High-precision initial alignment method

Abstract

The invention relates to a high-precision initial alignment method which comprises the following steps: a transfer alignment step: providing a main inertial navigation system and a sub inertial navigation system, simultaneously rotating for 90 degrees around a certain horizontal axis to erect, and obtaining a first attitude matrix of the sub inertial navigation system after the erection is completed through a transfer alignment algorithm so as to complete azimuth fine alignment; a rotation modulation step: at the in-place position of the transfer alignment step, taking the first attitude matrix as an initial attitude, rotating the sub inertial navigation system around a sky axis by 180 degrees, then rotating the sub inertial navigation system to a symmetrical position and then rotating the sub inertial navigation system by 180 degrees to return to the original position for rotation modulation, and obtaining a second attitude matrix of the sub inertial navigation system to complete horizontal attitude fine alignment; and a fusion step: fusing the azimuth result of the first attitude matrix and the horizontal attitude result of the second attitude matrix to obtain a final attitude matrix so as to complete initial alignment. According to the high-precision initial alignment method provided by the invention, the characteristics of rotation modulation alignment and transfer alignment are effectively combined, and the initial alignment precision is improved.

Description

Technical Field

[0001] The invention relates to the technical field of inertial navigation and combined navigation, and in particular to a high-precision initial alignment method. Background Art

[0002] An inertial navigation system (INS) is a navigation aid that uses computers, motion sensors (accelerometers) and rotation sensors (gyroscopes) to continuously calculate an object by inferring its position, direction and velocity (direction and speed of motion) without the need for external references. It can provide fully autonomous navigation information and has the advantages of short response time, high reliability, small size and light weight. It is widely used in military and civilian navigation fields such as aircraft and ships, and has important national defense significance and huge economic benefits.

[0003] Initial alignment provides the initial attitude for inertial navigation. Its accuracy directly affects the accuracy of subsequent inertial navigation. At present, the azimuth alignment accuracy of the inertial navigation system is affected by the gyro constant drift. The error accumulates over time and requires regular calibration and maintenance.

[0004] In the related art, two measures are often used to improve the navigation accuracy of the inertial navigation system. One is to design and manufacture inertial components with higher precision. However, due to the high level of research and development of optical gyroscopes, the room for improving the precision of inertial components is already limited. The other is to adopt system technology, such as the use of rotation modulation technology, which introduces a transfer mechanism on the basis of the traditional strapdown inertial navigation system. By controlling the transfer mechanism, the inertial measurement unit (IMU) is continuously, periodically, and regularly rotated, so that the mean value of the inertial device error in a short period is close to zero, thereby reducing the long-term accumulated error of the system and achieving the purpose of improving the system accuracy. For a micro inertial navigation system with light volume and small size, although the rotation modulation technology can obtain better horizontal attitude accuracy, it is difficult to obtain high-precision azimuth accuracy only through rotation modulation due to large random noise.

[0005] In order to achieve high-precision azimuth alignment of low-precision products, transfer alignment technology is often used. Transfer alignment technology refers to using the higher-precision main inertial navigation system to calibrate the lower-precision sub-inertial navigation system, and estimating the installation error between the main and sub-inertial navigation systems to solve the initial alignment problem of the sub-inertial navigation system under the condition of a moving base. However, transfer alignment technology usually requires the carrier to have specific maneuvers. However, under most conditions, it is impossible to simultaneously meet the large-scale maneuvers of multiple angles. Therefore, it is difficult to simultaneously meet the rapid convergence of horizontal attitude when meeting the rapid convergence of azimuth. Summary of the invention

[0006] The technical problem to be solved by the present application is that the rotation modulation technology in the related technology is difficult to obtain high-precision azimuth accuracy, and the transfer alignment technology is difficult to simultaneously meet the requirements of rapid azimuth convergence and rapid horizontal attitude convergence.

[0007] The present invention provides a high-precision initial alignment method, comprising the following steps:

[0008] Transfer alignment step: providing a main inertial navigation system and a sub-inertial navigation system, wherein the main inertial navigation system and the sub-inertial navigation system are simultaneously rotated 90° around a horizontal axis for erection, and a first attitude matrix of the sub-inertial navigation system after erection is completed is obtained through a transfer alignment algorithm to complete azimuth precise alignment;

[0009] Rotation modulation step: at the position in the transfer alignment step, the sub-inertial navigation system is rotated 180° around the celestial axis to a symmetrical position and then rotated -180° back to the original position for rotation modulation, so as to obtain a second attitude matrix of the sub-inertial navigation system, so as to complete the horizontal attitude precise alignment;

[0010] Fusion step: fusing the orientation result of the first posture matrix and the horizontal posture result of the second posture matrix to obtain a final posture matrix to complete the initial alignment.

[0011] In one embodiment, the transfer alignment algorithm comprises:

[0012] Taking the attitude matrix of the main inertial navigation system as the initial attitude, a first state equation is established, and the first state equation is expressed as:

[0013] Among them, F is the state transfer matrix, the state vector x INSSys is the parameter error state vector of the inertial navigation system, x INSSens is the accelerometer and gyro parameter error state vector, x Aid is the auxiliary state vector, w is the system state noise;

[0014] A first measurement equation is established, wherein the first measurement equation is expressed as: z=Hx+v;

[0015] Where H is the measurement matrix including the attitude matrix of the main inertial navigation system, and v is the measurement noise;

[0016] Filtering is performed based on the first state equation and the first measurement equation to correct the inertial navigation system parameter error and the device parameter error in real time, obtain the first attitude matrix, and complete the azimuth precise alignment.

[0017] In one implementation, the filtering method is Kalman filtering.

[0018] In one embodiment, the Kalman filter comprises:

[0019] When the extrapolation period is a first set integer multiple of the sampling period, the extrapolation period calculation is performed;

[0020] When the update period is a second set integer multiple of the extrapolation period, performing update period calculation;

[0021] After completing the update calculation, the estimated values ​​of the inertial navigation system parameter error and the device parameter error are corrected in real time to obtain the first attitude matrix.

[0022] In one implementation, the filtering method is nonlinear filtering.

[0023] In one embodiment, when the sub-inertial navigation system performs rotational modulation, after staying at the position in the transfer alignment step for t seconds, it uses the first posture matrix as the initial posture, rotates 180° around the celestial axis to a symmetrical position, stays for t seconds, and then rotates -180° to return to the original position.

[0024] In one implementation, obtaining the second attitude matrix of the sub-inertial navigation system includes:

[0025] Using the first posture matrix as an initial posture, establishing a second state equation, wherein the second state equation is the same as the first state equation;

[0026] A second measurement equation is established, wherein the second measurement equation is expressed as: z=Hx+v;

[0027] Where H is the measurement matrix and v is the measurement noise;

[0028] Filtering is performed based on the second state equation and the second measurement equation to correct the inertial navigation system parameter error and the device parameter error in real time, obtain the second attitude matrix, and complete the horizontal attitude precise alignment.

[0029] In one embodiment, the fusing step comprises:

[0030] Calculate the angle azm_x between the horizontal axis and the north direction based on the first posture matrix;

[0031] The final posture matrix is ​​calculated based on the angle azm_x and the second posture matrix.

[0032] In one embodiment, the angle azm_x between the horizontal axis and the north direction is calculated as follows:

[0033]

[0034] in, Represents the first posture matrix The value of the i-th row and j-th column in .

[0035] In one embodiment, the calculating of the final posture matrix based on the angle azm_x and the second posture matrix comprises:

[0036] Let the final posture matrix

[0037] Calculate the intermediate quantity q using the formula:

[0038] Among them, C ij Represents the final posture matrix The value of row i and column j in ;

[0039] Calculate the final posture matrix based on the angle azm_x Other components of to obtain the final posture matrix;

[0040] The calculation formula is:

[0041] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0042] The present application provides a high-precision initial alignment method, which uses transfer alignment to achieve high-precision azimuth alignment, converges azimuth quickly in seconds, and then uses rotation modulation self-alignment to achieve high-precision horizontal attitude alignment, and finally effectively combines the characteristics of rotation modulation alignment and transfer alignment to form the final high-precision rapid initial alignment. It effectively improves the initial alignment accuracy of the low-precision inertial navigation system, and has the advantages of fast convergence time and strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 Flow chart of a high-precision initial alignment method in one embodiment of the present invention.

[0045] Figure 2 Schematic diagram of the process of a high-precision initial alignment method in one embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] like Figure 1 and Figure 2 As shown, Figure 1 Flow chart of a high-precision initial alignment method in one embodiment of the present invention. Figure 2 Schematic diagram of the process of a high-precision initial alignment method in one embodiment of the present invention.

[0048] This embodiment provides a high-precision initial alignment method, comprising the following steps:

[0049] S1, transfer alignment step: providing a main inertial navigation system and a sub-inertial navigation system, the main inertial navigation system and the sub-inertial navigation system are simultaneously rotated 90° around a horizontal axis for erection, and a first attitude matrix of the sub-inertial navigation system after erection is completed is obtained through a transfer alignment algorithm to complete azimuth precise alignment;

[0050] S2, rotation modulation step: at the in-place position of the transfer alignment step, with the first attitude matrix as the initial attitude, the sub-inertial navigation system rotates 180° around the celestial axis to a symmetrical position and then rotates -180° back to the original position for rotation modulation, to obtain the second attitude matrix of the sub-inertial navigation system, so as to complete the horizontal attitude precise alignment;

[0051] S3, fusion step: fuse the orientation result of the first posture matrix and the horizontal posture result of the second posture matrix to obtain the final posture matrix to complete the initial alignment.

[0052] This embodiment provides a high-precision initial alignment method, which uses transfer alignment to achieve high-precision azimuth alignment, quickly converges azimuth in seconds, and then uses rotation modulation self-alignment to achieve high-precision horizontal attitude alignment. Finally, the characteristics of rotation modulation alignment and transfer alignment are effectively combined to form the final high-precision rapid initial alignment. It effectively improves the initial alignment accuracy of the low-precision inertial navigation system, and has the advantages of fast convergence time and strong practicality. It is applied to the initial alignment scheme with erection and rotation processes, and meets the requirements of rapid convergence of azimuth and rapid convergence of horizontal attitude.

[0053] Each step is described and explained in detail below.

[0054] In this embodiment, the projection of the angular velocity of the gyro output body coordinate system B of the sub-inertial navigation system relative to the geocentric inertial coordinate system I in the B system is: The accelerometer output of the sub-inertial navigation system is the specific force f in the body coordinate system B B , the main inertial navigation system outputs the speed in the navigation system and posture Navigation system N system: XYZ axes point to the northeast sky respectively, navigation system L system: XYZ axes point to the northeast ground respectively, initial body coordinate system B system: Y axis points downward, XZ is horizontal.

[0055] In one embodiment, the transfer alignment algorithm includes:

[0056] Step S11: Using the attitude matrix of the main inertial navigation system as the initial attitude, establish a first state equation, which is expressed as:

[0057] Among them, F is the state transfer matrix, the state vector x INSSys is the parameter error state vector of the inertial navigation system, x INSSens is the accelerometer and gyro parameter error state vector, x Aid is the auxiliary state vector, and w is the system state noise.

[0058] Specifically, in this embodiment, the first state equation is established according to the inertial navigation error model.

[0059] The first state equation is:

[0060]

[0061] Among them, F is the state transfer matrix, which is a 22×22-dimensional matrix; w is the system state noise, which is a 22×1-dimensional vector; for example, the state vector x is a 22-dimensional vector, which contains the 10-dimensional inertial navigation system parameter error state vector x INSSys , 6-dimensional device parameter error state vector x INSSens And the 6-dimensional auxiliary state vector x Aid , auxiliary state vector x Aid Including the installation deviation angle and lever arm error of the master inertial navigation system. Of course, in other embodiments, it can also be other dimensional vectors.

[0062] where x INSSys Specifically expressed as:

[0063]

[0064] They represent the components of the object position error angle in the X, Y, and Z directions in the navigation coordinate system respectively. are the components of the carrier velocity error in the navigation system in the X, Y, and Z directions, respectively. are the components of the carrier attitude error angle in the navigation system in the X, Y, and Z directions, and δh is the carrier height error.

[0065] x INSSens It includes three accelerometer bias errors B' and three gyro bias errors B".

[0066] x Aid It includes the installation deviation angles of the three master inertial navigation systems and the three arm errors.

[0067] F is the state transfer matrix, where F 11 is the coefficient matrix of the linearized state error equation of the 10×10-dimensional strapdown inertial navigation system. The specific expression is:

[0068]

[0069] in, is the component of displacement angular velocity in the X, Y, and Z directions in the navigation system, is the component of the earth's rotation angular velocity in the Y and Z directions under the navigation system, R M is the meridian curvature radius, R N is the radius of curvature of the y-axis, L is the latitude, h is the height, is the velocity component in the X, Y, and Z directions under the navigation system, are the values ​​of the specific forces measured by the three accelerometers in the navigation system. The above parameters are output by the gyro of the sub-inertial navigation system and the accelerometer output f B It can be obtained through inertial navigation calculation, which will not be described in detail here. The initial position of the inertial navigation system is the local position, the initial velocity is zero, and the initial attitude is set to the attitude matrix of the main inertial navigation system, that is, the initial equal

[0070] in is the attitude matrix solved by the inertial navigation system, according to the initial attitude matrix Transformed to get.

[0071] F 22 =diag([-1 / τ1 -1 / τ2 -1 / τ3 -1 / τ4 -1 / τ5 -1 / τ6]).

[0072] Among them, diag() represents the diagonal elements, τ iRepresents the first-order Markov process correlation time of three accelerometers and three gyroscopes, which is set according to the device performance.

[0073] Step S12, establishing a first measurement equation, the first measurement equation is expressed as: z=Hx+v;

[0074] Where H is the measurement matrix including the attitude matrix of the main inertial navigation system, and v is the measurement noise.

[0075] Specifically, the measurement matrix v is the measurement noise, I 3×3 is the 3x3 identity matrix, is the main inertial navigation system attitude matrix, express The cross product of It is obtained by dividing the equivalent rotation vector of the attitude matrix of the main inertial navigation system at the current moment and the previous moment by the sampling period.

[0076] Calculate intermediate variables, in, Initialized to the identity matrix and updated after each estimation.

[0077] Observable

[0078] in, is the velocity component in the X, Y, and Z directions under the navigation system, The components of velocity in the X, Y, and Z directions in the navigation system of the main inertial navigation system, are the components of the velocity in the X, Y, and Z directions of the navigation system introduced by the lever arm.

[0079] Step S13: filtering based on the first state equation and the first measurement equation to correct the inertial navigation system parameter error and the device parameter error in real time, obtain the first attitude matrix, and complete the azimuth precise alignment.

[0080] In one embodiment, the filtering method is Kalman filtering, which has a faster convergence speed.

[0081] In one embodiment, the execution method of Kalman filtering for feedback correction includes:

[0082] A. When the extrapolation period is a first set integer multiple of the sampling period, the extrapolation period calculation is performed.

[0083] Specifically, it is determined whether the extrapolation period has arrived (the extrapolation period is generally an integer multiple of the sampling period, such as 2 sampling periods for one extrapolation period). If it has arrived, the extrapolation period calculation is performed as follows:

[0084]

[0085] Among them, the subscript n represents the current sampling time, and the subscript n-1 represents the previous sampling time; represents the state vector x at time n; Φ n,n-1 Represents the discretized value of the state transfer matrix F from time n-1 to time n; The state vector correction value obtained by updating the state vector at time n-1; Q n-1 is the variance matrix of the system noise w at time n-1; the superscript T indicates the transpose of the corresponding matrix; Represents the updated value of the state vector covariance matrix at time n-1; Represents the covariance matrix of the state vector at time n.

[0086] B. When the update period is a second set integer multiple of the extrapolation period, the update period calculation is performed.

[0087] Specifically, after the above extrapolation cycle calculation is completed, it is determined whether the update cycle has arrived (the update cycle is generally an integer multiple of the extrapolation cycle, such as 10 extrapolation cycles for one update cycle). If it has arrived, the following update cycle calculation is performed:

[0088]

[0089] Among them, R n represents the measurement noise matrix at time n, which is set according to the measurement noise level; H n represents the measurement matrix H at time n; K n Represents the filter gain at time n; represents the observed quantity z at time n Obs ; represents the updated value of the state vector x obtained at time n; (+E) is a superscript, indicating that after the state update in the basic equation of the discrete Kalman filter, the specified parameter is updated at the specified time (here t n The value of the specified parameter at the specified time (at the specified moment); (+C) is a superscript, indicating the value of the specified parameter at the specified time after the control formula in the basic equation of the discrete Kalman filter; (-) is a superscript, indicating the value of the specified parameter at the specified time before the state update formula and the control formula take effect.

[0090] C. After completing the update calculation, the estimated values ​​of the inertial navigation system parameter error and the device parameter error are corrected in real time to obtain the first attitude matrix.

[0091] The estimated values ​​of each error state are obtained through Kalman filtering, and the navigation parameters are corrected using the estimated values. The corrected navigation parameters are used as the initial values ​​for the next navigation to continue navigation calculation until the process is completed. The specific process is:

[0092] First calculate the navigation parameter error:

[0093]

[0094] Among them, X n (i) is the i-th element of the state vector x; δθ N is the position error, and its three components are δh is the carrier height error; is the velocity error, and its three components are φ L is the attitude error, and its three components are respectively Obtained through posture matrix transformation.

[0095] Then make navigation parameter corrections:

[0096]

[0097] in, h=、v N , is the navigation parameter.

[0098] Then calculate the estimated value of the installation angle:

[0099]

[0100] Then proceed with the installation of the main inertial navigation system. Correction:

[0101]

[0102] Finally, the device parameters and lever arm parameters are corrected in an open loop, namely:

[0103]

[0104] Get the first posture matrix Recorded as

[0105] Through the above scheme, the optimal estimation is achieved, which facilitates the completion of precise azimuth alignment.

[0106] In one embodiment, the filtering method is nonlinear filtering.

[0107] In one embodiment, when the sub-inertial navigation system performs rotational modulation, after staying at the position of the transfer alignment step for t seconds, it uses the first attitude matrix as the initial attitude, rotates 180° around the celestial axis at a speed of w to a symmetrical position, stays for t seconds, and then rotates -180° at a speed of w to return to the original position.

[0108] Specifically, t represents the time spent at each position, which is set according to the total time of the initial alignment. For example, if the total time required for the initial alignment is 40 seconds, then after deducting the time for erecting 90 degrees in step S1 (if the erection angular velocity is 20 degrees / second, the erection time is about 5 seconds), the time spent at each position is about 8 seconds, so t can be set to 8 seconds. w represents the speed of rotation, which is set according to the capacity of the indexing mechanism in the inertial navigation system, and is generally set to 20 degrees / second or 30 degrees / second.

[0109] In one embodiment, obtaining a second attitude matrix of the sub-inertial navigation system includes:

[0110] The first posture matrix is ​​used as the initial posture to establish the second state equation, which is the same as the first state equation.

[0111] A second measurement equation is established, and the second measurement equation is expressed as: z=Hx+v;

[0112] Where H is the measurement matrix and v is the measurement noise.

[0113] Specifically, the measurement matrix H = [0 3×3 I 3×3 0 3×3 0 3×7 0 3×3 0 3×3 ],

[0114] Observable

[0115] The meaning of each parameter is consistent with step S12.

[0116] Filtering is performed based on the second state equation and the second measurement equation to correct the inertial navigation system parameter error and device parameter error in real time to obtain the second attitude matrix The horizontal posture alignment is completed. The specific execution method is consistent with step S13, and the second posture matrix obtained Recorded as

[0117] In one embodiment, S3, the fusion step includes:

[0118] Step S31, calculating the angle azm_x between the horizontal axis and the north direction based on the first posture matrix.

[0119] In one embodiment, the angle azm_x between the horizontal axis and the north direction is calculated as follows:

[0120]

[0121] Among them, atan2 is the inverse tangent function, Represents the first posture matrix The value of the i-th row and j-th column in is normalized to the range of 0 to 360 degrees.

[0122] Step S32: Calculate the final posture matrix based on the angle azm_x and the second posture matrix.

[0123] In one embodiment, calculating the final posture matrix based on the angle azm_x and the second posture matrix includes:

[0124] Let the final posture matrix

[0125] Calculate the intermediate quantity q using the formula:

[0126] Among them, C ij Represents the final posture matrix The value of row i and column j in ;

[0127] Calculate the final posture matrix based on the angle azm_x Other components of to obtain the final posture matrix;

[0128] The calculation formula is:

[0129] The final result is the attitude of the starting and ending position. After rotation modulation, it returns to the original position, so the orientation does not change. The orientation value of step S1 is used directly. If it cannot return to the original position according to the process setting or angle judgment, the output of the inertial navigation system (gyro output) is used in the process of returning to the original position. and the accelerometer output f B ) to perform navigation calculations, and finally fuse the navigation calculation attitude with the rotation modulation results.

[0130] In the description of the present application, it should be noted that the terms "upper", "lower", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances.

[0131] It should be noted that, in this application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0132] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0133] The above is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest range consistent with the principles and novel features applied for herein.

Claims

1. A high-precision initial alignment method, characterized in that: The following steps are involved: Transfer alignment step: providing a main inertial navigation system and a sub-inertial navigation system, wherein the main inertial navigation system and the sub-inertial navigation system are simultaneously rotated 90° around a horizontal axis for erection, and a first attitude matrix of the sub-inertial navigation system after erection is completed is obtained through a transfer alignment algorithm to complete azimuth precise alignment; Rotation modulation step: at the position in the transfer alignment step, the sub-inertial navigation system is rotated 180° around the celestial axis to a symmetrical position and then rotated -180° back to the original position for rotation modulation, so as to obtain a second attitude matrix of the sub-inertial navigation system, so as to complete the horizontal attitude precise alignment; Fusion step: fusing the orientation result of the first posture matrix and the horizontal posture result of the second posture matrix to obtain a final posture matrix to complete the initial alignment.

2. The high-precision initial alignment method according to claim 1, characterized in that: The transfer alignment algorithm includes: Taking the attitude matrix of the main inertial navigation system as the initial attitude, a first state equation is established, and the first state equation is expressed as: Among them, F is the state transfer matrix, the state vector x INSSys is the parameter error state vector of the inertial navigation system, x INSSens is the accelerometer and gyro parameter error state vector, x Aid is the auxiliary state vector, w is the system state noise; A first measurement equation is established, wherein the first measurement equation is expressed as: z=Hx+v; Where H is the measurement matrix including the attitude matrix of the main inertial navigation system, and v is the measurement noise; Filtering is performed based on the first state equation and the first measurement equation to correct the inertial navigation system parameter error and the device parameter error in real time, obtain the first attitude matrix, and complete the azimuth precise alignment.

3. The high-precision initial alignment method according to claim 2, characterized in that: The filtering method is Kalman filtering.

4. The high-precision initial alignment method according to claim 3, characterized in that: The Kalman filter comprises: When the extrapolation period is a first set integer multiple of the sampling period, the extrapolation period calculation is performed; When the update period is a second set integer multiple of the extrapolation period, performing update period calculation; After completing the update calculation, the estimated values ​​of the inertial navigation system parameter error and the device parameter error are corrected in real time to obtain the first attitude matrix.

5. The high-precision initial alignment method according to claim 2, characterized in that: The filtering method is nonlinear filtering.

6. The high-precision initial alignment method according to claim 1, characterized in that: When the sub-inertial navigation system performs rotational modulation, after staying at the position in the transfer alignment step for t seconds, the first posture matrix is ​​used as the initial posture, and it rotates 180° around the celestial axis to a symmetrical position, stays for t seconds, and then rotates -180° to return to the original position.

7. The high-precision initial alignment method according to claim 2, characterized in that: The obtaining of the second attitude matrix of the sub-inertial navigation system comprises: Using the first posture matrix as an initial posture, establishing a second state equation, wherein the second state equation is the same as the first state equation; A second measurement equation is established, wherein the second measurement equation is expressed as: z=Hx+v; Where H is the measurement matrix, v is the measurement noise; Filtering is performed based on the second state equation and the second measurement equation to correct the inertial navigation system parameter error and the device parameter error in real time, obtain the second attitude matrix, and complete the horizontal attitude precise alignment.

8. The high-precision initial alignment method according to claim 1, characterized in that: The fusion step comprises: Calculate the angle azm_x between the horizontal axis and the north direction based on the first posture matrix; The final posture matrix is ​​calculated based on the angle azm_x and the second posture matrix.

9. The high-precision initial alignment method according to claim 8, characterized in that: The angle azm_x between the horizontal axis and the north direction is calculated as: in, Represents the first posture matrix The value of the i-th row and j-th column in .

10. The high-precision initial alignment method according to claim 9, characterized in that: The calculation of the final posture matrix based on the angle azm_x and the second posture matrix comprises: Let the final posture matrix Calculate the intermediate quantity q using the formula: Among them, C ij Represents the final posture matrix The value of row i and column j in ; Calculate the final posture matrix based on the angle azm_x Other components of to obtain the final posture matrix; The calculation formula is:

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