A high-precision initial alignment method

Abstract

The application 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, rotating 90 degrees around a horizontal axis to be erected, obtaining a first attitude matrix of the sub-inertial navigation system after the erection is completed through a transfer alignment algorithm, and completing azimuth fine alignment; a rotation modulation step: rotating the sub-inertial navigation system 180 degrees around the skyward axis to a symmetrical position and then rotating-180 degrees back to the original position for rotation modulation at the in-place position of the transfer alignment step, taking the first attitude matrix as an initial attitude, and obtaining a second attitude matrix of the sub-inertial navigation system to complete horizontal attitude fine alignment; and a fusion step: fusing an azimuth result of the first attitude matrix and a horizontal attitude result of the second attitude matrix to obtain a final attitude matrix to complete initial alignment. The application provides a high-precision initial alignment method which effectively combines the characteristics of rotation modulation alignment and transfer alignment and improves the initial alignment precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of inertial navigation and integrated navigation, and in particular to a high-precision initial alignment method. BACKGROUND

[0002] An inertial navigation system (INS) is a navigation aid device using a computer, a motion sensor (accelerometer) and a rotation sensor (gyroscope) to continuously calculate the position, direction and speed (direction and speed of motion) of an object by reckoning motion without the need for external references, and can provide completely autonomous navigation information, has the advantages of short reaction time, high reliability, small size and light weight, and is widely used in military and civilian navigation fields such as aircraft and ships, and has important national defense significance and great economic benefits.

[0003] Initial alignment provides initial attitude for inertial navigation, and its precision directly affects the subsequent inertial navigation precision. The azimuth alignment precision of the current inertial navigation system is affected by the constant drift of the gyroscope, and the error accumulates over time, so it needs to be calibrated and maintained regularly.

[0004] In related technologies, two measures are often used to improve the navigation precision of the inertial navigation system. One is to design and manufacture higher-precision inertial elements, but the precision of the inertial elements has limited space for improvement due to the high level of development of optical gyroscopes. The other is to use system technology, such as using rotation modulation technology, introducing a rotation mechanism on the basis of the traditional strapdown inertial navigation system, and making the inertial measurement unit (IMU) rotate continuously, periodically and regularly by controlling the rotation mechanism, so that the average 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 precision. For a micro inertial navigation system with small size and light weight, although the rotation modulation technology can obtain good horizontal attitude precision, it is difficult to obtain high-precision azimuth precision due to the large random noise.

[0005] To achieve high-precision azimuth alignment of low-precision products, transfer alignment technology is often used. Transfer alignment technology refers to using a high-precision master inertial navigation system to calibrate a low-precision slave inertial navigation system, and estimating the installation error between the master and slave inertial navigation systems to solve the initial alignment problem of the slave inertial navigation system under a moving base. However, transfer alignment technology usually requires a specific maneuver of the carrier, but it is difficult to meet the large-scale maneuver of multiple angles at the same time under most conditions, so it is difficult to meet the rapid convergence of both azimuth and horizontal attitude at the same time. SUMMARY

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

[0007] The embodiment of the present application provides a high-precision initial alignment method, which comprises the following steps:

[0008] The transfer alignment step: a main inertial navigation system and a sub-inertial navigation system are provided, the main inertial navigation system and the sub-inertial navigation system are simultaneously rotated by 90° around a horizontal axis to be erected, a first attitude matrix of the sub-inertial navigation system after the erection is completed is obtained through a transfer alignment algorithm, so that the azimuth fine alignment is completed;

[0009] The rotation modulation step: in the in-place position of the transfer alignment step, the sub-inertial navigation system is rotated by 180° around the vertical axis to reach the symmetric position and then rotated by-180° to return to the original position for rotation modulation, a second attitude matrix of the sub-inertial navigation system is obtained, so that the horizontal attitude fine alignment is completed;

[0010] The fusion step: the azimuth result of the first attitude matrix and the horizontal attitude result of the second attitude matrix are fused to obtain a final attitude matrix, so that the initial alignment is completed.

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

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

[0013] Wherein, is a state transition matrix, and a state vector , is an inertial navigation system parameter error state vector, is an accelerometer and gyroscope parameter error state vector, is an auxiliary state vector, is system state noise;

[0014] A first measurement equation is established, and the first measurement equation is expressed as: ;

[0015] Wherein, H is a measurement matrix comprising the attitude matrix of the main inertial navigation system, and v is measurement noise;

[0016] Filtering is performed based on the first state equation and the first measurement equation, so that the inertial navigation system parameter error and the device parameter error are corrected in real time, the first attitude matrix is obtained, and the azimuth fine alignment is completed.

[0017] In an embodiment, the filtering mode is Kalman filtering.

[0018] In an embodiment, the Kalman filtering 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, the update period calculation is performed;

[0021] After the update calculation is completed, the estimated values of the inertial navigation system parameter error and the device parameter error are corrected in real time, and the first attitude matrix is obtained.

[0022] In an embodiment, the filtering manner is a nonlinear filtering.

[0023] In an embodiment, when the sub-inertial navigation system is subjected to rotational modulation, after the in-place position of the transfer alignment step is stayed for t seconds, the first attitude matrix is taken as an initial attitude, the in-symmetrical position is reached after rotating 180° around the zenith axis, and the original position is returned after rotating -180° after staying for t seconds.

[0024] In an embodiment, the obtaining of the second attitude matrix of the sub-inertial navigation system comprises:

[0025] The second state equation is established with the first attitude matrix as an initial attitude, and the second state equation is the same as the first state equation;

[0026] The second measurement equation is established, and the second measurement equation is expressed as: ;

[0027] Wherein, H is a measurement matrix, and v is a measurement noise.

[0028] Based on the second state equation and the second measurement equation, filtering is performed to correct the inertial navigation system parameter error and the device parameter error in real time, and the second attitude matrix is obtained, and the horizontal attitude fine alignment is completed.

[0029] In an embodiment, the fusion step comprises:

[0030] The included angle between the horizontal axis and the north direction is calculated based on the first attitude matrix azm_x ;

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

[0032] In an embodiment, the included angle between the horizontal axis and the north direction azm_x is calculated according to the following formula:

[0033] ;

[0034] Wherein, denotes a first attitude matrix the i-th row of the final attitude matrix i the i-th column of the final attitude matrix j .

[0035] In one embodiment, the final attitude matrix is calculated based on the included angle azm_x and the second attitude matrix, comprising:

[0036] Let the final attitude matrix be = the second attitude matrix .

[0037] An intermediate quantity is calculated, and the calculation formula is: .

[0038] wherein, denotes the value of the i-th row of the final attitude matrix the i-th column of the final attitude matrix i . j

[0039] The other components of the final attitude matrix azm_x are calculated based on the included angle to obtain the final attitude matrix.

[0040] The calculation formula is: .

[0041] The technical scheme provided by the embodiments of the present application has the following beneficial effects:

[0042] The present application provides a high-precision initial alignment method, which realizes high-precision azimuth alignment by using transfer alignment, converges azimuth in seconds, realizes high-precision horizontal attitude alignment by using rotation modulation self-alignment, and finally effectively combines the characteristics of rotation modulation alignment and transfer alignment to form the final high-precision rapid initial alignment. The initial alignment precision of a low-precision inertial navigation system is effectively improved, and the method has the advantages of fast convergence time and strong practicability. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0044] Figure 1 The flowchart of the high-precision initial alignment method in an embodiment of the present application.

[0045] Figure 2 The process schematic diagram of the high-precision initial alignment method in an embodiment of the present application. ​DETAILED DESCRIPTION

[0046] In order to make the personnel in the technical field better understand the scheme of the present application, the technical scheme in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0047] As shown in Figure 1 and Figure 2 , wherein, Figure 1 is a flow chart of the high-precision initial alignment method in an embodiment of the present application. Figure 2 is a process schematic diagram of the high-precision initial alignment method in an embodiment of the present application.

[0048] The embodiment provides a high-precision initial alignment method, which comprises the following steps:

[0049] S1, transfer alignment step: a main inertial navigation system and a sub-inertial navigation system are provided, the main inertial navigation system and the sub-inertial navigation system are simultaneously rotated by 90° around a certain horizontal axis to be erected, a first attitude matrix of the sub-inertial navigation system after the erection is completed is obtained through a transfer alignment algorithm, so as to complete the azimuth fine alignment;

[0050] S2, rotation modulation step: in the in-place position of the transfer alignment step, the first attitude matrix is taken as an initial attitude, the sub-inertial navigation system is rotated by 180° around the vertical axis to a symmetrical position and then rotated by-180° to return to the original position for rotation modulation, a second attitude matrix of the sub-inertial navigation system is obtained, so as to complete the horizontal attitude fine alignment;

[0051] S3, fusion step: the azimuth result of the first attitude matrix and the horizontal attitude result of the second attitude matrix are fused to obtain a final attitude matrix, so as to complete the initial alignment.

[0052] The embodiment provides a high-precision initial alignment method, which realizes high-precision azimuth alignment by using transfer alignment, converges the azimuth in seconds, realizes high-precision horizontal attitude alignment by using rotation modulation self-alignment, and finally effectively combines the characteristics of the rotation modulation alignment and the transfer alignment to form the final high-precision rapid initial alignment. The initial alignment precision of the low-precision inertial navigation system is effectively improved, and the method has the advantages of fast convergence time and strong practicability, and is applied to the initial alignment scheme with the erection and rotation process, and meets the azimuth rapid convergence and the horizontal attitude rapid convergence.

[0053] The steps will be described and explained in detail below.

[0054] In the embodiment, the projection of the angular velocity of the body coordinate system B of the gyroscope output of the sub-inertial navigation system relative to the earth-centered inertial coordinate system I in the body coordinate system B is , the specific force of the accelerometer output of the sub-inertial navigation system in the body coordinate system B is , the velocity of the main inertial navigation system output in the navigation system is , and the attitude is , the navigation system N: the XYZ axes respectively point to the northeast sky, the navigation system L: the XYZ axes respectively point to the northeast ground, the initial body coordinate system B: the Y axis points downward, and the XZ plane is horizontal.

[0055] In an embodiment, the transfer alignment algorithm comprises:

[0056] Step S11, taking the attitude matrix of the main inertial navigation system as an initial attitude, a first state equation is established, and the first state equation is expressed as:

[0057] wherein, is a state transition matrix, a state vector , is an inertial navigation system parameter error state vector, is an accelerometer and gyroscope parameter error state vector, is an auxiliary state vector, is a system state noise.

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

[0059] The first state equation is:

[0060] .

[0061] wherein, is a state transition matrix, and is a matrix of dimension; is a system state noise, and is a vector of dimension; for example, the state vector is a 22-dimensional vector, including a 10-dimensional inertial navigation system parameter error state vector , a 6-dimensional device parameter error state vector , and a 6-dimensional auxiliary state vector The auxiliary state vector includes the installation deviation angle and the arm error of the main and sub-inertial navigation systems. Of course, in other embodiments, other dimensional vectors can also be used.

[0062] wherein is specifically expressed as:

[0063] ;​

[0064] , , respectively represent the components of the navigation coordinate system body position error angle in X, Y, Z axis directions, , , respectively represent the components of the navigation coordinate system body velocity error in X, Y, Z axis directions, , , respectively represent the components of the navigation coordinate system body attitude error angle in X, Y, Z axis directions, is the body height error.

[0065] successively contain 3 accelerometer bias errors and 3 gyroscope bias errors .

[0066] successively contain 3 installation deviation angles of the main sub-inertial navigation system and 3 rod arm errors.

[0067] is the state transition matrix, where is the coefficient matrix of the linearized expression of the strapdown inertial navigation system state error equation with dimension of , and the specific expression is:

[0068]

[0069] wherein, , , is the component of the navigation coordinate system body angular velocity in X, Y, Z directions, , is the component of the earth rotation angular velocity in Y, Z directions, is the meridian curvature radius, is the prime vertical curvature radius, is the latitude, is the height, , , is the component of the navigation coordinate system body velocity in X, Y, Z directions, , , respectively represent the values of the specific forces measured by the three accelerometers in the navigation coordinate system. The above parameters are output by the sub-inertial navigation system gyroscope and the accelerometer The initial position of the inertial navigation system is the local position, the initial speed is zero, and the initial attitude is set as the attitude matrix of the master inertial navigation system, i.e., the initial is equal to .

[0070] wherein is the attitude matrix solved by the inertial navigation system, and is obtained according to the initial attitude matrix .

[0071] .

[0072] wherein, denotes diagonal elements, denotes a first-order Markov process correlation time of the three accelerometers and the three gyroscopes, and is set according to the device performance.

[0073] Step S12, establishing a first measurement equation, the first measurement equation is expressed as: .

[0074] wherein, H is a measurement matrix including the attitude matrix of the master inertial navigation system, and v is measurement noise.

[0075] Specifically, the measurement matrix , v is measurement noise, is a 3x3 unit matrix, is the attitude matrix of the master inertial navigation system, denotes the cross product of , and is obtained by dividing the equivalent rotation vector of the attitude matrix of the master inertial navigation system at the current time and the last time by the sampling period.

[0076] An intermediate variable is calculated, wherein, is initialized as a unit matrix and is updated after each estimation is completed.

[0077] The observation quantity .

[0078] wherein, , , are components of the velocity in the X, Y, and Z directions in the navigation system, , , are components of the velocity in the X, Y, and Z directions in the navigation system of the master inertial navigation system, , , are components of the velocity in the X, Y, and Z directions in the navigation system introduced by the boom.​

[0079] Step S13: 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 fine 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 the Kalman filter 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, determine 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 so, perform the following extrapolation period calculation:

[0084] ;

[0085] Among them, the subscript n Indicates the current sampling time, the subscript n-1 Indicates the last sampling moment; Represents the state vector at time n ; express n-1 Time has come n The state transition matrix at time The discretized value; express n-1 The state vector update value at the moment is the state vector correction value; for n-1 Time system noise The variance matrix of ; the superscript T indicates the transpose of the corresponding matrix; express n-1 Updated value of the state vector covariance matrix at the moment; express n The covariance matrix of the state vector at time t.

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

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

[0088] ;

[0089] in, denotes n the measurement noise matrix, which is set according to the measurement noise level; denotes n the measurement matrix at time ; denotes n the filter gain at time ; n denotes the observation at time ; n denotes the state vector obtained at time ; is a superscript, indicating that the designated parameter has a value at the designated time (here, time ) after the state update in the basic equation of the discrete Kalman filter; is a superscript, indicating that the designated parameter has a value at the designated time after the control equation in the basic equation of the discrete Kalman filter; is a superscript, indicating that the designated parameter has a value at the designated time before the state update equation and the control equation take effect.

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

[0091] After Kalman filtering, the estimated values of each error state are obtained, and the navigation parameters are corrected using the estimated values. The corrected navigation parameters are used as the initial values for the next navigation calculation, and the navigation calculation continues until the process ends. The specific process is as follows:

[0092] First, calculate the navigation parameter errors:

[0093] .

[0094] wherein, X n ( i ) is the th element of the state vector i ; is the position error, whose three components are , , ; is the carrier altitude error; is the velocity error, whose three components are , , ; is the attitude error, whose three components are obtained by converting through the attitude matrix , , .

[0095] Then, the navigation parameter is corrected:

[0096] .

[0097] wherein, , , , is the navigation parameter.

[0098] Then, the installation angle estimation value is calculated again:

[0099] .

[0100] Then, the installation angle of the main and sub inertial navigation system is corrected again:

[0101] . Finally, the device parameters and the lever arm parameters are open-loop corrected, i.e.:

[0102]

[0103] . The first attitude matrix is obtained

[0104] denoted as . .

[0105] Through the above scheme, the optimal estimation is realized, and the azimuth precision alignment is facilitated.

[0106] In an embodiment, the filtering manner is a nonlinear filtering.

[0107] In an embodiment, when the sub inertial navigation system is subjected to the rotation modulation, after staying at the to-position for t seconds in the transferring alignment step, the first attitude matrix is taken as the initial attitude, the to-position is rotated by 180° around the skyward axis at a speed of w , and then stays at the symmetric position for t seconds, and then is rotated by -180° around the skyward axis at a speed of w , and then returns to the original position.

[0108] Specifically, t represents the time of staying at each position, and is set according to the total time of the initial alignment, for example, if the total time of the initial alignment is required to be 40 seconds, after deducting the time of erecting the 90-degree angle in the S1 step (if the erecting angle speed is 20 degrees per second, then the erecting time is about 5 seconds), the staying time at each position is about 8 seconds, and then t can be set to 8 seconds. w represents the speed of rotation, which is set according to the capability of the rotation mechanism in the inertial navigation system, and is generally set to 20 degrees per second or 30 degrees per second.

[0109] In an embodiment, obtaining the second attitude matrix of the sub inertial navigation system comprises:

[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] The second measurement equation is established and expressed as: ;

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

[0113] Specifically, the measurement matrix ,

[0114] Observation .

[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 , complete the horizontal posture alignment. The specific execution method is consistent with step S13, and the second posture matrix obtained is Recorded as .

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

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

[0119] In one embodiment, the angle between the horizontal axis and the north direction is azm_x The calculation formula is:

[0120] ;

[0121] in, atan2 is the inverse tangent function, Represents the first posture matrix Middle i Rank j The values ​​in the column are normalized to the range of 0 to 360 degrees.

[0122] Step S32: Based on the angle azm_x Calculate the final pose matrix using the second pose matrix.

[0123] In one embodiment, based on the angle azm_x Calculating the final pose matrix from the second pose matrix includes:

[0124] Let the final pose matrix = Second posture matrix ;

[0125] Calculate the intermediate quantity The calculation formula is: ;

[0126] Wherein, represents the value of the final attitude matrix in the first i row and the first j column;

[0127] Based on the included angle azm_x azm_x Calculate the other components of the final attitude matrix To obtain the final attitude matrix;

[0128] The calculation formula is: .

[0129] The final attitude is given at the vertical end position, and after rotation modulation, it returns to the original position, so the orientation does not change. The orientation value of step S1 is directly used. If the original position cannot be returned according to the flow setting or angle judgment, the output of the inertial navigation system (gyro output and accelerometer output ) can be used for navigation calculation during the process of returning to the original position. Finally, the navigation calculation attitude and the rotation modulation result are fused.

[0130] In the description of the present application, it should be noted that the orientation or position relationship indicated by the terms "upper", "lower" and the like is based on the orientation or position relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, and does not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication between the two elements inside. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0131] It should be noted that, in the present application, the relational terms such as "first" and "second", and the like, are used solely to distinguish one from another entity or action, without necessarily requiring or implying any actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[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; "and / or" in the text only means a description of the relationship between associated objects, which means that there can be three relationships, for example, A and / or B, which can mean that A exists alone, A and B exist together, and B exists alone, and in addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0133] The above is only a specific embodiment of the present application, which enables those skilled in the art to 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 these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features applied 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, rotating the main inertial navigation system and the sub-inertial navigation system 90 degrees around a horizontal axis for erection, and obtaining a first attitude matrix of the sub-inertial navigation system after erection through a transfer alignment algorithm to complete azimuth fine alignment; Rotation modulation step: At the position in the transfer alignment step, using the first attitude matrix as the initial attitude, 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 to obtain a second attitude matrix of the sub-inertial navigation system, thereby completing horizontal attitude fine 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; Wherein, the transfer alignment algorithm includes: The attitude matrix of the main inertial navigation system is used as the initial attitude to establish a first state equation, which is expressed as: ; in, is the state transfer matrix, the state vector , is the parameter error state vector of the inertial navigation system, is the accelerometer and gyroscope parameter error state vector, is the auxiliary state vector, is the system state noise; A first measurement equation is established, which is expressed as: ; Where H is the measurement matrix including the attitude matrix of the main inertial navigation system, and v is the measurement noise; Performing filtering based on the first state equation and the first measurement equation to correct inertial navigation system parameter errors and device parameter errors in real time, obtaining the first attitude matrix, and completing azimuth fine alignment; Wherein, obtaining the second attitude matrix of the sub-inertial navigation system includes: 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, which is expressed as: ; Where H is the measurement matrix , is a 3×3 identity matrix, and 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 horizontal attitude fine alignment.

2. The high-precision initial alignment method according to claim 1, wherein: The filtering method is Kalman filtering.

3. The high-precision initial alignment method according to claim 2, wherein: The Kalman filter includes: 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.

4. The high-precision initial alignment method according to claim 1, wherein: The filtering method is nonlinear filtering.

5. The high-precision initial alignment method according to claim 1, wherein: When the sub-inertial navigation system performs rotational modulation, after staying at the in-place 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.

6. The high-precision initial alignment method according to claim 1, wherein: The fusion step comprises: Calculate the angle between the horizontal axis and the north direction based on the first posture matrix azm_x ; Based on the angle azm_x Calculate the final pose matrix using the second pose matrix.

7. The high-precision initial alignment method according to claim 6, wherein: The angle between the horizontal axis and the north azm_ x The calculation formula is: ； in, Represents the first posture matrix Middle i Rank j The value of the column.

8. The high-precision initial alignment method according to claim 7, wherein: Based on the angle azm_x Calculating the final pose matrix from the second pose matrix includes: Let the final pose matrix = Second posture matrix ; Calculate intermediate quantities , the calculation formula is: ; in, Represents the final pose matrix Middle i Rank j The value of the column; Based on the angle azm_x Calculate the final pose matrix Other components of to obtain the final posture matrix; The calculation formula is: .

Images