High-precision transfer alignment method for active isolation optical fiber platform

Abstract

The application relates to a high-precision transfer alignment method of an active isolation optical fiber platform and belongs to the technical field of inertial navigation. The application is based on an optical fiber platform system with a multi-axis rotating mechanism, the system can control the rotation of a platform body around a celestial axis to improve the observability of the system, meanwhile, the optical fiber platform can isolate the angular motion of a carrier in a space stable mode, and can keep stable relative to inertial space, so that the influence of external disturbance on the use precision of instruments can be eliminated or reduced. The application uses the speed and position information provided by high-precision master inertial navigation as a reference, adopts a speed+position matching mode, constructs a high-order transfer alignment Kalman filter model, realizes high-precision estimation of the attitude misalignment angle of the platform body of the optical fiber platform, estimates and compensates the zero offset error of the inertial instrument, and fully utilizes the stability of the instrument to improve the alignment performance. The application solves the problems of high requirement and low precision of the existing optical fiber platform inertial navigation in dynamic base transfer alignment.

Description

Technical Field

[0001] This invention relates to a high-precision transmission alignment method for an active isolated fiber optic platform, belonging to the field of inertial navigation technology. Background Technology

[0002] The fiber optic gyroscope inertial platform system is a novel platform-type inertial system. It is equipped with three high-precision fiber optic gyroscopes, enabling direct measurement of the carrier's angular motion. Additionally, it features three rotation axes, allowing the platform components to rotate around these axes, providing "three-self" functionality. During operation, it can control the platform's rotation according to a predetermined rotation control strategy and directly perform navigation calculations using the outputs of the accelerometers and gyroscopes.

[0003] For the alignment transfer of inertial navigation systems (INS) on a moving base, environmental factors such as carrier motion and low-frequency disturbances during navigation, along with limitations imposed by carrier stealth, maneuverability, and deformation, reduce the system's observability. Under these external constraints, using attitude matching information for alignment transfer cannot meet operational requirements. Traditional platform INS systems still rely on optical aiming schemes for alignment transfer, which necessitates the installation of complex optical paths on the ship and periodic calibration, posing significant challenges to user operation and use. Summary of the Invention

[0004] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a high-precision transmission alignment method for an active isolation fiber optic platform. This method improves the operability and alignment accuracy of the user even when the carrier is affected by environmental factors such as low-frequency disturbances from ocean waves, and is also limited by factors such as the carrier's concealment, mobility, and deformation.

[0005] The technical solution of this invention is: a high-precision transmission alignment method for an active isolation fiber optic platform, comprising:

[0006] S1. Power on and heat up the inertial system of the fiber optic platform. After the temperature stabilizes and meets the working conditions, initialize the parameters. After the fiber optic platform frame is locked to zero, enter the transfer alignment process.

[0007] S2. Based on the gyroscope output signal of the fiber optic platform inertial system, calculate the angular velocity information sensed by the fiber optic platform body, and apply corresponding control to the fiber optic platform rotation mechanism to keep the fiber optic platform body stable relative to the inertial space.

[0008] S3, apply control to the optical fiber platform rotation mechanism to make the optical fiber platform body rotate and stay continuously along the predetermined rotation path;

[0009] S4, collecting the inertial measurement data of the fiber platform, the synchronization signal, the speed and position signal of the high-precision main inertial navigation system in real time, and aligning the fiber platform data with the main inertial navigation data according to the synchronization signal;

[0010] S5, performing coarse alignment by using the inertial measurement data of the fiber platform to obtain an initial attitude matrix of the fiber platform body relative to a navigation coordinate system;

[0011] S6, performing fine alignment by using the coarse alignment result and the inertial measurement data of the fiber platform to perform navigation solution, and updating the state matrix of the Kalman filter in real time;

[0012] S7, judging whether the filtering time is reached; if yes, calculating the observation and observation matrix of the Kalman filter by using the main inertial navigation data and the navigation solution result received at the current time, and updating the Kalman filter equation to calculate the state estimation value;

[0013] S8, judging whether the alignment end time is reached; if no, performing feedback correction on the system by using the estimated speed and position error of the Kalman filter; if yes, ending the alignment, compensating and correcting the navigation result of the fiber platform body by using the estimated attitude misalignment angle of the Kalman filter, and obtaining the transfer alignment result of the fiber platform inertial system.

[0014] Further, the open-loop transfer function of the fiber platform rotation mechanism subjected to the corresponding control is wherein J is the platform frame shaft rotational inertia, G FOG (s) is the fiber gyroscope transfer function, G c (s) is the loop correction network, K p is the power stage amplification coefficient, G m (s) is the shaft end torque motor transfer function.

[0015] Further, the predetermined rotation path comprises: rotating the fiber platform 180 degrees in the positive direction around the outer ring frame shaft from the zero position, then staying for a period of time, then rotating 180 degrees in the negative direction around the outer ring frame shaft, then staying for a period of time, and repeating the process until the alignment is completed, wherein the rotation time plus the staying time is equal to the total alignment time.

[0016] Further, the alignment comprises: the fiber platform collects the periodic square wave signal output by the main inertial navigation system, and defines the first falling edge of the synchronization signal received by the fiber platform as the starting time when the transfer alignment process starts, and then aligns the time stamps of the inertial measurement data and the main inertial navigation speed and position information.

[0017] Further, the initial attitude matrix of the fiber platform body relative to the navigation coordinate system is obtained by:

[0018] A relatively accurate initial attitude information is obtained by using a multi-vector attitude determination analytical coarse alignment method based on external auxiliary information. The solution method is as follows:

[0019] The values ​​of the velocity vectors α and β of the computing station system and the navigation system:

[0020]

[0021] Where V and ΔV represent velocity and velocity increment, respectively, T represents the sampling period, i represents the sampling time, the superscript g represents the projection in the navigation frame, and k is the number of samples. For t i The transformation matrix from the time-stage system to the solidification stage system, where Δθ is the angular increment. For t i The transformation matrix from the time-based navigation frame to the solidified navigation frame, V g For the navigation system velocity, t i Let I be the time interval, and let I be the identity matrix. G is the projection of the rotational angular velocity of the navigation frame relative to the inertial frame onto the navigation frame. g The projection of gravitational acceleration onto the navigation system. The projection of the Earth's rotational angular velocity onto the navigation system;

[0022] Find α and β at multiple times, and then use the relation... The least squares method was used to fit the data.

[0023] The initial attitude matrix of the fiber optic platform is:

[0024]

[0025] In the formula, The attitude transfer matrix from the solidification stage to the solidification stage can be obtained using gyroscope measurements. The attitude transfer matrix from the initial navigation frame to the solidified navigation frame can be obtained based on the Earth's rotation angular velocity and alignment time. Let be the attitude transition matrix from the initial navigation frame to the current navigation frame. The attitude matrix can be calculated based on the angular velocity caused by the motion of the carrier lines; therefore, the calculation of the attitude matrix is ​​transformed into... The calculation.

[0026] Furthermore, the state equation of the Kalman filter in S6 is: In the formula, X, Here, represents the state variable and its derivative, respectively; A is the state matrix; ω(t) is the system noise.

[0027] The method for real-time updating of the Kalman filter state matrix is ​​as follows:

[0028]

[0029] wherein, is a one-step prediction of the state at time k, φ k / k-1 is a filter state transition matrix, is an estimated value of the state at time k-1, P k / k-1 is a one-step prediction variance matrix, P k-1 is an estimated variance matrix, Q k-1 is a system noise driving matrix.

[0030] Further, the observation equation of the Kalman filter in the S7 is:

[0031] Z = HX + v(t)

[0032] wherein, X is a state quantity, Z is an observation quantity; H is an observation matrix; v(t) is an observation noise;

[0033] The observation matrix is:

[0034]

[0035] In the formula, δV r is a velocity error vector generated by the lever arm effect, δP r is a position error vector generated by the lever arm effect;

[0036] The measurement update calculation method of the Kalman filter in the S7 is:

[0037]

[0038] wherein, is an optimal estimation of the state at time k, K k is a filter gain matrix, Z k is an observation quantity, R k is a measurement noise variance matrix, is a one-step prediction of the state at time k, H k is an observation matrix, P k / k-1 is a one-step prediction variance matrix, I is an identity matrix.

[0039] Further, in the S8, the velocity and position error estimated by the Kalman filter are used to feedback and correct the system, and the velocity correction method is:

[0040]

[0041] wherein, denotes the velocity before and after the Kalman filter feedback compensation at time k;

[0042] The position correction method is:

[0043]

[0044] wherein, respectively represent the latitude, longitude and height before and after the Kalman filter feedback compensation at the k moment;

[0045] In the S8, the calculation method of the optical fiber platform inertial system transfer alignment result obtained by the attitude misalignment angle estimated by the Kalman filter comprises:

[0046] According to the fine alignment navigation calculation result, the optical fiber platform body attitude matrix at the alignment end moment is

[0047] The calculation method of the misalignment angle attitude compensation matrix according to the fine alignment Kalman filter estimation value is:

[0048]

[0049] wherein, [phi x , phi y , phi z ] respectively represent the x, y and z direction attitude error angle estimation value;

[0050] The calculation method of the transfer alignment result according to the optical fiber platform attitude matrix and the misalignment angle compensation matrix is:

[0051]

[0052] wherein, is the optical fiber platform attitude matrix after compensation, that is, the transfer alignment result.

[0053] A computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by the processor to realize the steps of the active isolation type optical fiber platform high-precision transfer alignment method.

[0054] An active isolation type optical fiber platform high-precision transfer alignment device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to realize the steps of the active isolation type optical fiber platform high-precision transfer alignment method.

[0055] Compared with the prior art, the present application has the following advantages:

[0056] (1) The present application is used in the active isolation type optical fiber platform inertial navigation system dynamic base transfer alignment, which can replace the traditional optical sighting scheme, greatly reduces the equipment support requirements and operation difficulty, and improves the operability of the user.

[0057] (2) The application adopts a Kalman filter optimal estimation transfer alignment method based on speed+position matching, has no special limitation on carrier maneuvering conditions, can adapt to the influence of a certain degree of carrier deformation, and has better environmental adaptability.

[0058] (3) The application adopts an active isolation type rotation control strategy, isolates the console body from external angular motion, can reduce the influence of carrier angular motion on transfer alignment, and has higher precision. BRIEF DESCRIPTION OF DRAWINGS

[0059] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not intended to limit the scope of the application. Moreover, like reference numerals designate like parts throughout the several views in the drawings. In the drawings:

[0060] Figure 1 The figure is a schematic diagram of the system scheme of the application;

[0061] Figure 2 The figure is a time allocation diagram of coarse alignment and fine alignment of the application;

[0062] Figure 3 The figure is a flow chart of the fine alignment module of the application. DETAILED DESCRIPTION

[0063] The application aims to overcome the influence of low-frequency disturbance and other factors on dynamic environment carriers, and the limitation of carrier concealment, maneuvering ability and carrier deformation, and provides an active isolation type optical fiber platform high-precision transfer alignment method to establish the initial attitude reference of the optical fiber platform inertial navigation system dynamic base.

[0064] In order to better understand the above technical solutions, the application technical solutions will be described in detail below by means of the accompanying drawings and specific embodiments. It should be understood that the embodiments of the application and the specific features in the embodiments are detailed descriptions of the application technical solutions, and are not limitations of the application technical solutions. In the case of no conflict, the technical features in the embodiments of the application and the embodiments can be combined with each other.

[0065] The active isolation type optical fiber platform high-precision transfer alignment method provided by the embodiments of the application will be described in further detail below in combination with the accompanying drawings of the specification. The specific implementation manner can include:

[0066] S1: power on and warm up the optical fiber platform inertial system, initialize parameters after the temperature is stable and meets the working conditions, lock zero of the platform frame, and enter the transfer alignment process;

[0067] S2: According to the gyroscope output signal of the optical fiber platform system, the angular velocity information sensed by the platform table body is calculated, a corresponding control torque is applied to the platform rotating mechanism, and the table body is kept stable relative to the inertial space;

[0068] S3: A control instruction is applied to the optical fiber platform rotating mechanism, so that the table body rotates and stops continuously according to the predetermined rotating path, and the system observability is improved;

[0069] S4: Real-time acquisition of optical fiber platform inertial measurement data signals and high-precision main inertial navigation system synchronous signals, speed and position signals, and alignment of optical fiber platform data and main inertial navigation data according to the synchronous signals;

[0070] S5: Coarse alignment is performed using the optical fiber platform inertial measurement data to roughly obtain the initial attitude matrix of the platform table body relative to the navigation coordinate system;

[0071] S6: The coarse alignment result and the optical fiber platform inertial measurement data are used for fine alignment process navigation solution, and the Kalman filter state matrix is updated in real time;

[0072] S7: Determine whether it is the filtering time, if yes, use the main inertial navigation data and the navigation solution received at the current time to calculate the Kalman filter observation and observation matrix, and update the Kalman filter equation to calculate the state estimate value;

[0073] S8: Determine whether it is the end time of alignment, if not, use the Kalman filter estimated speed and position error to feedback and correct the system; if yes, end the alignment, use the attitude misalignment angle estimated by the Kalman filter to compensate and correct the table body navigation result, and obtain the transfer alignment result of the optical fiber platform system.

[0074] Further, the open-loop transfer function of the control loop in S2 for keeping the table body stable in inertial space is:

[0075]

[0076] Wherein, J is the rotational inertia of the platform frame shaft, G FOG (s) is the transfer function of the fiber optic gyroscope, G c (s) is the loop correction network, K p is the power level amplification coefficient, G m (s) is the transfer function of the shaft end torque motor.

[0077] In one possible implementation, in S3 to increase the system observability, the table body is rotated 180 degrees around the zenith axis during the alignment process, and the predetermined rotating path is as follows:

[0078] Serial number Outer ring angle (°) Inner ring angle (°) Table body angle (°) 0 Forward rotation 180 0 0 1 180 0 0 2 Reverse rotation 180 0 0 3 … … …

[0079] As shown in the table above, the fiber optic platform is rotated 180 degrees in the positive direction around the outer ring frame axis from the zero position, and then held for a period of time. Then it is rotated 180 degrees in the negative direction around the outer ring frame axis, and then held for a period of time. This process is repeated until the alignment is completed. The rotation time plus the holding time equals the total alignment time.

[0080] The transfer alignment process includes multiple dwelling positions and multiple rotation processes. Starting from the zero position, the platform body rotates 180° forward and backward around the outer ring axis each time. After rotating to each position, the platform body is in a spatially stable state and dwells for a period of time.

[0081] Furthermore, in step S4, the main inertial navigation system outputs a synchronization signal to perform time synchronization and data alignment between the main and sub-inertial navigation systems, specifically including:

[0082] The fiber optic platform acquires the periodic square wave signal output by the main inertial navigation system. When the alignment process begins, the first falling edge of the synchronization signal received by the platform is defined as the start time. Subsequently, the inertial measurement data and the velocity and position information of the main inertial navigation system are time-stamped and aligned.

[0083] In one possible implementation, obtaining the coarse alignment attitude matrix using inertial measurement data from the fiber optic platform in step S5 specifically includes:

[0084] A relatively accurate initial attitude information is obtained by using a multi-vector attitude determination analytical coarse alignment method based on external auxiliary information. The solution method is as follows:

[0085] The values ​​of the velocity vectors α and β of the computing station system and the navigation system:

[0086]

[0087] Where V and ΔV represent velocity and velocity increment, respectively, T represents the sampling period, the subscript i represents the i-th sampling time, the superscript g represents the projection in the navigation frame, and k is the number of samples. For t i The transformation matrix from the time-stage system to the solidification stage system, where Δθ is the angular increment. For t i The transformation matrix from the time-based navigation frame to the solidified navigation frame, V g For the navigation system velocity, t i Let I be the time interval, and let I be the identity matrix. G is the projection of the rotational angular velocity of the navigation frame relative to the inertial frame onto the navigation frame. g The projection of gravitational acceleration onto the navigation system. The projection of the Earth's rotational angular velocity onto the navigation system;

[0088] Find α and β at multiple times, and then use the relation... The least square method is used to fit and obtain Results

[0089] The initial posture matrix solving method of the table body is as follows:

[0090]

[0091] In the formula, is the posture transfer matrix from the table system to the solidification table system, which can be obtained by using the gyro measurement value; is the posture transfer matrix from the initial navigation system to the solidification navigation system, which can be obtained according to the earth rotation angular velocity and the alignment time; is the posture transfer matrix from the initial navigation system to the current navigation system, which can be calculated according to the dependent angular velocity caused by the linear motion of the carrier, so that the calculation of the posture matrix can be converted into the calculation of .

[0092] In a possible implementation manner, the state equation of the fine alignment Kalman filter in S6 is as follows:

[0093]

[0094] In the formula, X, is the state quantity, the differential of the state quantity; A is the state matrix; ω(t) is the system noise.

[0095] Further, the state update formula of the fine alignment Kalman filter in S6 is as follows:

[0096]

[0097] In the formula, X is the one-step prediction of the state at time k, φ k / k-1 is the filter state transfer matrix, is the estimated value of the state at time k-1, P k / k-1 is the variance matrix of the one-step prediction, P k-1 is the estimated variance matrix, Q k-1 is the system noise driving matrix.

[0098] In a possible implementation manner, the observation equation of the fine alignment Kalman filter in S7 is as follows:

[0099] Z=HX+v(t)

[0100] In the formula, Z is the observation quantity; X is the state quantity; H is the observation matrix; v(t) is the observation noise;

[0101] The observation matrix can be represented as:

[0102] wherein, δV r is the velocity error vector generated by the lever arm effect, δP r is the position error vector generated by the lever arm effect;

[0103] In one possible implementation, the measurement update calculation formula of the S7 fine alignment Kalman filter is:

[0104]

[0105] wherein, is the optimal estimation of the state at time k, K k is the filter gain matrix, Z k is the observation, R k is the measurement noise variance matrix, H k is the observation matrix, and I is the unit matrix.

[0106] In one possible implementation, the S8 uses the Kalman filter to estimate the velocity and position error to correct the system, and the velocity correction formula is as follows:

[0107]

[0108] wherein, denotes the velocity before and after the Kalman filter feedback compensation at time k;

[0109] The position correction formula is:

[0110]

[0111] wherein, denote the latitude, longitude, and height before and after the Kalman filter feedback compensation at time k, respectively;

[0112] In one possible implementation, the calculation method of the optical fiber platform system transfer alignment result obtained by the attitude misalignment angle estimated by the Kalman filter in the S8 is as follows:

[0113] According to the fine alignment navigation calculation result, the platform body attitude matrix at the end of the alignment is

[0114] The calculation method of the misalignment angle attitude compensation matrix according to the Kalman filter estimation value is as follows:

[0115]

[0116] wherein, [φ x , φ y , φ z ] denote the x, y, and z direction attitude error angle estimation values, respectively;

[0117] The calculation method for obtaining the transfer alignment result according to the platform attitude matrix and the misalignment angle compensation matrix is as follows:

[0118]

[0119] wherein, is the platform attitude matrix after compensation, that is, the transfer alignment result.

[0120] In the scheme provided in the embodiment of the application, the transfer alignment scheme adopts the Kalman filter optimal estimation method based on the "speed+position" matching to estimate the attitude misalignment angle of the optical fiber platform, that is, the speed and position errors output by the primary and secondary inertial navigation systems are used as observation values, the error parameters are estimated through the Kalman filter, and the rotation of the platform around the skyward axis is controlled to improve the observability of the Kalman filter, so that high-precision transfer alignment in a dynamic environment is realized. The overall scheme principle block diagram is as shown in Figure 1 .

[0121] The implementation steps of the high-precision transfer alignment method of the active isolation type optical fiber platform in the embodiment include:

[0122] (1) Platform power-up and warming

[0123] The optical fiber platform inertial system is powered up and warmed up, and after the temperature is stable and meets the working conditions, parameter initialization is performed, and the platform frame is locked to zero to enter the transfer alignment process.

[0124] (2) Platform rotation control

[0125] Control instructions are applied to the rotation mechanism of the optical fiber platform, so that the platform rotates continuously and stops according to the predetermined rotation path. The rotation process is shown in the following table, which includes 12 dwell positions and 12 rotation processes. The platform rotates 12 times around the outer ring axis with a rotation angle of 180°, and the rotation angle rate is 15° / s. After rotating to each position, the platform is in a space stable state and dwells for a period of time. The total time of the entire alignment process is 15 minutes.

[0126] Serial number Outer ring angle (°) Inner ring angle (°) Table body angle (°) 0 Forward rotation 180 0 0 1 180 0 0 2 Reverse rotation 180 0 0 3 0 0 0 4 … … …

[0127] (3) Primary and secondary inertial navigation data acquisition

[0128] The optical fiber platform inertial measurement data signals, the synchronous signals, the speed and position signals of the high-precision primary inertial navigation system are acquired in real time, and the optical fiber platform data and the primary inertial navigation data are aligned according to the synchronous signals.

[0129] (4) Coarse alignment calculation

[0130] The sampling time distribution of the coarse and fine alignment processes is as shown in Figure 2The coarse alignment process flow chart is shown in FIG. 2. The coarse alignment calculation is performed using the coarse alignment process fiber platform inertial measurement data and the master inertial navigation sampling data, and the initial attitude matrix of the platform body relative to the navigation coordinate system is roughly obtained.

[0131] (5) Fine alignment calculation

[0132] The fine alignment process flow chart is shown in FIG. 3. The fine alignment process navigation solution is performed using the coarse alignment result and the fiber platform inertial measurement data, and the Kalman filter state matrix is updated in real time. Figure 3

[0133] The selected state variables in the fine alignment Kalman filter are:

[0134] X = [Z gx ,Z gy ,Z gz ,φ x ,φ y ,φ z ,Z ax ,Z ay ,Z az ,δV E ,δV N ,δV U ,δL,δλ,δh] T

[0135] wherein Z gx , Z gy , Z gz represent gyroscope zero bias, Z ax , Z ay , Z az represent accelerometer zero bias, φ x , φ y , φ z represent attitude misalignment angle, δV E , δV N , δV U represent velocity error, and δL, δλ, δh represent position error.

[0136] The state matrix calculation formula is as follows:

[0137]

[0138] wherein,

[0139]

[0140] wherein ω ie is the earth rotation angular velocity, [V E , V N , V U ] are eastward, northward and skyward velocities, and R M ​R is the principal meridian radius of curvature, h is the height, L is the latitude, N R is the principal meridian radius of curvature, h is the height, L is the latitude,

[0141] [f E , f N , f U ] are eastward, northward, and skyward specific force.

[0142] The state transition matrix is calculated according to the state matrix, and the calculation formula is:

[0143]

[0144] Where, A(t k ) is the state matrix at t k , T is the sampling period, and I is the unit matrix.

[0145] It is judged whether the filtering time is reached, if yes, the Kalman filter observation and observation matrix are calculated by using the main inertial navigation data and navigation solution received at the current time, and the observation selected by the fine alignment Kalman filter is:

[0146] Z = [δV E , δV N , δV U , δL, δλ, δh] T

[0147] The observation calculation formula is as follows:

[0148]

[0149] Where V is the velocity vector, [L, λ, h] is the latitude, longitude, and height, and the subscript s represents the fiber platform, and m represents the main inertial navigation.

[0150] The observation matrix calculation formula is as follows:

[0151]

[0152] In the formula, δV r is the velocity error vector generated by the lever arm effect, and δP r is the position error vector generated by the lever arm effect.

[0153] The Kalman filter equation is updated, and the state quantity estimation value is calculated.

[0154] (6) Estimation error compensation and correction, calculation of alignment result

[0155] It is judged whether the alignment end time is reached, if not, the system is feedback corrected by using the Kalman filter estimated velocity and position error, and the calculation formula is as follows:

[0156]

[0157] wherein, is the state estimate value.

[0158] If the alignment end time is reached, the alignment is ended, the attitude misalignment angle obtained by the Kalman filter estimation is used to compensate and correct the navigation result of the platform body, the transfer alignment result of the optical fiber platform system is calculated, and the calculation formula is as follows:

[0159] According to the navigation calculation result of the fine alignment, the platform body attitude matrix at the alignment end time is

[0160] According to the estimation value of the fine alignment Kalman filter, the calculation method of the misalignment angle attitude compensation matrix is as follows:

[0161]

[0162] wherein, respectively represent the x, y, and z direction attitude error angle estimation values;

[0163] According to the platform body attitude matrix and the misalignment angle compensation matrix, the calculation formula of the transfer alignment result is as follows:

[0164]

[0165] wherein, is the platform body attitude matrix after compensation, that is, the transfer alignment result.

[0166] The above detailed description of the present application is made in combination with specific embodiments and exemplary examples, but these descriptions cannot be understood as limitations of the present application. Those skilled in the art understand that the technical solutions and embodiments of the present application can be variously replaced, modified or improved without deviating from the spirit and scope of the present application, and these all fall within the scope of the present application. The protection scope of the present application is subject to the appended claims.

[0167] The present application provides a computer readable storage medium, which stores computer instructions, when the computer instructions run on a computer, make the computer execute Figure 1 the method.

[0168] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer usable program codes.

[0169] The present application is described in reference to the flowchart and / or block diagrams of the methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 Figure 1 The flowchart and / or block diagrams in the present application illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to the present application. In this regard, each block in the flowchart and / or block diagrams can represent a module, segment, or portion of code, which comprises one or more executable

[0170] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 Figure 1 The flowchart and / or block diagrams in the present application illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to the present application. In this regard, each block in the flowchart and / or block diagrams can represent a module, segment, or portion of code, which comprises one or more executable

[0171] The computer program instructions can also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 Figure 1 The flowchart and / or block diagrams in the present application illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to the present application. In this regard, each block in the flowchart and / or block diagrams can represent a module, segment, or portion of code, which comprises one or more executable

[0172] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the

[0173] Those skilled in the art will appreciate that the application described herein is susceptible to variations and modifications other than those specifically described. It is to be understood that the application includes all such variations and modifications which fall within the spirit and scope of the present application.​​​

Claims

1. A high precision transfer alignment method for an active isolated fiber platform, characterized in that, The method comprises the following steps: S1, power on and warm up the fiber platform inertial system, and initialize parameters after the temperature is stable and meets the working conditions, and the fiber platform frame is locked to zero and then enters the transfer alignment process; S2, according to the gyro output signal of the fiber platform inertial system, calculate the angular velocity information sensed by the fiber platform table body, and apply corresponding control to the fiber platform rotating mechanism to keep the fiber platform table body stable relative to the inertial space; S3, apply control to the fiber platform rotating mechanism to make the fiber platform table body rotate continuously and stay according to the predetermined rotating path; S4, collect the fiber platform inertial measurement data signal and the synchronous signal, speed and position signal of the high-precision main inertial navigation system in real time, and align the fiber platform data and the main inertial navigation data according to the synchronous signal; S5, perform coarse alignment by using the fiber platform inertial measurement data to obtain the initial attitude matrix of the fiber platform table body relative to the navigation coordinate system; S6, perform fine alignment by using the coarse alignment result and the fiber platform inertial measurement data to perform navigation solution, and update the Kalman filter state matrix in real time; S7, judge whether the filtering time is reached; If yes, calculate the Kalman filter observation and observation matrix by using the main inertial navigation data and the navigation solution received at the current time, update the Kalman filter equation, and calculate the state quantity estimation value; S8, judge whether the alignment end time is reached; If no, perform feedback correction on the system by using the Kalman filter estimated speed and position error; if yes, end the alignment, compensate and correct the fiber platform table body navigation result by using the attitude misalignment angle estimated by the Kalman filter, and obtain the fiber platform inertial system transfer alignment result.

2. The method of claim 1, wherein the method further comprises: The open loop transfer function of the fiber optic platform indexing mechanism under the corresponding control is where J is the platform frame shaft moment of inertia, G FOG (s) is the fiber optic gyroscope transfer function, G c (s) is the loop correction network, K p is the power stage amplification coefficient, G m (s) is the shaft end torque motor transfer function.

3. The method of claim 1, wherein the method further comprises: The predetermined rotating path comprises: rotating the fiber platform 180 degrees in the positive direction around the outer ring frame shaft from the zero position, then staying for a period of time, rotating 180 degrees in the reverse direction around the outer ring frame shaft, then staying for a period of time, and repeating the process until the alignment is ended, wherein the rotating time plus the staying time is equal to the total alignment time.

4. The method of claim 1, wherein the method further comprises: The alignment comprises: the fiber platform collects the periodic square wave signal output by the main inertial navigation system, and defines the time when the fiber platform receives the first falling edge of the synchronous signal as the starting time after starting the transfer alignment process, and then aligns the time stamps of the inertial measurement data and the main inertial navigation speed and position information.

5. The method of claim 1, wherein the method further comprises: The method for obtaining the initial attitude matrix of the fiber platform table body relative to the navigation coordinate system comprises: An accurate initial attitude information is obtained by using a multi-vector attitude determination analysis formula based on external auxiliary information, and the solving method is as follows: The values of the table system speed vector and the navigation system speed vector α, β are calculated: where V and AV represent velocity and velocity increment respectively, T represents sampling period, i represents sampling time, the upper index g represents projection in navigation system, k represents sampling number, is the transformation matrix from the navigation system to the solidification system at time t i , and Δθ is the angular increment, is the transformation matrix from the navigation system to the solidification system at time t i , V g is the navigation system velocity, t i is the time, and I is the unit matrix, is the angular velocity of the navigation system relative to the inertial system projected in the navigation system, G g is the gravity acceleration projected in the navigation system, is the angular velocity of the earth rotation projected in the navigation system; The α and β at multiple time points are found, and the relationship is The least square method is used for fitting to obtain The initial attitude matrix of the fiber platform table body is: In the formula, is the attitude transfer matrix from the platform system to the solidified platform system, which can be obtained by gyro measurement values; is the attitude transfer matrix from the initial navigation system to the solidified navigation system, which can be obtained according to the earth rotation angular velocity and the alignment time; is the attitude transfer matrix from the initial navigation system to the current navigation system, the calculation of the attitude matrix is converted into the calculation of .

6. The method of claim 1, wherein the method is a high precision transfer alignment method for an active isolated optical bench platform. The state equation of the Kalman filter in the S6 is In the formula, X, respectively, state quantity, differential of state quantity; A is a state matrix; w(t) is system noise; The method for updating the Kalman filter state matrix in real time is: wherein, is a one-step prediction of the state at time k, φ k / k-1 is a filter state transition matrix, is an estimate of the state at time k-1, P k / k-1 is a variance matrix of the one-step prediction, P k-1 is a variance matrix of the estimate, Q k-1 is a system noise driving matrix.

7. The high-precision transmission alignment method for an active isolated optical fiber platform according to claim 1, characterized in that, The observation equation of the Kalman filter in S7 is: Z=HX+v(t) Wherein, X is the state quantity, Z is the observation, H is the observation matrix, and v(t) is the observation noise; The observation matrix is: where δV r is the velocity error vector resulting from the lever arm effect, δP r is the position error vector resulting from the lever arm effect; The measurement update calculation method of the Kalman filter in S7 is: wherein, is the optimal estimate of the state at time k, K k is the filter gain matrix, Z k is the observation, R k is the measurement noise variance matrix, is the one-step prediction of the state at time k, H k is the observation matrix, P k / k-1 is the variance matrix of the one-step prediction, I is the identity matrix.

8. The high-precision transmission alignment method for an active isolated optical fiber platform according to claim 1, characterized in that, In S8, the system is corrected by using the Kalman filter estimated speed and position error, the speed correction method is: wherein, vk represents the speed before and after Kalman filter feedback compensation at time k. The position correction method is: wherein, respectively represent the latitude, longitude and height before and after the Kalman filter feedback compensation at time k. The calculation method of the transfer alignment result of the fiber platform inertial system using the attitude misalignment angle estimated by the Kalman filter in the S8 comprises: According to the fine alignment navigation calculation result, the optical fiber platform table body attitude matrix at the alignment end moment is The calculation method of the misalignment angle attitude compensation matrix according to the Kalman filter estimation value of the fine alignment is: wherein [φ x , φ y , φ z ] represent the estimated values of the attitude error angles in the x, y, z directions, respectively; The calculation method of the transfer alignment result according to the fiber platform attitude matrix and the misalignment angle compensation matrix is: wherein, is the post-compensation fiber bench pose matrix, i.e. the transfer alignment result.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1-8. The computer program is executed by the processor to realize the steps of the method in any one of claims 1-8.

10. An active isolated fiber platform high precision transfer alignment apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the apparatus characterized by: The processor executes the computer program to realize the steps of the method in any one of claims 1-8.

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