CN112697143B - High-precision carrier dynamic attitude measurement method and system - Google Patents
High-precision carrier dynamic attitude measurement method and system Download PDFInfo
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Abstract
The invention provides a high-precision carrier dynamic attitude measurement method and system, which comprise two micro-electromechanical inertial measurement units, wherein one of the two micro-electromechanical inertial measurement units adopts a double-position reciprocating transposition mode, and the other micro-electromechanical inertial measurement unit adopts a mode of fixedly connecting with a carrier. Relative attitude, position and speed equivalent between the two micro-electromechanical inertia measurement units are introduced as new observed quantities, zero offset of gyros and accelerometers of the two micro-electromechanical inertia measurement units is effectively estimated, and therefore compensation can be better performed on the two systems. The micro-electromechanical inertia measurement unit fixedly connected with the carrier is used for attitude output inertial navigation, so that the phenomenon of peak jump of an attitude calculation result caused by reciprocating rotation of the first micro-electromechanical inertia measurement unit is successfully eliminated, and the accuracy of the whole system is improved. In the using process of the invention, accurate position information is not required to be introduced, so that satellite signals are not required to be introduced, and the system has better anti-interference performance, stability and concealment.
Description
Technical Field
The invention relates to the technical field of inertial navigation, in particular to a high-precision carrier dynamic attitude measurement method and system.
Background
The inertial navigation is a pure autonomous navigation mode which only depends on information of an inertial device without introducing external information and cannot radiate information to the outside, and has good anti-interference performance, reliability and concealment because the inertial navigation does not need the external information and cannot radiate signals to the outside, so that the inertial navigation technology becomes an important component in the navigation technical field and is widely applied to actual navigation tasks.
With the development of the inertial navigation technology, the inertial navigation system is increasingly developing towards miniaturization and high precision, and the micro-electromechanical inertial measurement unit gradually enters the field of vision of people due to the outstanding advantages of small volume, low power consumption and low price, so that the micro-electromechanical inertial measurement unit is widely applied to the field of current inertial navigation. The attitude measurement is an important application field of a strapdown inertial system, and the basic principle of the attitude measurement is to obtain attitude information of the carrier, such as course, roll, pitch and the like, by utilizing angular motion information of a gyroscope sensitive carrier through calculation and filtering, and further measure and control the attitude of the carrier.
At present, attitude information applied to various subsystems carried on a ship is transmitted by a main inertial navigation system on the ship, and because the deck of the offshore ship deforms, the attitude information obtained by the subsystems is inaccurate due to factors such as data transmission time delay between the main inertial navigation system and the subsystems. In order to solve the problem, a corresponding high-precision attitude measurement system is required to be assembled for each subsystem, but most of the conventional high-precision dynamic attitude measurement systems adopt high-precision systems (such as a fiber-optic gyroscope, a laser gyroscope and the like), are high in price and large in size, and are not beneficial to a large amount of equipment on a ship, so that weapon subsystems on the ship cannot own high-precision attitude measurement systems, and the attitude values of the subsystems are inaccurate.
At present, some existing methods have respective disadvantages, for example, a static micro-electromechanical inertia measurement unit is adopted, and the precision is low, so that the application requirements cannot be met. If the scheme of measuring the attitude by introducing satellite signals in a combined navigation mode is introduced, the system is easily interfered by the outside and has reduced reliability. If a single-axis rotation inertial measurement unit system is applied, the reciprocating rotation process of the system can cause the attitude calculation result to have peak jumping, so that the accuracy of the attitude calculation result is reduced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a high-precision carrier dynamic attitude measurement method and system. The invention reduces the volume, power consumption and cost of the attitude measurement system by adopting the micro-electromechanical inertial measurement unit, improves the accuracy of the attitude measurement system by the mode of the double micro-electromechanical inertial measurement units in coordination and transposition, and further provides real-time, stable and accurate attitude information for each subsystem on a ship.
In order to achieve the technical purpose, the invention adopts the technical scheme that:
the high-precision carrier dynamic attitude measurement method comprises the following steps:
(1) the carrier is provided with a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit, wherein the first micro-electromechanical inertia measurement unit is arranged on the carrier through a rotary table and can be driven by the rotary table to periodically rotate in a reciprocating manner, and the second micro-electromechanical inertia measurement unit is directly and fixedly connected to the carrier;
(2) respectively calibrating the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit;
(3) respectively carrying out coarse alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and taking data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit as navigation parameters obtained by first-time inertial navigation calculation during the coarse alignment;
(4) performing inertial navigation calculation at the current moment according to navigation parameters obtained by previous inertial navigation calculation, and if the first micro-electromechanical inertial measurement unit at the current moment is in a rotating state, performing filtering estimation on the second micro-electromechanical inertial measurement unit by applying a state transform Kalman filtering algorithm to obtain a carrier attitude value at the current moment, wherein the first micro-electromechanical inertial measurement unit only predicts the carrier attitude value and does not perform filtering; if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment;
(5) and (5) repeating the step (4) until the end.
Further, the rotation rule of the first micro-electromechanical inertia measurement unit is as follows
The two positions are rotated back and forth, and stay at each position for a preset time, wherein the preset time is 3 to 8 minutes.
Further, the method for marking in step (2) of the present invention comprises:
for the first micro-electromechanical inertia measurement unit
Position calibration is carried out, and a first micro-electromechanical inertia measurement unit is calibrated
The gyro scale factor and zero offset of the position, the accelerometer scale factor and zero offset, and the first micro-electromechanical inertial measurement unit are calibrated at the same time
Initial attitude angle at position and relative attitude relation with second micro-electromechanical inertial measurement unit
；
For the first micro-electromechanical inertia measurement unit
Position calibration is carried out, and a first micro-electromechanical inertia measurement unit is calibrated
The gyro scale factor and zero offset of the position, the accelerometer scale factor and zero offset, and the first micro-electromechanical inertial measurement unit are calibrated at the same time
Initial attitude angle at position and relative attitude relation with second micro-electromechanical inertial measurement unit
；
And calibrating the second micro-electromechanical inertia measurement unit, and calibrating the initial attitude angle, the gyro scale factor and the zero offset of the second micro-electromechanical inertia measurement unit and the accelerometer scale factor and the zero offset of the second micro-electromechanical inertia measurement unit.
Furthermore, in the step (4) of the invention, 30-dimensional state quantity is selected from the state transformation Kalman filtering algorithm, namely
The selected navigation coordinate system is a northeast coordinate system, wherein
Three attitude errors of the second micro-electromechanical inertial measurement unit are respectively a course angle error, a rolling angle error and a pitch angle error,
three speed errors of the second micro-electromechanical inertia measurement unit are respectively a north speed error, an east speed error and a ground speed error,
three position errors of the second micro-electromechanical inertia measurement unit are respectively longitude error, latitude error and altitude error,
three gyro errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis gyro, zero offset of a y-axis gyro and zero offset of a z-axis gyro,
the three accelerometer errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis accelerometer, zero offset of a y-axis accelerometer and zero offset of a z-axis accelerometer. While
Respectively a course angle error, a rolling angle error and a pitch angle error of the first micro-electromechanical inertia measurement unit,
respectively a north direction speed error, an east direction speed error and a ground direction speed error of the first micro-electromechanical inertia measurement unit,
respectively a longitude error, a latitude error and an altitude error of the first micro-electromechanical inertial measurement unit,
the zero offset of an x-axis gyroscope, the zero offset of a y-axis gyroscope and the zero offset of a z-axis gyroscope of the first micro-electromechanical inertial measurement unit respectively;
selecting 15-dimensional observed quantity from state transformation Kalman filtering algorithm
Wherein
, 
,
Three speed values of the second micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
,
,
three speed values of the first micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
,
,
three speed values of the carrier in the north direction, the east direction and the ground direction,
the difference values of three attitude values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three speed values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three position values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively.
The state equation and the observation equation in the state transformation Kalman filtering algorithm are as follows:
wherein
Is a derivative of the selected state quantity;F(t) Is a state transition matrix;x(t) Is the selected state quantity;G(t) Is a process noise distribution matrix;w(t) Is process noise;z(t) Is an observed quantity;H(t) Is an observation matrix;v(t) To observe the noise.
According to the invention, when the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit are both in a static state, the difference value between the north speed of the first inertia measurement unit and the carrier speed is selected
The difference between the east velocity of the first inertial measurement unit and the velocity of the carrier
The difference between the ground speed of the first inertial measurement unit and the ground phase speed of the carrier
The difference between the north velocity of the second inertial measurement unit and the velocity of the carrier
The difference between the east speed and the carrier speed of the second inertial measurement unit
The difference between the ground speed of the second inertial measurement unit and the ground phase speed of the carrier
On the basis of observed quantity, the difference value of the north direction speed between two sets of micro-electromechanical inertia measurement units is selected by adding
East velocity difference
Difference of ground speed
Angle difference of course
Difference of transverse rolling angle
Differential value of pitch angle
Longitude difference, longitude difference
Difference in latitude
Difference in height
The Kalman filtering observation correction is carried out on the observed quantity, and due to the introduction of the difference observed quantity between the two sets of micro-electromechanical inertia measuring units, the gyro zero offset and the adding table zero offset of the two sets of micro-electromechanical inertia measuring units can be estimated, so that the gyro zero offset and the accelerometer zero offset of the two sets of micro-electromechanical inertia measuring units are estimated by the method, wherein the gyro zero offset and the accelerometer zero offset of the first micro-electromechanical inertia measuring unit respectively comprise the following state quantities:
respectively an x-axis gyroscope zero offset, a y-axis gyroscope zero offset and a z-axis gyroscope zero offset of the first micro-electromechanical inertial measurement unit,
the zero offset of an x-axis accelerometer, the zero offset of a y-axis accelerometer and the zero offset of a z-axis accelerometer of the first micro-electromechanical inertial measurement unit respectively; the gyro zero offset and the accelerometer zero offset of the second inertia micro-electromechanical inertia measurement unit respectively comprise the following state quantities:
respectively an x-axis gyroscope zero offset, a y-axis gyroscope zero offset and a z-axis gyroscope zero offset of the second micro-electromechanical inertial measurement unit,
the zero offset of an x-axis accelerometer, the zero offset of a y-axis accelerometer and the zero offset of a z-axis accelerometer of the second micro-electromechanical inertial measurement unit are respectively. Meanwhile, the gyro zero offset value and the accelerometer zero offset value are subtracted from the original data of the two sets of micro-electromechanical inertia measurement units, and then the following inertial navigation calculation and filtering are carried out continuously, so that the gyro zero offset and the accelerometer zero offset values of the two sets of micro-electromechanical inertia measurement units which are estimated finally tend to be flat in a reciprocating manner, and the attitude value output by the second micro-electromechanical inertia measurement unit is the accurate carrier attitude value, namely the roll angle
And a pitch angle
Angle of course
。
The invention also provides a high-precision carrier dynamic attitude measurement system, which comprises:
the micro-electromechanical inertia measurement system comprises a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit, wherein the first micro-electromechanical inertia measurement unit is arranged on a carrier through a rotary table and can periodically rotate back and forth under the drive of the rotary table, and the second micro-electromechanical inertia measurement unit is directly and fixedly connected to the carrier;
the data acquisition module is respectively connected with the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit and is used for acquiring data from the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit,
the calibration module is used for respectively calibrating the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit;
the rough alignment module is used for respectively carrying out rough alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit during rough alignment is used as navigation parameters obtained by first inertial navigation calculation;
the attitude calculation module is used for performing inertial navigation calculation at the current moment according to navigation parameters obtained by previous inertial navigation calculation, and if the first micro-electromechanical inertial measurement unit at the current moment is in a rotating state, filtering estimation is performed on the second micro-electromechanical inertial measurement unit by applying a state transformation Kalman filtering algorithm to obtain a carrier attitude value at the current moment, and the first micro-electromechanical inertial measurement unit only predicts the carrier attitude value and does not perform filtering; and if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment.
Further, the data acquisition module is realized based on an FPGA.
Furthermore, the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit are respectively composed of three gyroscopes and three accelerometers, and the three gyroscopes and the three accelerometers are respectively assembled in a mode that three axes are perpendicular to each other.
Further, the rotation rule of the first micro-electromechanical inertia measurement unit is
The two positions are rotated back and forth, each position is stopped for a set time, such as 5 minutes.
Furthermore, the first micro-electromechanical inertia measurement unit is fixedly connected with the rotary table through a standard fastening screw, so that the first micro-electromechanical inertia measurement unit and the rotary table can be fully ensured to rotate synchronously. The Z axis of the first micro-electromechanical inertia measurement unit is collinear with the rotating axis of the rotary table, and the rotary table stops after initialization is completed
And the position, the X axis, the Y axis and the Z axis of the micro-electromechanical inertia measurement unit form a right-hand system.
Compared with the prior art, the invention has the following advantages:
the basic measuring device is a micro-electromechanical inertial measuring unit, has small volume, low price and low power consumption, and effectively solves the problems of large volume, high cost and high power consumption of the existing high-precision attitude measuring system;
the invention adopts a mode of double micro-electromechanical inertia measurement units for coordinated transposition, wherein one of the two micro-electromechanical inertia measurement units adopts
The other adopts a mode of fixedly connecting with the carrier. Wherein the first micro-electromechanical inertial measurement unit rotates due to the use of
The two-position reciprocating transposition mode can effectively modulate the gyro constant drift and the accelerometer zero offset which are vertical to the rotating shaft, and the two parts are continuously increased along with the accumulation of time to cause the dispersion of attitude errors, so the invention can effectively improve the attitude measurement precision of the system;
in the application process of the single-axis rotating micro-electromechanical inertia measurement unit system, the reciprocating rotation process of the system can cause the peak jump of the attitude calculation result, so that the accuracy of the attitude calculation result is reduced. The invention introduces the relative attitude, position and speed equivalent between the first micro-electromechanical inertial measurement unit and the second micro-electromechanical inertial measurement unit as new observed quantities, selects the corresponding gyro zero-offset and accelerometer zero-offset as Kalman filtering state quantities, estimates the gyro zero-offset and accelerometer zero-offset through Kalman filtering, thereby effectively estimating the gyro and accelerometer zero-offset of the two micro-electromechanical inertial measurement units, subtracts the gyro and accelerometer zero-offset on the basis of the original gyro data and acceleration data, and then sequentially carries out inertial navigation calculation and filtering estimation at the next moment, thereby realizing the correction and compensation of the system. And because the second micro-electromechanical inertia measurement unit is adopted to output inertial navigation for the attitude, the phenomenon that the peak jump occurs in the attitude calculation result caused by the reciprocating rotation of the first micro-electromechanical inertia measurement unit is successfully eliminated, and the accuracy of the whole system is improved.
Because the system does not need to introduce accurate position information in the application process, satellite signals do not need to be introduced, and the anti-interference performance and the reliability of the system are greatly improved.
Drawings
FIG. 1 is a schematic structural diagram of a high-precision carrier dynamic attitude measurement system according to an embodiment of the present invention;
FIG. 2 is a schematic view of an assembly structure of a first MEMS inertial measurement unit and a turntable according to an embodiment of the present invention;
FIG. 3 is a schematic view of a first MEMS inertial measurement unit according to an embodiment of the invention
Location arrival
A schematic rotational direction of position;
FIG. 4 is a schematic view of a first MEMS inertial measurement unit according to an embodiment of the invention
Location arrival
A schematic rotational direction of position;
fig. 5 is a flow chart of high-precision carrier dynamic attitude measurement according to an embodiment of the invention.
Detailed Description
For the purpose of promoting a clear understanding of the objects, aspects and advantages of the embodiments of the invention, reference will now be made to the drawings and detailed description, wherein there are shown in the drawings and described in detail, various modifications of the embodiments described herein, and other embodiments of the invention will be apparent to those skilled in the art. The exemplary embodiments of the present invention and the description thereof are provided to explain the present invention and not to limit the present invention.
At present, attitude information applied to various subsystems carried on a ship is transmitted by a main inertial navigation system on the ship, because the deck of the offshore ship is deformed, the attitude information obtained by the subsystems is inaccurate due to factors such as data transmission time delay between the main inertial navigation system and the subsystems and the like, in order to solve the problem, a corresponding high-precision attitude measuring system is required to be assembled on each subsystem, but if high-precision inertial navigation devices (such as a laser gyro, a fiber-optic gyro and the like) are adopted, the size is huge, the cost is relatively high, and the system is unrealistic,
according to the embodiment, the micro-electromechanical inertia measurement unit with relatively low price, smaller volume and lower power consumption is adopted, and the purpose of assembling a high-precision attitude measurement system for various subsystems carried on a ship is realized in a mode of double micro-electromechanical inertia measurement units in a coordinated transposition mode, so that the attitude precision of each subsystem is improved.
Referring to fig. 1, a high-precision carrier dynamic attitude measurement system includes:
the measurement device comprises a first micro-electromechanical inertia measurement unit 1 and a second micro-electromechanical inertia measurement unit 2, wherein the first micro-electromechanical inertia measurement unit 1 is installed on a carrier through a rotary table 101 and can periodically rotate back and forth under the drive of the rotary table, and the second micro-electromechanical inertia measurement unit 2 is directly and fixedly connected to the carrier;
the data acquisition module 3 is respectively connected with the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit and is used for acquiring data from the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit,
the calibration module is used for respectively calibrating the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit;
the rough alignment module is used for respectively carrying out rough alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit during rough alignment is used as navigation parameters obtained by first inertial navigation calculation;
the attitude calculation module 4 is used for performing inertial navigation calculation at the current moment according to navigation parameters obtained by inertial navigation calculation of a first micro-electromechanical inertial measurement unit and a second micro-electromechanical inertial measurement unit at the previous time during carrier dynamic attitude measurement, and if the first micro-electromechanical inertial measurement unit at the current moment is in a rotating state, filtering estimation is performed on the second micro-electromechanical inertial measurement unit by applying a state transformation Kalman filtering algorithm to obtain a carrier attitude value at the current moment, and the first micro-electromechanical inertial measurement unit only predicts the carrier attitude value and does not perform filtering; and if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment.
Wherein, the sequence of inertial navigation resolving is speed updating, position updating and attitude updating. Firstly, the attitude obtained by the previous inertial navigation solution is utilized to carry out specific force projection, and then gemini is utilized
Carrying out speed updating by a sample rowing effect compensation algorithm; updating the position information by applying the latest speed obtained by the inertial navigation solution at the current moment; and (3) calculating and updating the obtained speed and position information by using the inertial navigation at the current moment, and updating to obtain the current attitude information by using a double-subsample cone compensation algorithm. And applying the speed, position and attitude information obtained by inertial navigation resolving and updating at the current moment, and applying a state transform Kalman filtering algorithm to carry out filtering estimation through the selected state quantity and the observed quantity so as to estimate an attitude error value of the carrier, thereby realizing real-time resolving of the carrier attitude and obtaining a carrier attitude value at the current moment.
The data acquisition module in this embodiment is implemented by an FPGA. The gyro zero offset and the adding table zero offset of the two sets of micro-electromechanical inertia measurement units are estimated by utilizing the first micro-electromechanical inertia measurement unit to modulate the gyro constant drift and the accelerometer zero offset in the first micro-electromechanical inertia measurement unit in the direction vertical to the rotating shaft of the rotary table through periodic reciprocating rotation, introducing information such as relative position, speed, attitude and the like between the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit as new observed quantities on the basis of taking the respective speeds of the two sets of micro-electromechanical inertia measurement units as the observed quantities, and further improving the attitude measurement precision of the system.
The first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit are respectively composed of three gyroscopes and three accelerometers, and the three gyroscopes and the three accelerometers are respectively assembled in a mode that three axes are perpendicular to each other.
The rotation rule of the first micro-electromechanical inertia measurement unit is
The two positions were rotated back and forth, each position staying for 5 minutes. The assembly structure of the first micro-electromechanical inertia measurement unit and the rotary table is shown in figure 2, the rotary table 5 is driven to rotate by a driving motor, the driving motor is installed in a rotary table base 6, the output end of the driving motor is connected with the rotary table 5, the first micro-electromechanical inertia measurement unit 1 is fixedly connected with the rotary table 5 through a standard fastening screw, and the rotation synchronism between the first micro-electromechanical inertia measurement unit and the rotary table is fully guaranteed. The Z axis of the first micro-electromechanical inertia measurement unit is collinear with the rotating axis of the rotary table, and the rotary table stops after initialization is completed
And the position, the X axis, the Y axis and the Z axis of the micro-electromechanical inertia measurement unit form a right-hand system. In that
After the position is stopped for five minutes, the turntable rotates clockwise (from the top view) around the rotation axis
Location arrival
Position as shown in fig. 3. In that
After the position has been parked for another five minutes, the turntable is rotated counter-clockwise (from the top view) about the axis of rotation, from the position
Arrive at
Position, as shown in fig. 4, so as to reciprocate.
Before the high-precision carrier dynamic attitude measurement system is used, firstly, a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit in the system are calibrated, wherein the calibration is divided into two processes, and the first micro-electromechanical inertia measurement unit is fixed on the first micro-electromechanical inertia measurement unit
The position is calibrated, and then the first micro-electromechanical inertia measurement unit is fixed
The position is calibrated, the second micro-electromechanical inertia measurement unit is also calibrated in the process, and the first micro-electromechanical inertia measurement unit is respectively calibrated
The position,
A gyro scale factor and zero offset, an accelerometer scale factor and zero offset for the location, a gyro scale factor and zero offset, an accelerometer scale factor and zero offset for the second microelectromechanical inertial measurement unit, and the first microelectromechanical inertial measurement unit at
Relative attitude relationship between the position and the second micro-electromechanical inertial measurement unit
And a first microelectromechanical inertial measurement unit
Relative attitude relationship between the position and the second micro-electromechanical inertial measurement unit
。
Referring to fig. 5, the high-precision carrier dynamic attitude measurement method includes the following steps:
(1) the carrier is provided with a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit, wherein the first micro-electromechanical inertia measurement unit is arranged on the carrier through a rotary table and can be driven by the rotary table to periodically rotate in a reciprocating manner, and the second micro-electromechanical inertia measurement unit is directly and fixedly connected to the carrier; the rotation rule of the first micro-electromechanical inertia measurement unit is
The two positions were rotated back and forth, each position staying for 5 minutes.
(2) The first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit are respectively calibrated, and the calibration method is clearly described in the foregoing and is not described in detail herein.
(3) Respectively carrying out coarse alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and taking data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit as navigation parameters obtained by first-time inertial navigation calculation during the coarse alignment;
(4) and performing inertial navigation calculation at the current moment according to the navigation parameters obtained by the previous inertial navigation calculation. The inertial navigation solution is 0.01s, the navigation parameters obtained in the course of coarse alignment are applied to the first inertial navigation solution, and the navigation parameters obtained in the previous inertial navigation solution (namely the navigation parameters obtained by the previous state transformation Kalman filtering estimation) are applied to the next inertial navigation solution each time. If the first micro-electromechanical inertia measurement unit is in a rotating state at the current moment, filtering estimation is carried out on the second micro-electromechanical inertia measurement unit by applying a state transformation Kalman filtering algorithm to obtain a carrier attitude value at the current moment, and the first micro-electromechanical inertia measurement unit only predicts the carrier attitude value without filtering; and if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment.
(5) And (5) repeating the step (4) until the navigation is finished. In an embodiment of the present invention, the rotation rule of the first mems inertial measurement unit is
The two positions are rotated back and forth and allowed to dwell at each position for a predetermined time, such as 5 minutes.
Based on the basic theory of inertial navigation, the invention selects 30-dimensional state quantity by using STEKF (state transform Kalman filtering)
Wherein
Three attitude errors of the second micro-electromechanical inertial measurement unit are respectively a course angle error, a rolling angle error and a pitch angle error,
three speed errors of the second micro-electromechanical inertia measurement unit are respectively a north speed error, an east speed error and a ground speed error,
three position errors of the second micro-electromechanical inertia measurement unit are respectively longitude error, latitude error and altitude error,
three gyro errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis gyro, zero offset of a y-axis gyro and zero offset of a z-axis gyro,
the three accelerometer errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis accelerometer, zero offset of a y-axis accelerometer and zero offset of a z-axis accelerometer. While
Respectively a course angle error, a rolling angle error and a pitch angle error of the first micro-electromechanical inertia measurement unit,
respectively a north direction speed error, an east direction speed error and a ground direction speed error of the first micro-electromechanical inertia measurement unit,
respectively a longitude error, a latitude error and an altitude error of the first micro-electromechanical inertial measurement unit,
respectively an x-axis gyroscope zero offset, a y-axis gyroscope zero offset and a z-axis gyroscope zero offset of the first micro-electromechanical inertial measurement unit,
the zero offset of the x-axis accelerometer, the zero offset of the y-axis accelerometer and the zero offset of the z-axis accelerometer of the first micro-electromechanical inertial measurement unit are respectively.
For the selection of the observed quantity, the invention selects the 15-dimensional observed quantity, namely
Wherein
, 
,
Three speed values of the second micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
, 
,
three speed values of the first micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
, 
,
three speed values of the carrier in the north direction, the east direction and the ground direction,
the difference values of three attitude values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three speed values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
respectively a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unitDifference of three position values.
The state equation and the observation equation in the state transformation Kalman filtering algorithm are as follows:
wherein
Is a derivative of the selected state quantity;F(t) Is a state transition matrix;x(t) Is the selected state quantity;G(t) Is a process noise distribution matrix;w(t) Is process noise;z(t) Is an observed quantity;H(t) Is an observation matrix;v(t) To observe the noise.
In an embodiment of the present invention, the inertial navigation solution sequence includes velocity update, position update, and attitude update. Firstly, carrying out specific force projection by utilizing attitude information in navigation parameters obtained by previous inertial navigation calculation (the attitude information applied by the first inertial navigation calculation is the attitude information obtained by rough alignment), and then updating speed information by utilizing a double-subsample rowing effect compensation algorithm. And then, updating the position information by applying the latest speed obtained by the inertial navigation calculation. And then, the current attitude information is obtained by updating by applying the velocity information and the position information obtained by the inertial navigation solution and by using a double-subsample cone compensation algorithm. And finally, applying the speed, position and attitude information obtained by inertial navigation resolving and updating, and applying a state transform Kalman filtering algorithm to carry out filtering estimation through the selected state quantity and the observed quantity, thereby estimating the attitude error value of the carrier and further realizing the real-time resolving of the carrier attitude.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (9)
1. The high-precision carrier dynamic attitude measurement method is characterized by comprising the following steps:
(1) the carrier is provided with a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit, wherein the first micro-electromechanical inertia measurement unit is arranged on the carrier through a rotary table and can be driven by the rotary table to periodically rotate in a reciprocating manner, and the second micro-electromechanical inertia measurement unit is directly and fixedly connected to the carrier;
(2) respectively calibrating the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit;
(3) respectively carrying out coarse alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and taking data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit as navigation parameters obtained by first-time inertial navigation calculation during the coarse alignment;
(4) performing inertial navigation calculation at the current moment according to navigation parameters obtained by previous inertial navigation calculation, and if the first micro-electromechanical inertial measurement unit at the current moment is in a rotating state, performing filtering estimation on the second micro-electromechanical inertial measurement unit by applying a state transform Kalman filtering algorithm to obtain a carrier attitude value at the current moment, wherein the first micro-electromechanical inertial measurement unit only predicts the carrier attitude value and does not perform filtering; if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment; wherein 30-dimensional state quantities are selected from the state transform Kalman filtering algorithm
Wherein
Three attitude errors of the second micro-electromechanical inertial measurement unit are respectively a course angle error, a rolling angle error and a pitch angle error,
three speed errors of the second micro-electromechanical inertia measurement unit are respectively a north speed error, an east speed error and a ground speed error,
three position errors of the second micro-electromechanical inertia measurement unit are respectively longitude error, latitude error and altitude error,
three gyro errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis gyro, zero offset of a y-axis gyro and zero offset of a z-axis gyro,
three accelerometer errors of the second micro-electromechanical inertial measurement unit are respectively zero offset of an x-axis accelerometer, zero offset of a y-axis accelerometer and zero offset of a z-axis accelerometer; while
Respectively a course angle error, a rolling angle error and a pitch angle error of the first micro-electromechanical inertia measurement unit,
respectively a north direction speed error, an east direction speed error and a ground direction speed error of the first micro-electromechanical inertia measurement unit,
respectively a longitude error, a latitude error and an altitude error of the first micro-electromechanical inertial measurement unit,
respectively an x-axis gyroscope zero offset, a y-axis gyroscope zero offset and a z-axis gyroscope zero offset of the first micro-electromechanical inertial measurement unit,
the zero offset of an x-axis accelerometer, the zero offset of a y-axis accelerometer and the zero offset of a z-axis accelerometer of the first micro-electromechanical inertial measurement unit respectively;
selecting 15-dimensional observed quantity from state transformation Kalman filtering algorithm
Wherein
Three speed values of the second micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
three speed values of the first micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
three speed values of the carrier in the north direction, the east direction and the ground direction,
the difference values of three attitude values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three speed values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three position values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively obtained;
the state equation and the observation equation in the state transformation Kalman filtering algorithm are as follows:
wherein
Is a derivative of the selected state quantity;F(t) Is a state transition matrix;x(t) Is the selected state quantity;G(t) Is a process noise distribution matrix;w(t) Is process noise;z(t) Is an observed quantity;H(t) Is an observation matrix;v(t) To observe noise;
(5) and (5) repeating the step (4) until the end.
2. The method as claimed in claim 1, wherein the first MEMS inertial measurement unit has a rotation rule of
The two positions are rotated back and forth and stay at each position for a preset time.
3. The method of claim 2, wherein the predetermined time is 3 to 8 minutes.
4. The high-precision carrier dynamic attitude measurement method according to claim 2, wherein the calibration method in step (2) includes:
for the first micro-electromechanical inertia measurement unit
Position calibration is carried out, and a first micro-electromechanical inertia measurement unit is calibrated
The gyro scale factor and zero offset of the position, the accelerometer scale factor and zero offset, and the first micro-electromechanical inertial measurement unit are calibrated at the same time
Initial attitude angle at position and relative attitude relation with second micro-electromechanical inertial measurement unit
；
For the first micro-electromechanical inertia measurement unit
Position calibration is carried out, and a first micro-electromechanical inertia measurement unit is calibrated
The gyro scale factor and zero offset of the position, the accelerometer scale factor and zero offset, and the first micro-electromechanical inertial measurement unit are calibrated at the same time
Initial attitude angle at position and relative attitude relation with second micro-electromechanical inertial measurement unit
；
And calibrating the second micro-electromechanical inertia measurement unit, and calibrating the initial attitude angle, the gyro scale factor and the zero offset of the second micro-electromechanical inertia measurement unit and the accelerometer scale factor and the zero offset of the second micro-electromechanical inertia measurement unit.
5. High accuracy carrier dynamic attitude measurement system, its characterized in that includes:
the micro-electromechanical inertia measurement system comprises a first micro-electromechanical inertia measurement unit and a second micro-electromechanical inertia measurement unit, wherein the first micro-electromechanical inertia measurement unit is arranged on a carrier through a rotary table and can periodically rotate back and forth under the drive of the rotary table, and the second micro-electromechanical inertia measurement unit is directly and fixedly connected to the carrier;
the data acquisition module is respectively connected with the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit and is used for acquiring data from the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit,
the calibration module is used for respectively calibrating the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit;
the rough alignment module is used for respectively carrying out rough alignment on the calibrated first micro-electromechanical inertia measurement unit and the calibrated second micro-electromechanical inertia measurement unit, and data output by the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit during rough alignment is used as navigation parameters obtained by first inertial navigation calculation;
the attitude calculation module is used for performing inertial navigation calculation at the current moment according to navigation parameters obtained by previous inertial navigation calculation, and if the first micro-electromechanical inertial measurement unit at the current moment is in a rotating state, filtering estimation is performed on the second micro-electromechanical inertial measurement unit by applying a state transformation Kalman filtering algorithm to obtain a carrier attitude value at the current moment, and the first micro-electromechanical inertial measurement unit only predicts the carrier attitude value and does not perform filtering; if the first micro-electromechanical inertia measurement unit is in a static state at the current moment, simultaneously applying a state transformation Kalman filtering algorithm to the first micro-electromechanical inertia measurement unit and the second micro-electromechanical inertia measurement unit for filtering estimation to obtain a carrier attitude value at the current moment, wherein 30-dimensional state quantity is selected from the state transformation Kalman filtering algorithm, namely the state quantity is selected
Wherein
Three attitude errors of the second micro-electromechanical inertial measurement unit are respectively a course angle error, a rolling angle error and a pitch angle error,
three speed errors of the second micro-electromechanical inertia measurement unit are respectively a north speed error, an east speed error and a ground speed error,
three position errors of the second micro-electromechanical inertia measurement unit are respectively longitude error, latitude error and altitude error,
three gyro errors of the second micro-electromechanical inertia measurement unit are respectively zero offset of an x-axis gyro, zero offset of a y-axis gyro and zero offset of a z-axis gyro,
three accelerometer errors of the second micro-electromechanical inertial measurement unit are respectively zero offset of an x-axis accelerometer, zero offset of a y-axis accelerometer and zero offset of a z-axis accelerometer; while
Respectively the course angle error of the first micro-electromechanical inertia measurement unit,Rolling angle error and pitch angle error,
respectively a north direction speed error, an east direction speed error and a ground direction speed error of the first micro-electromechanical inertia measurement unit,
respectively a longitude error, a latitude error and an altitude error of the first micro-electromechanical inertial measurement unit,
respectively an x-axis gyroscope zero offset, a y-axis gyroscope zero offset and a z-axis gyroscope zero offset of the first micro-electromechanical inertial measurement unit,
the zero offset of an x-axis accelerometer, the zero offset of a y-axis accelerometer and the zero offset of a z-axis accelerometer of the first micro-electromechanical inertial measurement unit respectively;
selecting 15-dimensional observed quantity from state transformation Kalman filtering algorithm
Wherein
Three speed values of the second micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
three speed values of the first micro-electromechanical inertia measurement unit in the north direction, the east direction and the ground direction,
three speed values of the carrier in the north direction, the east direction and the ground direction,
the difference values of three attitude values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three speed values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively,
the difference values of the three position values of the first micro-electromechanical inertia measuring unit and the second micro-electromechanical inertia measuring unit are respectively obtained;
the state equation and the observation equation in the state transformation Kalman filtering algorithm are as follows:
wherein
Is a derivative of the selected state quantity;F(t) Is a state transition matrix;x(t) Is the selected state quantity;G(t) Is a process noise distribution matrix;w(t) Is process noise;z(t) Is an observed quantity;H(t) Is an observation matrix;v(t) To observe the noise.
6. The high-precision carrier dynamic attitude measurement system of claim 5, wherein the data acquisition module is implemented based on an FPGA.
7. The high accuracy carrier dynamic attitude measurement system of claim 5, wherein the first and second microelectromechanical inertial measurement units are each composed of three gyroscopes and three accelerometers, respectively, and the three gyroscopes and the three accelerometers are each assembled in such a manner that three axes are perpendicular to each other.
8. A high precision carrier dynamic attitude measurement system as claimed in claim 5, 6 or 7, characterized in that the rotation rule of the first microelectromechanical inertial measurement unit is
The two positions rotate back and forth, and each position stays for a set time.
9. The high accuracy carrier dynamic attitude measurement system of claim 8, wherein the first microelectromechanical inertial measurement unit is secured to the turntable by standard fastening screws, the first microelectromechanical inertial measurement unit rotating synchronously with the turntable.
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