CN114322998A - SINS _ OD combined navigation correction method based on lever arm estimation - Google Patents
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Abstract
The SINS _ OD combined navigation correction method based on the lever arm estimation comprises the steps of measuring a real lever arm value of SINS _ OD combined navigation, and taking the real lever arm value as a lever arm correction reference value of the SINS _ OD combined navigation; synchronously acquiring IMU data and OD data, and selecting a state variable of SINS _ OD combined navigation; establishing a Kalman filtering equation and a measurement equation according to the state variables; inputting the lever arm value of the SINS _ OD combined navigation measured in real time into a Kalman filtering equation and a measurement equation to obtain a lever arm estimation value; and when the error between the lever arm estimation value and the lever arm correction reference value is in a preset range and the variance between the installation deviation angle of the SINS system and the OD and the scale coefficient estimation error of the OD is smaller than a preset threshold value, carrying out feedback correction on the installation deviation angle and the scale coefficient estimation error, and carrying out SINS _ OD combined navigation by adopting the corrected installation deviation angle and scale coefficient error. The method can estimate the installation deviation angle between the SINS _ OD and the scale coefficient error of the OD on line, correct the errors and improve the precision of SINS _ OD combined navigation.
Description
Technical Field
The invention belongs to the technical field of inertial navigation, and particularly relates to a lever arm estimation-based SINS _ OD combined navigation correction method.
Background
The Strapdown Inertial Navigation System (SINS) can provide information including attitude, speed, position, acceleration, angular velocity and the like through navigation calculation of a navigation computer by utilizing the output of a gyroscope and an accelerometer, and has the advantages of strong autonomy, good dynamic performance, comprehensive navigation information and high output frequency, but in practice, an inertial device has certain error, and the navigation error is accumulated along with time and cannot work independently for a long time. The GNSS has wide positioning range and high precision, but is easy to generate signal shielding and signal interference and is easy to cheat, and the GNSS navigation in sensitive areas is unreliable due to the fact that the GNSS is relied on. The Odometer (OD) is similar to a Strapdown Inertial Navigation System (SINS), and has the characteristics of complete autonomy and no error accumulation over time, but the update frequency is low and the noise is large. Under the condition that the GNSS cannot be received due to shielding or is unreliable due to interference, an SINS _ OD integrated navigation system is constructed, various errors of the integrated navigation system are estimated by adopting a mature Kalman filter, and the attitude, speed and position errors of the system are corrected by using error state estimation, so that long-time autonomous positioning navigation can be realized.
Before SINS _ OD combined navigation, a track similarity principle is usually adopted, starting point coordinates, target point coordinates and driving mileage are accurately known through GNSS, the target point is located through the combined navigation, course deviation, pitching deviation and scale coefficient errors of an Odometer (OD) between a Strapdown Inertial Navigation System (SINS) and the Odometer (OD) are calibrated, and the system is written after one-time calibration is completed. However, when the vehicle is running, the pitching and course installation error angles can be changed due to shaking interference, the odometer scale error coefficients can be changed due to deformation caused by load change, abrasion with the ground and difference of running speed in the use process of the tire, and if the positioning error is not estimated and corrected in real time, the positioning error is increased more than ideal.
Disclosure of Invention
The invention overcomes one of the defects of the prior art, and provides a lever arm estimation-based SINS _ OD combined navigation correction method, which can estimate the installation deviation angle between SINS _ ODs and the scale coefficient error of the ODs on line on the basis of calibrating the installation error between the SINS _ ODs and the scale coefficient error of the ODs by using the lever arm once, correct the installation deviation angle between the SINS _ ODs and the scale coefficient error of the ODs, and further improve the precision of SINS _ OD combined navigation.
According to an aspect of the disclosure, the present invention provides a method for correcting SINS _ OD integrated navigation based on lever arm estimation, the method comprising:
step S1: measuring a real lever arm value of the SINS _ OD combined navigation, and taking the real lever arm value as a lever arm correction reference value of the SINS _ OD combined navigation;
step S2: initializing the SINS _ OD combined navigation, synchronously acquiring IMU data and OD data, and selecting a state variable of the SINS _ OD combined navigation;
step S3: establishing a Kalman filtering equation and a measurement equation according to the state variables of the SINS _ OD integrated navigation;
step S4: inputting the lever arm value of the SINS _ OD combined navigation measured in real time into the Kalman filtering equation and the measurement equation to obtain a lever arm estimation value of the SINS _ OD combined navigation;
step S5: and when the error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is in a preset range, and the variance between the installation deviation angle of the SINS and the OD and the scale coefficient estimation error of the OD is smaller than a preset threshold value, carrying out feedback correction on the installation deviation angle of the SINS system and the OD and the scale coefficient estimation error of the OD, and carrying out SINS _ OD combined navigation by adopting the corrected installation deviation angle of the SINS and the OD and the scale coefficient error of the OD.
In one possible implementation, the real lever arm value is a real lever arm value between the SINS system and the OD.
In a possible implementation manner, the state variables of the SINS _ OD combined navigation are:
wherein phi isTRepresenting east, north, and sky misalignment angle errors, δ v, in SINS _ OD combined navigational misalignment angle errornRepresenting the east-direction speed error, the north-direction speed error and the sky-direction speed error in the SINS _ OD combined navigation speed error; δ p represents latitude error, longitude error and altitude error in SINS _ OD combined navigation position error; δ pDRepresenting latitude error, longitude error and altitude error of SINS _ OD combined navigation dead reckoning; epsilonbRepresenting the random constant drift of an x-axis gyroscope, a y-axis gyroscope and a z-axis gyroscope of the SINS _ OD combined navigation;
representing random constant zero offset of an x-axis accelerometer, a y-axis accelerometer and a z-axis accelerometer of the SINS _ OD combined navigation; xiOD＝[δθ δψ δkOD]Respectively representing the pitch, course installation deviation angle and scale coefficient error of the SINS _ OD combined navigation; delta lbRepresenting lever arms in three directions between the SINS system and the OD.
In one possible implementation, the Kalman filter equation
Wherein X is a system error state variable, W is a system noise variable, F is a system state transition matrix, and G is a system noise transition matrix;
the measurement equation Z ═ HX + V, where Z is the measurement vector, H is the measurement matrix, and V is the measurement noise vector.
In a possible implementation manner, while performing SINS _ OD combined navigation by using the corrected installation deviation angle of the SINS and the OD and the calibration coefficient error of the OD, setting the installation deviation angle of the SINS and the OD, the calibration coefficient error of the OD, and the lever arm estimation value as initial values of the SINS _ OD combined navigation, setting a corresponding state variable to zero, performing kalman filtering, and when an error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is within a preset range, and a variance between the installation deviation angle of the SINS and the OD and the calibration coefficient estimation error of the OD is smaller than a preset threshold, repeating the above steps S1-S5.
The SINS _ OD combined navigation correction method measures the real lever arm value of SINS _ OD combined navigation, and takes the real lever arm value as the lever arm correction reference value of the SINS _ OD combined navigation; initializing SINS _ OD combined navigation, synchronously acquiring IMU data and OD data, and selecting a state variable of the SINS _ OD combined navigation; establishing a Kalman filtering equation and a measurement equation according to the state variables of the SINS _ OD integrated navigation; inputting the lever arm value of the SINS _ OD combined navigation measured in real time into the Kalman filtering equation and the measurement equation to obtain a lever arm estimation value of the SINS _ OD combined navigation; and when the error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is in a preset range, and the mounting deviation angle between the SINS system and the OD and the scale coefficient estimation error variance of the OD are smaller than a preset threshold value, carrying out feedback correction on the mounting deviation angle between the SINS system and the OD and the scale coefficient estimation error of the OD, and carrying out the SINS _ OD combined navigation by adopting the corrected mounting deviation angle between the SINS system and the OD and the scale coefficient error of the OD. The method can estimate the installation deviation angle between the SINS _ ODs and the scale coefficient error of the ODs on line on the basis of calibrating the installation error between the SINS _ ODs and the scale coefficient error of the ODs by using the lever arm once, correct the installation deviation angle between the SINS _ ODs and the scale coefficient error of the ODs, and further improve the precision of SINS _ OD combined navigation.
Drawings
The accompanying drawings are included to provide a further understanding of the technology or prior art of the present application and are incorporated in and constitute a part of this specification. The drawings expressing the embodiments of the present application are used for explaining the technical solutions of the present application, and should not be construed as limiting the technical solutions of the present application.
Fig. 1 shows a flowchart of a method for correcting SINS _ OD combined navigation based on lever arm estimation according to an embodiment of the present disclosure;
FIG. 2 shows the pitch angle, setup offset angle, and estimated values of SINS _ OD integrated navigation based on boom arm estimation according to an embodiment of the present disclosure;
FIG. 3 shows a set value and an estimated value of the OD scale factor of the SINS _ OD combined navigation based on the lever arm estimation according to an embodiment of the present disclosure;
FIG. 4 illustrates standard deviation of estimated errors for pitch angle, mount offset angle for SINS _ OD integrated navigation based on boom arm estimation according to an embodiment of the present disclosure;
fig. 5 shows the standard deviation of the estimated error of the OD scale coefficients of the SINS _ OD combined navigation based on the boom arm estimation according to an embodiment of the present disclosure.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the accompanying drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the corresponding technical effects can be fully understood and implemented. The embodiments and the features of the embodiments can be combined without conflict, and the technical solutions formed are all within the scope of the present invention.
Fig. 1 shows a flowchart of a method for correcting SINS _ OD combined navigation based on lever arm estimation according to an embodiment of the present disclosure. As shown in fig. 1, the method may include:
step S1: and measuring the real lever arm value of the SINS _ OD combined navigation, and taking the real lever arm value as a lever arm correction reference value of the SINS _ OD combined navigation.
Step S2: initializing SINS _ OD combined navigation, synchronously acquiring IMU data and OD data, and selecting a state variable of the SINS _ OD combined navigation.
Before navigation, firstly, a real lever arm value between a Strapdown Inertial Navigation System (SINS) and an Odometer (OD) in an SINS _ OD combined navigation system is accurately measured, the real lever arm value is not changed under the condition that the SINS _ OD combined navigation system is fixed, and the real lever arm value can be used as a known reference value. After the SINS _ OD combined navigation system is powered on and started, initial alignment is firstly realized, and IMU data and OD data are synchronously acquired for combined navigation after the alignment is finished.
In SINS _ OD integrated navigation, according to the error characteristics of a Strapdown Inertial Navigation (SINS) navigation system in long-term operation, attitude error, speed error, position error, gyro drift, accelerometer zero offset, odometer and lever arm are selected as state variables of the SINS _ OD integrated navigation system, namely:
wherein phi isTRepresenting east, north, and sky misalignment angle errors, δ v, of inertial navigation misalignment angle errorsnRepresenting the inertial navigation speed error, namely an east speed error, a north speed error and a sky speed error; δ p represents latitude error, longitude error and altitude error in inertial navigation position error; δ pDLatitude error, longitude error and altitude error representing dead reckoning; epsilonbRepresents the random constant drift of the x-axis gyroscope, the y-axis gyroscope and the z-axis gyroscope;
representing a random constant zero offset for the x-axis accelerometer, the y-axis accelerometer, and the z-axis accelerometer; xiOD＝[δθ δψ δkOD]Respectively representing the errors of the pitching and course installation deviation angles and the scale coefficients; delta lbRepresenting lever arms in three directions between the SINS and OD.
Step S3: and establishing a Kalman filtering equation and a measurement equation according to the state variables of the SINS _ OD integrated navigation.
In one example, Kalman Filter equations
Wherein, X is a system error state variable, W is a system noise variable, F is a system state transition matrix, and G is a system noise transition matrix.
The measurement equation Z is HX + V, where Z is the measurement vector, H is the measurement matrix, and V is the measurement noise vector.
Step S4: and inputting the lever arm value of the SINS _ OD combined navigation measured in real time into a Kalman filtering equation and a measurement equation to obtain a lever arm estimation value of the SINS _ OD combined navigation.
Step S5: and when the error between the lever arm estimation value of SINS _ OD combined navigation and the lever arm correction reference value is in a preset range, and the variance between the installation deviation angle of the SINS system and the OD and the scale coefficient estimation error of the OD is smaller than a preset threshold value, carrying out feedback correction on the installation deviation angle of the SINS system and the OD and the scale coefficient estimation error of the OD, and carrying out SINS _ OD combined navigation by adopting the corrected installation deviation angle of the SINS and the OD and the scale coefficient error of the OD.
According to observability analysis, the observability degree of the installation deviation angle and the OD scale coefficient error between an SINS system and an OD of SINS _ OD combined navigation is larger than the observability degree of a lever arm, so that in the combined navigation process, when the error between the lever arm estimation value and the actual value of the SINS to the OD reaches a set threshold range and the variance of the installation deviation angle and the scale coefficient estimation error is smaller than a set threshold, the installation deviation angle and the OD scale coefficient between the SINS and the OD are considered to be accurately estimated, the installation deviation angle and the OD scale coefficient error between the SINS and the OD can be subjected to feedback correction, and new installation deviation angle and OD scale coefficient error between the SINS and the OD after correction are adopted for combined navigation. At the moment, resetting the installation deviation angle between the SINS and the OD, OD scale coefficient errors and the estimation error variance of the errors of the three lever arms as initial values, clearing the corresponding state variables, continuing filtering, and repeating the operations when the estimated value of the lever arm is close to the true value again and the corresponding state variables are converged, thereby realizing SINS _ OD combined navigation correction and SINS _ OD combined navigation based on the lever arm estimation.
Fig. 2 and 3 show the pitch angle, installation offset angle, OD index setting and estimation values of the SINS _ OD integrated navigation based on lever arm estimation according to an embodiment of the present disclosure, respectively; fig. 4 and 5 show the pitch angle, the installation offset angle, and the standard deviation of the estimated error of the OD scale factor of the SINS _ OD integrated navigation based on the lever arm estimation according to an embodiment of the present disclosure, respectively.
As shown in fig. 2-5, the pitch angle, the installation deviation angle (course installation deviation) and the set value, the estimated value and the standard deviation of the estimated error of the OD scale coefficient error state variable of the navigation are combined by generating the trajectory simulation SINS _ OD. It can be seen that when the estimated value and the measured value of the arm of the SINS _ OD integrated navigation lever are close, the deviation error and the scale coefficient error of the pitch angle, the installation deviation angle in fig. 4 and fig. 5 are all converged, and as can be seen from fig. 2 and fig. 3, the estimation accuracy of the pitch angle, the installation deviation angle and the OD scale coefficient error all reach 90%, and the accuracy of the SINS _ OD integrated navigation is improved.
The SINS _ OD combined navigation correction method measures the real lever arm value of SINS _ OD combined navigation, and takes the real lever arm value as the lever arm correction reference value of the SINS _ OD combined navigation; initializing SINS _ OD combined navigation, synchronously acquiring IMU data and OD data, and selecting a state variable of the SINS _ OD combined navigation; establishing a Kalman filtering equation and a measurement equation according to the state variables of the SINS _ OD integrated navigation; inputting the lever arm value of the SINS _ OD combined navigation measured in real time into the Kalman filtering equation and the measurement equation to obtain a lever arm estimation value of the SINS _ OD combined navigation; and when the error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is in a preset range, and the mounting deviation angle between the SINS system and the OD and the scale coefficient estimation error variance of the OD are smaller than a preset threshold value, carrying out feedback correction on the mounting deviation angle between the SINS system and the OD and the scale coefficient estimation error of the OD, and carrying out the SINS _ OD combined navigation by adopting the corrected mounting deviation angle between the SINS system and the OD and the scale coefficient error of the OD. The method can estimate the installation deviation angle between the SINS _ ODs and the scale coefficient error of the ODs on line on the basis of calibrating the installation error between the SINS _ ODs and the scale coefficient error of the ODs by using the lever arm once, correct the installation deviation angle between the SINS _ ODs and the scale coefficient error of the ODs, and further improve the precision of SINS _ OD combined navigation.
Although the embodiments of the present invention have been described above, the above descriptions are only for the convenience of understanding the present invention, and are not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. A SINS _ OD combined navigation correction method based on lever arm estimation is characterized by comprising the following steps:
step S1: measuring a real lever arm value of the SINS _ OD combined navigation, and taking the real lever arm value as a lever arm correction reference value of the SINS _ OD combined navigation;
step S2: initializing the SINS _ OD combined navigation, synchronously acquiring IMU data and OD data, and selecting a state variable of the SINS _ OD combined navigation;
step S3: establishing a Kalman filtering equation and a measurement equation according to the state variables of the SINS _ OD integrated navigation;
step S4: inputting the lever arm value of the SINS _ OD combined navigation measured in real time into the Kalman filtering equation and the measurement equation to obtain a lever arm estimation value of the SINS _ OD combined navigation;
step S5: and when the error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is in a preset range, and the variance between the installation deviation angle of the SINS and the OD and the scale coefficient estimation error of the OD is smaller than a preset threshold value, carrying out feedback correction on the installation deviation angle of the SINS system and the OD and the scale coefficient estimation error of the OD, and carrying out SINS _ OD combined navigation by adopting the corrected installation deviation angle of the SINS and the OD and the scale coefficient error of the OD.
2. The method of claim 1, wherein the true lever arm value is a true lever arm value between the SINS system and the OD.
3. The method of claim 1, wherein the state variables of the SINS _ OD combined navigation are:
wherein phi isTRepresenting east, north, and sky misalignment angle errors, δ v, in SINS _ OD combined navigational misalignment angle errornRepresenting the east-direction speed error, the north-direction speed error and the sky-direction speed error in the SINS _ OD combined navigation speed error; δ p represents latitude error, longitude error and altitude error in SINS _ OD combined navigation position error; δ pDRepresenting latitude error, longitude error and altitude error of SINS _ OD combined navigation dead reckoning; epsilonbRepresenting the random constant drift of an x-axis gyroscope, a y-axis gyroscope and a z-axis gyroscope of the SINS _ OD combined navigation;
representing random constant zero offset of an x-axis accelerometer, a y-axis accelerometer and a z-axis accelerometer of the SINS _ OD combined navigation; xiOD＝[δθ δψ δkOD]Respectively representing the pitch, course installation deviation angle and scale coefficient error of the SINS _ OD combined navigation; delta lbRepresenting lever arms in three directions between the SINS system and the OD.
4. The SINS _ OD combined navigation correction method of claim 3, wherein the Kalman filter equation
Wherein X is a system error state variable, W is a system noise variable, F is a system state transition matrix, and G is a system noise transition matrix;
the measurement equation Z ═ HX + V, where Z is the measurement vector, H is the measurement matrix, and V is the measurement noise vector.
5. The method of claim 1, wherein the step S1-S5 is repeated when the corrected installation deviation angle of the SINS and the OD and the calibration coefficient error of the OD are used for SINS _ OD combined navigation, the installation deviation angle of the SINS and the OD, the calibration coefficient error of the OD and the lever arm estimation value are used as initial values of the SINS _ OD combined navigation, the corresponding state variables are set to zero, kalman filtering is performed, and when the error between the lever arm estimation value of the SINS _ OD combined navigation and the lever arm correction reference value is within a preset range and the variance between the installation deviation angle of the SINS and the OD and the calibration coefficient estimation error of the OD is smaller than a preset threshold.
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