A MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod

Abstract

A MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod includes: (1) the pod sends calibration commands, satellite navigation information, and dual-axis frame angles to the MEMS inertial navigation system via a communication interface; (2) during the self-calibration process, the MEMS inertial navigation system feeds back the dual-frame rotation to the pod, assisting the dual-axis pod in performing 8-position rotation during the calibration phase, during which the MEMS inertial navigation system estimates instrument errors, installation deviation angles, and reference surface deviation angles; (3) after completing the 8-position rotation during the calibration phase, the MEMS inertial navigation system enters the calibration self-test state; (4) during the calibration self-test process, the MEMS inertial navigation system feeds back the dual-frame rotation to the pod, assisting the pod in performing 5-position rotation during the testing phase, during which the correctness of calibration parameters is detected; (5) after the MEMS inertial navigation system completes the calibration self-test, it feeds back the calibration status and stores the calibration results. This invention solves the problem of calibration errors caused by environmental factors that cannot provide a horizontal reference or by an uneven reference surface.

Description

Technical Field

[0001] This invention relates to a MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod, for use in the field of inertial navigation. Background Technology

[0002] MEMS inertial navigation system is installed inside the airborne optoelectronic pod. Figure 1 The MEMS inertial navigation system is used to obtain attitude and heading information for sensitive pods and assist airborne optoelectronic pods in aiming and positioning. To ensure the accuracy of the attitude and heading information fed back to the pod by the MEMS inertial navigation system, it is necessary to correct the deviation angle between the MEMS inertial navigation system and the pod coordinate system. In addition, based on the long-term stability characteristics of MEMS instruments, the instruments need to be calibrated and maintained regularly to maintain accuracy.

[0003] Previously, calibrating the installation deviation angle required relying on a calibrated marble plate or turntable as a horizontal reference surface to ensure tracking the ground vertical. However, in actual engineering applications, the test conditions under the ideal laboratory environment may not be available, resulting in the pod's vertical axis not being perpendicular to the geoid. Under this condition, the installation deviation angle calibrated by the MEMS inertial navigation system is inaccurate. Therefore, it is necessary to find a method for calibrating the installation deviation angle of the MEMS inertial navigation system that does not rely on an absolute zero reference to ensure calibration accuracy. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod. While estimating and compensating for instrument errors, it can calibrate the installation deviation angle of the MEMS inertial navigation inside the pod without relying on a horizontal reference plane, thus solving the problem of calibration error caused by the inability to provide a horizontal reference or an uneven reference plane due to environmental factors.

[0005] The objective of this invention is achieved through the following technical solutions:

[0006] A MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod includes the following steps:

[0007] (1) The pod sends calibration commands, satellite navigation information and dual-axis frame angles to the MEMS inertial navigation system through the communication interface;

[0008] (2) During the self-calibration process of MEMS inertial navigation, the dual-frame rotation is fed back to the pod to assist the dual-axis pod in performing 8-position rotation during the calibration stage. During the rotation, MEMS inertial navigation estimates instrument error, installation deviation angle, and reference plane deviation angle.

[0009] (3) After completing the 8-position rotation during the calibration phase, the MEMS inertial navigation system enters the calibration self-test state;

[0010] (4) During the MEMS inertial navigation calibration self-test process, the dual-frame rotation is fed back to the pod to assist the pod in performing the 5-position rotation during the testing phase, and the correctness of the calibration parameters is detected during the rotation.

[0011] (5) After the MEMS inertial navigation calibration self-test is completed, the calibration status is fed back and the calibration results are stored.

[0012] In one embodiment of the present invention, the communication interface adopts any one of RS232 serial port, RS422 serial port, RS485 serial port, and CAN bus.

[0013] In one embodiment of the present invention, the satellite navigation information includes geographic system (northeast sky) speed and location information.

[0014] In one embodiment of the present invention, the dual-axis frame angle includes the pod pitch axis angle and the azimuth axis angle.

[0015] In one embodiment of the present invention, the MEMS inertial navigation system is an inertial measurement unit that uses a three-axis microelectromechanical gyroscope and a three-axis microelectromechanical accelerometer as sensors, is installed inside the pod, and can rotate with the pod.

[0016] In one embodiment of the present invention, during the rotation of the MEMS inertial navigation system with the pod, the pod's azimuth axis corresponds to the MEMS inertial navigation azimuth axis, and the pod's pitch axis corresponds to the MEMS inertial navigation roll axis.

[0017] In one embodiment of the present invention, the instrument error is the three-axis gyroscope zero drift, the three-axis accelerometer zero bias and the scale factor, the installation deviation angle is the deviation angle of the MEMS inertial navigation relative to the horizontal plane and the normal plane where the pod's optical axis is located, and the reference plane deviation angle is the deviation angle of the pod's optical axis relative to the geoid.

[0018] In one embodiment of the present invention, the rotation sequence of position 8 and the angle of the dual-axis frame in step (2) are detailed below. Figure 2 Middle ①~⑧.

[0019] In one embodiment of the present invention, the rotation sequence of the detection stage 5 and the angle of the dual-axis frame in step (4) are detailed below. Figure 2 Middle 9

[0020] Compared with the prior art, the present invention has the following advantages:

[0021] This invention achieves multi-position rotation of the MEMS inertial navigation system by utilizing the pitch and azimuth dual-axis frame angles of the pod. When calibrating the installation deviation angle between the MEMS inertial navigation system and the reference plane, the error angle of the reference plane itself relative to the geoid is estimated by the attitude error at different positions and compensated for, ensuring that the obtained installation deviation angle of the MEMS inertial navigation system is the true deviation relative to the geoid. Thus, the MEMS inertial navigation system can be self-calibrated without relying on or calibrating the horizontal reference plane. Attached Figure Description

[0022] Figure 1 System diagram

[0023] Figure 2 This is a flowchart of the MEMS inertial navigation self-calibration process.

[0024] Figure 3 The instrument error estimation curve is shown in the example.

[0025] Figure 4 The curves of gyroscope zero drift, accelerometer zero bias, and accelerometer scaling factor estimated by MEMS inertial navigation during the rotation process are shown in the example. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0027] A MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod includes the following steps:

[0028] (1) The pod sends inertial navigation calibration commands, satellite navigation information, and dual-axis frame angles to the MEMS via a communication interface. The communication interface can be any one of RS232 serial port, RS422 serial port, RS485 serial port, or CAN bus. The satellite navigation information includes velocity and position information in geographic system. The dual-axis frame angles include the pod's azimuth frame angle and pitch frame angle.

[0029] (2) During the self-calibration process of MEMS inertial navigation, the dual-frame rotation is fed back to the pod to assist the dual-axis pod in performing 8-position rotation during the calibration stage. During the rotation, MEMS inertial navigation estimates the instrument error, installation deviation angle, and reference plane deviation angle.

[0030] The target rotation of the dual-axis frame of the pod is fed back by MEMS inertial navigation. The initial zero position of the dual-axis frame is (azimuth 0°, pitch 0°). The eight rotation sequences during the calibration phase are as follows: initial zero position -> (azimuth 90°, pitch 0°) -> (azimuth 90°, pitch -90°) -> (azimuth 0°, pitch -90°) -> (azimuth 0°, pitch 0°) -> (azimuth 180°, pitch 0°) -> (azimuth 0°, pitch 0°) -> (azimuth 0°, pitch -90°) -> (azimuth 0°, pitch 0°).

[0031] The error of MEMS inertial navigation instruments is estimated by establishing a feedback-corrected Kalman filter model with 19-dimensional state variables and 7-dimensional observation variables. The state variables are selected as 3-dimensional attitude error, 3-dimensional velocity error, 3-dimensional position error, 3-dimensional gyroscope zero drift, 3-dimensional accelerometer zero bias, 3-dimensional accelerometer scale factor, and heading deviation angle. The observation variables are selected as velocity, position, and reference heading. The model is as follows:

[0032]

[0033] In the formula, n is the local geographic coordinate system, and b is the coordinate system of this country; For pitch angle error estimation, For roll angle error estimation, For azimuth error estimation; For the estimation of eastward velocity error, For northbound velocity error estimation, For the estimation of the upward velocity error; δL n For latitude error estimation, δλ n For longitude error estimation, δh n For height error estimation; For zero drift estimation of the right-hand gyroscope, For zero drift estimation of forward gyroscope, For zero drift estimation of vertical gyroscope; For the right-hand accelerometer zero bias estimation, For the forward accelerometer zero bias estimation, For zero bias estimation of vertical accelerometer; For the estimation of the right-hand accelerometer scale factor, For the estimation of the forward accelerometer scaling factor, For estimation of the vertical accelerometer scale factor; ψ n This is for estimating the installation deviation based on the reference heading.

[0034] Using eastward speed, northward speed, celestial speed, latitude, longitude, altitude, and reference heading as observations, the model is as follows:

[0035]

[0036] In the formula, Z k For observable measurement, it can be decomposed into Z. vk For velocity observation, Z pk For location observation, For azimuth observation; v ins For MEMS inertial navigation velocity, v gps For satellite speed, p ins For MEMS inertial navigation position, p gps For the position of the satellite guide, For MEMS inertial navigation azimuth, Let ψ be the reference azimuth angle, and ψ be the estimated azimuth installation deviation angle; H is the observation matrix, which can be decomposed into H... v For velocity observation matrix, H p For the location observation matrix, This is the azimuth observation matrix; X k V is the system state variable; k This is the noise matrix.

[0037] The closed-loop Kalman filter equation is as follows:

[0038] 1) Equations of state:

[0039]

[0040] In the formula, X k F is a system state variable. k / k-1 W is the one-step transition matrix from time k-1 to time k. k Z is the noise matrix; k For the measurement, H k Let V be the observation matrix at time k. k This is the noise matrix.

[0041] 2) Filtering equation

[0042]

[0043] In the formula, F represents the predicted system state from time k-1 to time k, where O is a zero matrix; k Let P be the system state matrix at time k. k Let Q be the system state covariance matrix at time k. k Let k be the system noise covariance matrix at time k. for The covariance matrix; Let H be the gain matrix at time k. k Let P be the observation matrix at time k. k / k-1 For X k / k-1 The covariance matrix, R k The noise covariance matrix is ​​measured at time k; The system state covariance matrix at time k is obtained, where I is the identity matrix; To obtain the estimated system state at time k, Z k For observation purposes.

[0044] The estimation process for installation deviation angle and datum plane deviation angle is as follows: Figure 2 In steps ④ to ⑧, when the biaxial frame angle is located at the angle in step ④, calculate the installation deviation angle. and When the biaxial frame angle is located at the angle in step ⑤, calculate the installation deviation angle. and As shown in the following formula:

[0045]

[0046] In the formula, B is the base coordinate system; The horizontal attitude angle of the MEMS inertial navigation system when it is converted from the b-frame to the B-frame in step ④; The horizontal attitude angle of the MEMS inertial navigation system when it is converted from the b-frame to the B-frame in step ⑤; The reference attitude angle is 0° (the reference angle for calculation). The reference plane deviation angle.

[0047] When the biaxial frame angle is located at the angle in step ⑥, calculate As shown in the following formula:

[0048]

[0049] When the biaxial frame angle is located at the angle in step ⑦, calculate the vertical installation deviation angle. As shown in the following formula:

[0050]

[0051] In the formula, This represents the roll angle of the MEMS inertial navigation system when transitioning from the b-frame to the B-frame at the current position.

[0052] When the biaxial frame angle is located at the angle in step ⑧, the horizontal installation deviation angle after calculating the compensation reference plane deviation angle is as follows:

[0053]

[0054] Then, based on the rotation matrix of the MEMS inertial navigation system between the B-frame and the b-frame... The installation deviation angle under the B-series is converted to the b-series as follows:

[0055]

[0056] In the formula, θ b For the pitch installation deviation angle of the b-series, γ b For the B-series lower roll installation deviation angle, The installation deviation angle for the lower position of the b-series; θ B For the B-series pitch installation deviation angle, γ B For the B-series lower roll installation deviation angle, The deviation angle is installed at the lower position of the B series.

[0057] (3) After completing the 8-position rotation during the calibration phase, the MEMS inertial navigation system enters the calibration self-test state. The gyroscope zero-drift estimate can be obtained through step (2). Accelerometer bias estimation Accelerometer scale factor estimation Installation deviation angle θ after deviation angle from datum plane b γ b , The MEMS inertial navigation system performs realignment and compensates for the above error terms, as shown in the following formula:

[0058]

[0059] In the formula, I is the identity matrix, and (φ×) is the matrix formed by θ. b γ b , The antisymmetric array formed.

[0060] After instrument error compensation and installation deviation angle compensation, the inertial navigation attitude and azimuth angle are recalculated and the angle is tested, i.e., the calibration self-test process is executed, see step (4).

[0061] (4) During the self-test of MEMS inertial navigation calibration, the dual-frame rotation is fed back to the pod to assist the pod in performing five position rotations during the testing phase, and the correctness of the calibration parameters is detected during the rotation.

[0062] The dual-axis frame target rotation of the pod is fed back by MEMS inertial navigation. The five rotation sequences during the calibration self-test phase are as follows: initial zero position -> (azimuth 180°, pitch 0°) -> (azimuth 0°, pitch 0°) -> (azimuth 0°, pitch -90°) -> (azimuth 0°, pitch 0°).

[0063] Calibration self-test procedure reference Figure 2 Middle step 9~ The remaining error after deducting the reference plane deviation angle from the MEMS inertial navigation attitude angle at each position is calculated. If the error does not exceed 0.1°, the calibration is complete; otherwise, the calibration fails.

[0064] Example:

[0065] The present invention will be described in detail below through specific embodiments.

[0066] Taking a MEMS inertial navigation calibration process as an example, the application of the method of the present invention will be explained. Before the test, the horizontal deflection angle of the reference plane was measured to be approximately 0.26° and -0.08° using a level.

[0067] (1) The pod sends calibration commands, satellite navigation information and dual-axis frame angles to the MEMS inertial navigation system through the communication interface.

[0068] (2) During the MEMS inertial navigation self-calibration process, the dual-frame rotation is fed back to the pod to assist the dual-axis pod in performing 8-position rotation during the calibration phase (during the rotation, the angle of the dual-axis frame is as follows). Figure 3 (a) During the rotation process, the MEMS inertial navigation system estimates the instrument error, installation deviation angle, and reference plane deviation angle.

[0069] During rotation, the MEMS inertial navigation system estimates the gyroscope zero drift, accelerometer zero bias, and accelerometer scale factor as follows: Figure 4 As shown, the estimated gyroscope zero drift is accelerometer zero bias accelerometer scale factor is

[0070] Measurements obtained during the rotation process The calculated deviation angle of the datum plane is: The installation deviation angle, which is basically consistent with the reference surface deviation angle measured before the test, is thus obtained as θ, which compensates for the reference surface deviation angle. b =0.0064°,γ b = -0.0017°,

[0071] (3) After completing the 8-position rotation during the calibration phase, the MEMS inertial navigation system enters the calibration self-test state.

[0072] (4) During the MEMS inertial navigation calibration self-test, the dual-frame rotation is fed back to the pod to assist the pod in performing a 5-position rotation during the testing phase (the angle of the dual-axis frame during the rotation is as follows). Figure 3 (b) During the rotation process, the correctness of the calibration parameters is checked. After a self-check process, and realignment using instrument information that compensates for the above errors, the remaining attitude deviation is: All values ​​are less than 0.1°, calibration complete.

[0073] (5) After the MEMS inertial navigation calibration self-test is completed, the calibration status is fed back and the calibration results are stored.

[0074] The contents not described in detail in this specification are common knowledge to those skilled in the art.

[0075] Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solutions of the present invention by utilizing the methods and techniques disclosed above without departing from the spirit and scope of the present invention. Therefore, any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solutions of the present invention shall fall within the protection scope of the technical solutions of the present invention.

Claims

1. A MEMS inertial navigation self-calibration method based on multi-position rotation of a dual-axis pod, characterized in that, include: (1) The pod sends calibration commands, satellite navigation information and dual-axis frame angles to the MEMS inertial navigation system through the communication interface; (2) During the self-calibration process, the MEMS inertial navigation system feeds back the dual-frame rotation to the pod, assisting the dual-axis pod in performing 8-position rotation during the calibration phase. During the rotation, the MEMS inertial navigation system estimates the instrument error, installation deviation angle, and reference plane deviation angle. The 8 rotation sequences during the calibration phase are as follows: initial zero position -> (azimuth 90°, pitch 0°) -> (azimuth 90°, pitch -90°) -> (azimuth 0°, pitch -90°) -> (azimuth 0°, pitch 0°) -> (azimuth 180°, pitch -9 ... (0° pitch) -> (0° azimuth, 0° elevation) -> (0° azimuth, -90° elevation) -> (0° azimuth, 0° elevation); The MEMS inertial navigation instrument error is estimated by establishing a feedback correction Kalman filter model with 19-dimensional state variables and 7-dimensional observation variables; among which, the state variables are selected as 3-dimensional attitude error, 3-dimensional velocity error, 3-dimensional position error, 3-dimensional gyroscope zero drift, 3-dimensional accelerometer zero bias, 3-dimensional accelerometer scale factor, and heading deviation angle, and the observation variables are selected as velocity, position, and reference heading; The eastward speed, northward speed, celestial speed, latitude, longitude, altitude, and reference heading are used as observations; When the biaxial frame angle is at 180 degrees azimuth and 0 degrees pitch, the installation deviation angle is calculated using the following formula. and : In the formula, For the base coordinate system; For MEMS inertial navigation System conversion to The horizontal attitude angle under the system; For MEMS inertial navigation System conversion to The horizontal attitude angle under the system; Used as a reference attitude angle; The reference plane deviation angle; When the biaxial frame angle is at 0 degrees azimuth and 0 degrees pitch, the following formula is used for calculation. : When the biaxial frame angle is at 0 degrees azimuth and -90 degrees pitch, the following vertical installation deviation angle is used. : In the formula, For the current position of the MEMS inertial navigation system System conversion to Roll angle under the system; When the biaxial frame angle is at 0 degrees azimuth and 0 degrees pitch, the horizontal installation deviation angle after calculating the compensation reference plane deviation angle is as follows: Then, based on MEMS inertial navigation... System conversion to Rotation matrix between systems Will Installation deviation angle conversion under system The following formula is used: In the formula, for Pitch deviation angle for Lower roll installation deviation angle, for The installation deviation angle is at the lower position; for Pitch deviation angle for Lower roll installation deviation angle, for The installation deviation angle is at the lower position; (3) After completing the 8-position rotation during the calibration phase, the MEMS inertial navigation system enters the calibration self-test state; (4) During the self-test of MEMS inertial navigation calibration, the double frame rotation is fed back to the pod to assist the pod in performing the 5-position rotation during the detection phase, and the correctness of the calibration parameters is detected during the rotation. (5) After the MEMS inertial navigation calibration self-test is completed, the calibration status is fed back and the calibration results are stored.

2. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, The communication interface can be any one of RS232 serial port, RS422 serial port, RS485 serial port, or CAN bus.

3. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, The satellite navigation information includes geographic speed and location information.

4. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, The dual-axis frame angles include the pod pitch axis angle and the azimuth axis angle.

5. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, MEMS inertial navigation is an inertial measurement unit that uses a three-axis microelectromechanical gyroscope and a three-axis microelectromechanical accelerometer as sensors, is installed inside the pod, and can rotate with the pod.

6. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, As the MEMS inertial navigation system rotates with the pod, the pod's azimuth axis corresponds to the MEMS inertial navigation azimuth axis, and the pod's pitch axis corresponds to the MEMS inertial navigation roll axis.

7. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, The instrument errors are the three-axis gyroscope zero drift, the three-axis accelerometer zero bias, and the scale factor. The installation deviation angle is the deviation angle between the MEMS inertial navigation system and the horizontal and normal planes where the pod's optical axis is located. The reference plane deviation angle is the deviation angle between the pod's optical axis and the geoid.

8. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, The five rotation sequences in the calibration self-test phase are as follows: initial zero position -> (azimuth 180°, pitch 0°) -> (azimuth 0°, pitch 0°) -> (azimuth 0°, pitch -90°) -> (azimuth 0°, pitch 0°).

9. The MEMS inertial navigation self-calibration method according to claim 1, characterized in that, During the calibration self-test, the calibration is completed when the remaining error after deducting the reference plane deviation angle from the MEMS inertial navigation attitude angle at each position does not exceed 0.1°.

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