CN110057383B - Lever arm error calibration method of AUV (autonomous Underwater vehicle) push navigation system - Google Patents
Lever arm error calibration method of AUV (autonomous Underwater vehicle) push navigation system Download PDFInfo
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Abstract
The invention relates to a lever arm error calibration method of an AUV (autonomous underwater vehicle) push navigation system, belonging to the field of underwater vehicles. Aiming at calibrating a lever arm error generated by a Doppler Velocity sonar (DVL) not being installed at an AUV mass center together with an AHRS (Attitude and Heading Reference System) in an AUV positioning navigation System, an error calibration model suitable for a Kalman filtering algorithm is constructed, and the length of the lever arm is identified by adopting a simple and feasible rotary motion mode. The method has the advantages that the requirement on inertial base navigation equipment is reduced because the AHRS is not required to provide heave information, the scheme has good universality, the method is suitable for solving the problem of lever arm length identification of various AUVs, and the positioning accuracy of the AUV positioning navigation system can be effectively improved through compensation of lever arm errors in the AUV positioning navigation system; meanwhile, the scheme can be directly obtained, the DVL, the AHRS and the center of mass (or the floating center) are not required to be positioned on the same straight line, namely, the corresponding lever arm length can be directly obtained no matter where the center of mass (the floating center) of the AUV is positioned, and the application prospect is wide.
Description
Technical Field
The invention relates to an AUV (Autonomous Underwater Vehicle) push navigation system lever arm error calibration method, belonging to the field of Underwater vehicles.
Background
An underwater locating navigation system composed of a DVL and an AHRS is an autonomous underwater navigation method commonly used by an AUV (autonomous underwater vehicle), wherein the DVL is theoretically installed on a rotation center of the AUV, but is limited by an AUV space, the DVL is usually far away from the rotation center of the AUV, a lever arm error exists, and the positioning accuracy of the locating navigation system is greatly influenced.
The invention designs a calibration method for lever arm errors of an AUV (autonomous Underwater vehicle) push navigation system, which improves the positioning accuracy of the AUV push navigation system by compensating the lever arm errors of the push navigation system.
A paper entitled "application and design of an H ∞ filter in compensation of the arm effect" published as 11/2009, employs H ∞ filtering to improve the accuracy of transfer alignment in the presence of flexural deformations in the length of the arm. However, the method needs the assistance of a high-precision inertial navigation system, the AUV generally adopts a low-cost commercial inertial unit, the length of the AUV hull is short, and the influence of deflection deformation on the error estimation of the lever arm is very small.
In the paper entitled "alignment lever arm error compensation algorithm between carrier advances" published in 2019, the length of a lever arm is measured by adopting a mechanical equation method, the lever arm is combined with an error model of a system to construct a Kalman state measurement equation, and the lever arm error identification of an inertial navigation system is realized by a 5-order CKF algorithm. However, the method is relatively large in calculated amount, high in requirement on the precision of the inertial element and not suitable for on-line arm lever error identification of the AUV position-pushing navigation system based on the low-cost commercial inertial unit.
Disclosure of Invention
The invention aims to solve the problem of lever arm error calibration in an AUV (autonomous underwater vehicle) positioning navigation system, and provides a lever arm error calibration method for the AUV positioning navigation system.
The invention aims to realize the calibration method of the lever arm error of the AUV (autonomous Underwater vehicle) push navigation system, which specifically comprises the following steps:
step 1, determining the motion mode of the AUV as rotary motion;
step 2, analyzing the system of the AUV rotary motion according to the characteristics of the AUV rotary motion, and constructing a lever arm error model suitable for a Kalman filtering algorithm;
step 3, determining system state quantity and observation quantity, constructing a state equation and an observation equation, and performing optimal estimation on the lever arm length of the AUV according to Kalman filtering;
and 4, calibrating positioning errors of the positioning navigation system caused by the lever arm effect according to the optimal estimation of the length of the AUV lever arm.
The invention also includes such structural features:
a lever arm error calibration method of an AUV (autonomous Underwater vehicle) push navigation system comprises the following steps in step 1:
step 1.1, DVL on AUV is positioned at the bow, and origin o of AUV carrying system b b Coincident with AUV centroid, x b The axis points to the bow direction of the boat b Axis perpendicular to x b Axis pointing in starboard direction, z b Axis perpendicular to x b -y b Plane, downward satisfying right hand rule, R CA The DVL mounting point is the distance from the center of mass under the carrier system, and the lever arm length vector is
A lever arm error is present;
step 1.2, when the AUV navigates underwater, angular motion can be generated,
output value of DVL in carrier coordinate system for point A, V bx At the point speed of A line
Along a carrier coordinate system x b Component of the axis, V by At the point speed of A line
Along the carrier coordinate system y b Component of the axis, ω bx ，ω by ，ω bz Angular velocities at points A, respectively
Projection components in the carrier coordinate system;
step 1.3, origin o of azimuth follow-up horizontal coordinate system b b′ Coincident with the origin of the vector system b, x b′ The axial direction is consistent with the AUV heading and is y b′ Form a local horizontal coordinate system, z b′ The axis is vertical downwards, and the three meet the right-hand rule;
step 1.4, R is the radius of the rotation motion of the AUV in the azimuth follow-up coordinate system, the rotation motion direction of the AUV and z b′ The coordinate of the rotation radius under the azimuth follow-up horizontal coordinate system is
And z b′ Shaft counter-clockwise rotationThe rotation time is negative, and the rotation radius is the coordinate under the azimuth follow-up horizontal coordinate system
Gamma is the roll angle of AUV movement, and theta is the pitch angle of AUV movement.
A lever arm error calibration method of an AUV (autonomous Underwater vehicle) push navigation system comprises the following steps in step 2:
and 2.1, analyzing the rotary motion system, wherein when the AUV does not have rolling and pitching motions, the linear speed at the C point of the carrier coordinate system is as follows:
while
So under the carrier coordinate system
Under the carrier system, the lever arm coordinate along the positive direction of the transverse rolling shaft of the carrier system of the AUV is
Linear velocity error under the carrier system at point a
Is composed of
Step 2.2, analyzing the rotary motion system, wherein pitching and rolling motions exist when the AUV does rotary motion, so that the rotary linear velocity of the AUV in the carrier coordinate system b is
Wherein
Arranged under an orientation follow-up horizontal coordinate system R DC Has the coordinates of
The rotational linear velocity of AUV under the carrier system is
And also
The output value of the DVL, i.e., the a-point velocity, is thus expressed as:
and the carrier system is b below R CA The coordinates of (a) are:
namely, it is
To obtain
Suppose that:
to obtain
A lever arm error calibration method of an AUV (autonomous Underwater vehicle) push navigation system comprises the following steps in step 3:
step 3.1 Lever arm Length
With [ R ] CA V by ] T And establishing a Kalman filtering equation as a state variable of the system, wherein the state equation is as follows:
w is white Gaussian noise satisfying a zero-mean normal distribution, and the observation equation is
v is white gaussian noise satisfying a zero-mean normal distribution;
step 3.2, carrying out lever arm length R in the AUV positioning navigation system according to Kalman filtering CA And carrying out optimal estimation.
A lever arm error calibration method of an AUV (autonomous Underwater vehicle) push navigation system, wherein the step 4 specifically comprises the following steps:
step 4.1, obtaining the lever arm length R from step 3 CA To obtain the speed error at point A
Step 4.2, according to
The velocity of the point A is obtained
By compensating for speed error at point A
Obtaining the speed of C point line
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the lever arm error between the DVL installation position and the AUV rotation central point in the underwater locating navigation system can be effectively identified by constructing the error calibration model suitable for the Kalman filtering algorithm, and the locating precision of the underwater locating navigation system is improved. The invention adopts a rotary motion mode to identify the length of the lever arm, and the scheme is simple and easy to implement; the heave information is not required to be provided by an AHRS (attitude and heading reference system), the requirement on inertial-based navigation equipment is reduced, the scheme is good in universality and suitable for solving the problem of lever arm length identification of various AUVs (autonomous underwater vehicles); meanwhile, the scheme can be directly obtained, the DVL, the AHRS and the center of mass (or the floating center) are not required to be positioned on the same straight line, namely the corresponding lever arm length can be directly obtained no matter where the center of mass (the floating center) of the AUV is positioned.
Drawings
FIG. 1 is a general flow chart of calibration of lever arm error of the AUV push navigation system;
FIG. 2 is a projection of the radius of rotation under the hull;
FIG. 3 is a schematic diagram of the velocity at different points of the AUV in the slewing motion;
FIG. 4 is a graphical illustration of the constant velocity error of the AUV, i.e., the lever arm error;
FIG. 5 is a schematic diagram of the DVL, AHRS and centroid not being collinear;
FIG. 6 is a simulation result of lever arm length estimation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The invention relates to the field of underwater autonomous navigation, and provides a lever arm error calibration method suitable for an AUV (autonomous underwater vehicle) positioning navigation system. Aiming at the lever arm error generated by a Doppler Velocity sonar (DVL) not being installed at an AUV mass center together with an Attitude and Heading Reference System (AHRS) in an AUV positioning navigation System, an error calibration model suitable for a Kalman filtering algorithm is constructed, and the length of the lever arm is identified by adopting a simple and easy rotary motion mode. The method has the advantages that the AHRS is not needed to provide heaving information, the requirement on inertial base navigation equipment is reduced, the scheme universality is good, the method is suitable for solving the problem of lever arm length identification of various AUVs, and the positioning accuracy of the AUV positioning navigation system can be effectively improved by compensating the error of the lever arm in the AUV positioning navigation system.
Embodiment mode 1: the method for calibrating the lever arm error of the AUV positioning navigation system in the embodiment comprises the following steps:
(1) According to the cause of the lever arm error of the AUV push navigation system shown in FIG. 4, the DVL on the AUV is positioned at the bow, the installation position is far away from the rotation center of the AUV, and the lever arm error exists. When the AUV navigates underwater, angular motion cannot be avoided, and the DVL senses the linear speed on a circle with the rotation center as the origin and the distance from the mounting point to the rotation center as the radius, so that a navigation system of the AUV generates a constant speed error and a constant speed error; determining the motion mode of the AUV as rotary motion, and calibrating the lever arm error of the AUV pushing navigation system;
(2) Analyzing a system for performing rotary motion on the AUV; when the AUV does the rotary motion, the AUV has the pitching and rolling motions, and the length of the lever arm is determined according to the characteristics of the rotary motion
(3) And constructing an error calibration model suitable for a Kalman filtering algorithm according to the rotary motion system of the AUV. Determining a state equation and an observation equation of the system according to the state quantity and the observed quantity of the system, and establishing a Kalman filtering equation; with [ R ] CA V by ] T And establishing a Kalman filtering equation as a state variable to calibrate a lever arm in the AUV positioning navigation system, wherein the state equation is as follows:
w is white Gaussian noise satisfying a zero-mean normal distribution, and the observation equation is
Wherein v is white gaussian noise satisfying a zero-mean normal distribution;
(4) Optimally estimating the lever arm length of the AUV by a Kalman filtering model, specifically estimating the lever arm length R in an AUV positioning navigation system according to Kalman filtering CA Carrying out optimal estimation;
(5) Calibrating the lever arm error of the AUV positioning navigation system according to the optimal estimation of the length of the lever arm of the AUV, specifically, calibrating the error of the lever arm of the AUV positioning navigation system by using the length R of the lever arm CA Calibrating the lever arm error in the AUV position-pulling navigation system by the optimal estimation;
embodiment mode 2: this embodiment differs from embodiment 1 in that: the step (1) is specifically as follows:
(1.1) origin o of AUV Carrier b, as shown in FIG. 2 b Coincident with AUV centroid, x b The axis points to the bow direction of the boat b Axis perpendicular to x b The shaft is provided with a plurality of axial grooves,pointing in the starboard direction, z b Axis perpendicular to x b -y b A plane, downward meeting right hand rules; r CA The distance from the DVL mounting point to the center of mass under the carrier system is defined as the lever arm length vector
As shown in the figure 3 of the drawings,
the output value of the DVL under the carrier coordinate system is the point A. V bx At the point speed of A line
Along a carrier coordinate system x b Component of the axis, V by Is at the A point line speed
Along the carrier coordinate system y b Component of the axis, ω bx ，ω by ，ω bz Angular velocities at points A, respectively
Projection components in the carrier coordinate system.
(1.2) origin o of azimuth follow-up horizontal coordinate system b b′ Coincident with the origin of the vector system b, x b′ The axial direction is consistent with the AUV heading and is y b′ Constituting a local horizontal coordinate system. z is a radical of b′ The axis is vertical downwards, and the three meet the right-hand rule.
And (1.3) R is the radius of the rotary motion of the orientation following coordinate system AUV. Direction of rotational movement of AUV and z as shown in FIG. 2 b′ The same-direction clockwise rotation of the shaft is positive, and the coordinates of the gyration radius under an azimuth follow-up horizontal coordinate system are as follows:
and z b′ When the shaft rotates anticlockwise in the opposite direction, the rotation radius is negative, and the coordinate of the rotation radius under the azimuth follow-up horizontal coordinate system is as follows:
gamma is a roll angle during AUV motion, and theta is a pitch angle during AUV motion;
embodiment mode 3: this embodiment differs from embodiment 1 in that: the step (2) is specifically as follows:
(2.1) aiming at the rod arm error in the positioning navigation system of the AUV, constructing an error calibration model suitable for a Kalman filtering algorithm to identify the rod arm length by adopting a rotary motion mode of the AUV;
(2.2) when the AUV has no rolling and pitching motion, the linear speed at the C point of the carrier coordinate system is as follows:
and then
So under the carrier coordinate system
As shown in fig. 4, under the carrier system, the coordinates of the lever arm along the positive direction of the carrier system roll axis of the AUV are:
linear velocity error under the carrier system at point a
Comprises the following steps:
(2.3) when the AUV does the rotary motion, the pitch motion and the roll motion exist, and then the rotary linear velocity of the AUV under the carrier coordinate system b is as follows:
wherein
Arranged under an orientation follow-up horizontal coordinate system R DC The coordinates of (a) are:
the rotational linear velocity of AUV under the carrier system is
And also
The output value of the DVL, i.e., the a-point velocity, can thus be expressed as:
and the carrier system is b below R CA The coordinates of (a) are:
namely, it is
To obtain
Suppose that:
to obtain
Embodiment 4: this embodiment differs from embodiment 1 in that: the step (3) is specifically as follows:
(3.1) under the condition that the rolling and pitching are considered when the AUV is used for making the rotary motion, the Kalman filtering method is utilized to carry out optimal estimation on the length of the lever arm;
(3.2) analysis of the AUV motion in accordance with embodiment 2 reveals that the boom arm length is such that the roll and pitch are taken into account
(3.3) with [ R ] CA V by ] T Establishing Kalman filtering equation as state variable of systemThe equation is:
w is white Gaussian noise satisfying a zero-mean normal distribution, and the observation equation is
Where v is white gaussian noise that satisfies a zero-mean normal distribution. The simulation test result is shown in fig. 6, the navigational speed of the AUV is set to 2 knots in a simulation mode, the turning radius is 10 meters, and the lever arm is 2 meters long; the attitude angle accuracy of the AHRS is 0.01 °, the course angle accuracy is 0.2 ° × sec (L), where L is the latitude coordinate of the AUV; the DVL constant error is 0.002m/s, and the dynamic error is +/-0.2%.
(3.4) obtaining the lever arm length R according to a Kalman filtering method CA As shown in fig. 6, the kalman filter state can accurately track the lever arm error, the length of the lever arm after averaging the kalman filter state is estimated to be 2.0214 meters, and the estimation error is 2.14%;
embodiment 5: this embodiment differs from embodiment 1 in that: the step (4) is specifically as follows:
(4.1) Lever arm Length R from embodiment 4 CA Can obtain the optimal estimation value of the speed error at the point A as
(4.2) velocity due to point A
Known according to the formula
By compensating for speed error at point A
Obtaining the speed of C point line
Claims (3)
1. A lever arm error calibration method of an AUV (autonomous Underwater vehicle) push navigation system is characterized by comprising the following steps:
step 1, determining the motion mode of the AUV as rotary motion;
step 1.1, DVL on AUV is positioned at the bow, and origin o of AUV carrying system b b Coincident with AUV centroid, x b The axis points to the bow direction of the boat b Axis perpendicular to x b Axis pointing in starboard direction, z b Axis perpendicular to x b -y b Plane, downward meeting right hand rule, R CA Is the distance from a DVL mounting point to a mass center under a carrier system, and the length vector of a lever arm is
Lever arm error exists;
step 1.2, when the AUV navigates underwater, angular motion can be generated,
output value of DVL for point A in carrier coordinate system, V bx At the point speed of A line
Along a carrier coordinate system x b Component of the axis, V by At the point speed of A line
Along the carrier coordinate system y b Component of the axis, ω bx ，ω by ，ω bz Angular velocities at points A, respectively
Projection components in a carrier coordinate system;
step 1.3, origin o of azimuth follow-up horizontal coordinate system b b′ Coincident with the origin of the vector system b, x b′ The axial direction is consistent with the AUV heading and y b′ Form a local horizontal coordinate system, z b′ The axis is vertical downwards, and the three meet the right-hand rule;
step 1.4, R is the radius of the rotation motion of the AUV in the azimuth follow-up coordinate system, the rotation motion direction of the AUV and z b′ The coordinate of the rotation radius under the azimuth follow-up horizontal coordinate system is
And z b′ The axis is negative when rotating anticlockwise in the reverse direction, and the coordinate of the gyration radius under the azimuth follow-up horizontal coordinate system is
Gamma is a roll angle when the AUV moves, and theta is a pitch angle when the AUV moves;
step 2, analyzing the system of the AUV rotary motion according to the characteristics of the AUV rotary motion, and constructing a lever arm error model suitable for a Kalman filtering algorithm;
and 2.1, analyzing the rotary motion system, wherein when the AUV does not have rolling and pitching motions, the linear speed at the C point of the carrier coordinate system is as follows:
while
So under the carrier coordinate system
Under the carrier system, the lever arm coordinate along the positive direction of the transverse rolling shaft of the carrier system of the AUV is
Linear velocity error under the carrier system at point a
Is composed of
Step 2.2, analyzing the rotary motion system, wherein pitching and rolling motions exist when the AUV does rotary motion, so that the rotary linear velocity of the AUV in the carrier coordinate system b is
Wherein
Arranged under an orientation follow-up horizontal coordinate system R DC Has the coordinates of
The rotational linear velocity of AUV under the carrier system is
And also
The output value of the DVL, i.e., the a-point velocity, is thus expressed as:
and the carrier system b is R CA Has the coordinates of
Namely, it is
To obtain
Suppose that
To obtain
Step 3, determining system state quantity and observation quantity, constructing a state equation and an observation equation, and performing optimal estimation on the lever arm length of the AUV according to Kalman filtering;
and 4, calibrating positioning errors of the positioning navigation system caused by the lever arm effect according to the optimal estimation of the length of the AUV lever arm.
2. The calibration method for the lever arm error of the AUV push navigation system according to claim 1, wherein the step 3 specifically comprises the following steps:
step 3.1 Lever arm Length
To be provided with
And establishing a Kalman filtering equation as a state variable of the system, wherein the state equation is as follows:
w is white Gaussian noise satisfying a zero-mean normal distribution, and the observation equation is
v is white gaussian noise satisfying a zero-mean normal distribution;
step 3.2, carrying out lever arm length R in the AUV positioning navigation system according to Kalman filtering CA And carrying out optimal estimation.
3. The calibration method for the lever arm error of the AUV push navigation system according to claim 2, wherein the step 4 specifically comprises the following steps:
step 4.1, obtaining the lever arm length R from step 3 CA To obtain the speed error at point A
Step 4.2, according to
The velocity of the point A is obtained
By compensating for speed error at point A
Obtaining the speed of C point line
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