contents are as follows of representative:

$T_i=\left[\begin{array}{ccccc}{T}_{11}& T_{12}& 0& 0& 0\\ T_{21}& T_{22}& 0& 0& 0\\ 0& 0& T_{11}& T_{12}& T_{13}\\ 0& 0& T_{21}& T_{22}& T_{23}\\ 0& 0& T_{31}& T_{32}& T_{33}\end{array}\right],$ $F=\left[\begin{array}{ccccc}0& 2{\mathrm{\Ω}}_U& 0& -g& 0\\ -2{\mathrm{\Ω}}_U& 0& g& 0& 0\\ 0& 0& 0& {\mathrm{\Ω}}_U& -{\mathrm{\Ω}}_N\\ 0& 0& -{\mathrm{\Ω}}_U& 0& 0\\ 0& 0& {\mathrm{\Ω}}_N& 0& 0\end{array}\right]$

(12) formula is determined the system equation of Kalman filter model for the strapdown inertial navitation system (SINS) initial attitude.For the application card Thalmann filter carries out the optimal estimation of state vector, also need set up the systematic observation equation.Choosing two horizontal velocity errors is observed quantity, and the systematic observation equation of foundation is

$Z\left(t\right)=\left[\begin{array}{cccccccccc}1& 0& 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 1& 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right]\left[\begin{array}{c}{X}_a\\ X_b\end{array}\right]+\left[\begin{array}{c}{\mathrm{\η}}_E\\ {\mathrm{\η}}_N\end{array}\right]=\mathrm{HX}\left(t\right)+\mathrm{\η}\left(t\right)...\left(13\right)$

Wherein, η (t) is the systematic observation noise vector, is N (O, white Gaussian noise process R).

(3) foundation of Kalman Filtering for Discrete model

According to said system equation and observation equation, it is as follows to set up the Kalman Filtering for Discrete equation.

Filtering equations:

Gain equation:

$K_k=P_{k,k-1}{H}_k^T{[H_k{P}_{k,k-1}{H}_k^T+R_k]}^{-1}...\left(15\right)$

Prediction error variance equation:

$P_{k,k-1}={\mathrm{\Φ}}_{k,k-1}{P}_{k-1}{\mathrm{\Φ}}_{k,k-1}^T+Q_{k-1}...\left(16\right)$

Filtering error variance equation:

P _k＝[I-K _kH _k]P _k，k-1 (17)

In the formula, Φ _{K, k-1}Be the state-transition matrix (system matrix) of discretize, Q, R are respectively the covariance matrix of system noise and observation noise.

(4) filtering starting condition

X(0)＝0 _10×1；

The value of the corresponding medium accuracy SINS of P (0), Q and R is as follows:

P(0)＝diag{(0.3m/s) ²，(0.3m/s) ²，(30′) ²，(10″) ²，(10″) ²，

(100μg) ²，(100μg) ²，(0.1°) ²，(0.1°) ²，(0.1°) ²}；

Q＝diag{(100μg) ²，(100μg) ²，(0.1°) ²，(0.1°) ²，(0.1°) ²，0，0，0，0，0}；

R＝diag{(0.1m/s) ²，(0.1m/s) ²}。

6, computing gyroscope Random Constant Drift and accelerometer value biasing often at random

The  that wave filter estimates _x,  _yBe accelerometer value biasing often at random, ε _x, ε _y, ε _zBe the gyroscope Random Constant Drift.

7, the transition matrix C between calculating carrier coordinate system b and the calculating geographic coordinate system n ' _b ^{N '}

Can utilize the angle increment or the angular velocity information of gyroscope output, adopt the hypercomplex number method to calculate C _b ^{N '}, calculation procedure is as follows:

(1) utilizes course angle  ₁, pitching angle theta ₁With roll angle γ ₁Attitude during first position of initialization is calculated the initial conversion Matrix C _b ^{N '}With hypercomplex number q, computing formula is as follows:

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

Then have:

$q_0=\±\frac{1}{2}\sqrt{1+T_{11}+T_{22}-T_{33}}$

$q_1=\±\frac{1}{2}\sqrt{1+T_{11}+T_{22}-T_{33}}$

$q_2=\±\frac{1}{2}\sqrt{1+T_{11}+T_{22}-T_{33}}$

$q_3=\±\frac{1}{2}\sqrt{1+T_{11}+T_{22}-T_{33}}$

(2) upgrade hypercomplex number q ₀, q ₁, q ₂, q ₃With transition matrix C _b ^{N '}

$q(n+1)=\{(1-\frac{{\left(\mathrm{\Δ}{\mathrm{\θ}}_0\right)}^2}{8}+\frac{{\left(\mathrm{\Δ}{\mathrm{\θ}}_0\right)}^4}{384})I+(\frac{1}{2}-\frac{{\left(\mathrm{\Δ}{\mathrm{\θ}}_0\right)}^2}{48})\left(\mathrm{\Δ\θ}\right)\}q\left(n\right)...\left(19\right)$

Wherein,

$\mathrm{\Δ\θ}=\left[\begin{array}{cccc}0& -\mathrm{\Δ}{\mathrm{\θ}}_x& -\mathrm{\Δ}{\mathrm{\θ}}_y& -{\mathrm{\Δ\θ}}_z\\ {\mathrm{\Δ\θ}}_x& 0& {\mathrm{\Δ\θ}}_z& -{\mathrm{\Δ\θ}}_y\\ {\mathrm{\Δ\θ}}_y& {-\mathrm{\Δ\θ}}_z& 0& {\mathrm{\Δ\θ}}_x\\ {\mathrm{\Δ\θ}}_z& {\mathrm{\Δ\θ}}_y& {-\mathrm{\Δ\θ}}_x& 0\end{array}\right]$

$\mathrm{\Δ}{\mathrm{\θ}}_0=\sqrt{{\mathrm{\Δ\θ}}_x^2+{\mathrm{\Δ\θ}}_y^2+{\mathrm{\Δ\θ}}_z^2}$

Transition matrix C _b ^{N '}More new formula as follows:

$C_b^{n^{\′}}=\left[\begin{array}{ccc}{q}_0^2+q_1^2-q_2^2-q_3^2& 2(q_1{q}_2-q_0{q}_3)& 2(q_1{q}_3+q_0{q}_2)\\ 2(q_1{q}_2+q_0{q}_3)& q_0^2-q_1^2+q_2^2-q_3^2& 2(q_2{q}_3-q_0{q}_1)\\ 2(q_1{q}_3-q_0{q}_2)& 2(q_2{q}_3+q_0{q}_1)& q_0^2-q_1^2-q_2^2+q_3^2\end{array}\right]...\left(20\right)$

8, calculate course angle  ₂, pitching angle theta ₂With roll angle γ ₂

The φ that utilizes Kalman Filter Estimation to go out _E, φ _N, φ _UCalculate the transition matrix C between true geographic coordinate system n and the calculating geographic coordinate system n ' _{N '} ⁿAccording to C _{N '} ⁿ(20) C that calculates of formula _b ^{N '}, calculate the transition matrix C between carrier coordinate system b and the true geographic coordinate system n _b ⁿ, again by C _b ⁿCalculate the course angle  of the second place ₂, pitching angle theta ₂With roll angle γ ₂, with its initial attitude as SINS.Concrete calculation procedure is as follows:

(1) the transition matrix C between true geographic coordinate system n of calculating and the calculating geographic coordinate system n ' _n ^{N '}

$C_{n^{\′}}^n=\left[\begin{array}{ccc}1& -{\mathrm{\φ}}_U& {\mathrm{\φ}}_N\\ {\mathrm{\φ}}_U& 1& -{\mathrm{\φ}}_E\\ -{\mathrm{\φ}}_N& {\mathrm{\φ}}_E& 1\end{array}\right]...\left(21\right)$

(2) the transition matrix C between calculating carrier coordinate system b and the true geographic coordinate system n _b ⁿ

$C_b^n=C_{n^{\′}}^n{C}_b^{n^{\′}}...\left(22\right)$

(3) calculate course angle  ₂, pitching angle theta ₂With roll angle γ ₂

Course angle  ₂, pitching angle theta ₂With roll angle γ ₂Definition shown in Fig. 2 a, Fig. 2 b and Fig. 2 c.

The C that (22) formula is calculated _b ⁿBe designated as

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

Again because

Therefore, by (23) formula and (24) formula, can determine course angle  ₂, pitching angle theta ₂With roll angle γ ₂Main value, promptly

If course angle  ₂, pitching angle theta ₂With roll angle γ ₂Span be defined as respectively [0,2 π], [π ,+π].So,  ₂, θ ₂And γ ₂True value can determine by following formula:

θ ₂=θ _{2 is main}(26)

By the definite  of (26) formula ₂, θ ₂And γ ₂Be course angle, the angle of pitch and the roll angle of SINS on the second place, it is entered the initial attitude of navigation duty as SINS.

Claims (1)

1, a kind of initial status of strapdown inertial navigation system is determined method, it is characterized in that may further comprise the steps:

(1) the SINS preheating is ready, keeps SINS at initial position, is called primary importance, and transfixion is gathered gyroscope output and accelerometer output;

(2), calculate the course angle  of primary importance according to accelerometer output and the relation of acceleration of gravity and the relation of gyroscope output and earth rotation angular speed ₁, pitching angle theta ₁With roll angle γ ₁

(3) SINS is rotated to any one position from primary importance around the space three-dimensional arbitrary axis, be called the second place, keep SINS, gather gyroscope output and accelerometer output in second place transfixion;

(4) adopt Kalman Filter Technology, with  ₁, θ ₁And γ ₁As initial parameter, the data of gyroscope and accelerometer output on two positions are handled, calculate the error angle between geographic coordinate system n ' and the true geographic coordinate system n when estimating the second place, abbreviate misalignment φ as _x, φ _yAnd φ _zAnd gyroscope constant value drift, accelerometer often are worth biasing;

(5) φ that utilizes Kalman Filter Estimation to go out _x, φ _yAnd φ z calculates the transition matrix C between true geographic coordinate system n and the calculating geographic coordinate system n ' _{N ＇} ⁿ, according to the angle increment or the angular velocity information of gyroscope output, adopt the hypercomplex number method, calculate the transition matrix C between carrier coordinate system b and the calculating geographic coordinate system n ' _b ^{N '}, again by C _b ⁿCalculate the course angle  of the second place ₂, pitching angle theta ₂With roll angle γ ₂, with its initial attitude as SINS.