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CN-121977612-A - Error online identification and high-precision self-alignment method for RINS

CN121977612ACN 121977612 ACN121977612 ACN 121977612ACN-121977612-A

Abstract

The invention discloses an error online identification and high-precision self-alignment method for RINS, belonging to the technical field of inertial navigation and integrated navigation. According to the method, an excitation mechanism of each error source to the platform deflection angle and the speed error under rotary modulation is analyzed through a system, and an expansion state vector comprising key error items of the platform deflection angle, the gyroscope and the accelerometer and first-order and second-order errors of the outer frame grating function is constructed. On the basis, the equivalent platform deflection angle and the heading attitude difference are taken as observables, and the Recursive Least Squares (RLS) algorithm is utilized to perform online joint estimation and real-time compensation on all states. The method can mechanically separate the equivalent deflection angle caused by the actual initial platform deflection angle and the sensor error, remarkably improve the alignment precision and the convergence speed, and effectively inhibit the speed and the course gesture oscillation in the subsequent navigation. Experimental verification shows that the method has the advantages of high precision and high reliability.

Inventors

  • WANG LEI
  • ZHANG HONG
  • WANG ZIQI
  • Ye jiangnan
  • TANG CHAOHUI

Assignees

  • 北京航空航天大学

Dates

Publication Date
20260505
Application Date
20260206

Claims (10)

  1. 1. An error online identification and high-precision self-alignment method for RINS, comprising the steps of: step 1, constructing an expansion state vector containing initial platform deflection angle, gyro error item, accelerometer error item and first-order and second-order harmonic coefficients of an outer frame grating function; Step 2, a system state equation is established based on the extended state vector, and a system measurement equation is established by taking the equivalent platform deflection angle and the heading attitude difference as observables; Step 3, on-line estimating all error items in the extended state vector by adopting a recursive least square algorithm based on the system state equation and the system measurement equation; And 4, compensating each error item in real time according to the estimation results of all the error items, and completing RINS high-precision self-alignment.
  2. 2. The method for online identification and high-precision self-alignment of errors in RINS according to claim 1, wherein the extended state vectors constructed in step 1 specifically include initial east, north and sky platform bias angles, north and sky equivalent gyro drift, gyro scale factor errors, gyro installation errors, accelerometer zero bias, accelerometer installation errors, and first and second order harmonic coefficients of the grating function.
  3. 3. The method for online identification and high-precision self-alignment of the error of RINS according to claim 2, wherein the equivalent platform deflection angle caused by the gyro error term is obtained by performing discrete integration on the projection of the gyro measurement error under an inertial measurement coordinate system, and the first-order and second-order harmonic coefficients of the grating function are used for representing the periodic attitude demodulation error related to the rotation angle caused by the measurement error of the outer frame grating sensor.
  4. 4. The method according to claim 1, wherein in the step 2, the system measurement equation uses the equivalent platform deflection angle and the heading attitude difference as observables, and the measurement matrix is composed of partial derivatives of each observables with respect to each state variable in the extended state vector, and reflects the excitation relation of each error source to observables under rotation modulation.
  5. 5. The method for online identification and high-precision self-alignment of errors for RINS according to claim 4, wherein the equivalent platform deflection angle is calculated from the ratio of the component projected in the horizontal direction by the accelerometer output at time t and the local gravitational acceleration, and is specifically reflected as an equivalent platform deflection angle dynamic model in the east and north directions.
  6. 6. The method for online identification and high-precision self-alignment of RINS errors according to claim 4, wherein the heading attitude difference is the difference between the carrier heading angle outputted in real time by RINS and the initial heading angle when entering into precision alignment, and the dynamic model contains the effects of the sky-direction gyro drift, the z-axis gyro scale factor error and the outer frame grating function error.
  7. 7. The method for online error identification and high-precision self-alignment of RINS according to claim 1, wherein in step 3, the recursive least square algorithm implements recursive estimation by: At the (k+1) th moment, calculating a gain matrix at the current moment by using the state estimation value at the previous moment, the measurement matrix at the current moment and the observed quantity at the current moment and combining a recursion update coefficient, and updating according to the gain matrix to obtain the state vector estimation value at the current moment, and realizing online, iterative and joint estimation of the extended state vector by continuously iterating the process.
  8. 8. The method for online identification and high-precision self-alignment of RINS errors according to claim 1, wherein in the step 4, the real-time compensation specifically includes correcting the initial attitude of the system according to the estimated initial platform drift angle, compensating the gyro output according to the estimated gyro drift, scale factor error and installation error, compensating the accelerometer output according to the estimated accelerometer zero drift and installation error, and compensating the course attitude solution according to the estimated first-order and second-order harmonic coefficients of the grating function.
  9. 9. An electronic device, comprising: One or more processors; A memory for storing one or more programs; wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the error online identification and high accuracy self-alignment method of any of claims 1-8 for RINS.
  10. 10. A computer readable storage medium having stored thereon executable instructions which when executed by a processor cause the processor to implement a method for online error identification and high precision self-alignment of RINS as claimed in any one of claims 1 to 8.

Description

Error online identification and high-precision self-alignment method for RINS Technical Field The invention belongs to the technical field of inertial navigation and integrated navigation, and particularly relates to an error online identification and high-precision self-alignment method for RINS. Background The initial alignment is a precondition of the inertial navigation system to realize high-precision navigation, and the precision and the convergence speed directly influence the overall performance of the system. The rotation modulation type inertial navigation system (RINS) can effectively modulate constant bias of the gyroscope and the accelerometer through the periodic rotation inertial measurement unit, obviously improve the navigation precision in long voyage, but simultaneously excite the sensor calibration residual error to cause obvious speed and gesture oscillation, which becomes a bottleneck problem for restricting RINS performance improvement. The current research of suppressing the speed oscillation is mainly focused on two technical paths, namely, optimizing a system rotation scheme to actively suppress error excitation and performing online error compensation through an amplification state filter. The method has the advantages that the method can inhibit specific errors to a certain extent by designing complex rotation sequences, but often prolongs the modulation period and is difficult to adapt to a shaped system, and the method introduces a limited error state on the basis of a traditional alignment model, can realize partial compensation, but generally lacks systematic analysis on multiple error coupling mechanisms, and particularly has insufficient attention on the influence of errors of a grating sensor, so that the inhibition effect is limited in a complex error environment. In addition, in the alignment scheme adopting the course gesture as the observed quantity, the grating error directly pollutes the measurement information, so that the alignment precision is reduced, obvious periodic gesture oscillation is caused, and the error is indistinguishable from the gyro scale factor error in a specific rotation mode, so that the difficulty of error identification and compensation is further increased. Therefore, in the prior art, on the premise of ensuring alignment rapidity, systematic online identification and effective compensation of the multi-source coupling error excited in the rotation modulation process are difficult to realize, so that alignment accuracy is limited, platform deflection angle oscillation is obvious, speed output is not smooth, and severe requirements of high-end applications such as high-dynamic carriers and multi-source information fusion on instantaneous data accuracy are difficult to meet. Disclosure of Invention In order to solve the technical problems, the invention provides an error online identification and high-precision self-alignment method for RINS, which is used for restraining off-angle oscillation in the alignment process by estimating and decoupling a key IMU error item and an initial platform off-angle in real time, so that the alignment precision and convergence speed are obviously improved. Meanwhile, key sensor errors such as grating sensor residual errors, low-order grating errors and the like are included in the state vector during static base alignment, and a more complete state space model is constructed. By on-line identification and compensation of the error parameters of the key sensor, the system speed and course attitude oscillation are effectively reduced. In order to achieve the above purpose, the invention adopts the following technical scheme: An error online identification and high-precision self-alignment method for RINS, comprising: step 1, constructing an expansion state vector containing initial platform deflection angle, gyro error item, accelerometer error item and first-order and second-order harmonic coefficients of an outer frame grating function; Step 2, a system state equation is established based on the extended state vector, and a system measurement equation is established by taking the equivalent platform deflection angle and the heading attitude difference as observables; Step 3, on-line estimating all error items in the extended state vector by adopting a recursive least square algorithm based on the system state equation and the system measurement equation; And 4, compensating each error item in real time according to the estimation results of all the error items, and completing RINS high-precision self-alignment. Further, the extended state vector constructed in the step 1 specifically comprises initial east, north and sky platform declination, north and sky equivalent gyro drift, gyro scale factor error, gyro installation error, accelerometer zero bias, accelerometer installation error and grating function first order and second order harmonic coefficients. Furthermore, the equivalent platform deflection angle